Glossary

52-Week High is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses 52-Week High alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

52-Week Low is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses 52-Week Low alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Accrual Ratio is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Accrual Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Accrued Interest is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Accrued Interest alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Active Addresses is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Active Addresses alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Adaptive Allocation is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies adaptive allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Adaptive Alpha is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies adaptive alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Adaptive Attribution is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies adaptive attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Address Reuse is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Address Reuse alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Adverse Selection is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Adverse Selection alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Agency Bond is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Agency Bond alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Airdrop is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Airdrop alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Algorithmic Allocation is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies algorithmic allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Algorithmic Alpha is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies algorithmic alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Algorithmic Attribution is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies algorithmic attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

All-Time High is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses All-Time High alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

All-Time Low is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses All-Time Low alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Excess return above a benchmark. Positive alpha indicates outperformance; negative alpha indicates underperformance.

A fund returning 12% when its benchmark returned 10% has generated 2% alpha.

Altcoin is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Altcoin alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

American Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses American Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

AMM (Automated Market Maker) is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses AMM (Automated Market Maker) alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Amortization is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Amortization alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

APR is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses APR alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

APY is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses APY alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Simultaneous buying and selling of identical securities in different markets to profit from price discrepancies.

Buying a stock at $100 on NYSE and selling at $101 on NASDAQ locks in 1% profit.

Asian Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Asian Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Asset Allocation is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Asset Allocation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Asset-Backed Security is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Asset-Backed Security alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Asset-Based Valuation is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Asset-Based Valuation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Asymmetric Allocation is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies asymmetric allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Asymmetric Alpha is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies asymmetric alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Asymmetric Attribution is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies asymmetric attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

At-the-Money Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses At-the-Money Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Auction Imbalance is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Auction Imbalance alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Autocorrelation is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Autocorrelation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Average Daily Volume is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Average Daily Volume alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Average Life is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Average Life alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Testing a trading strategy using historical data to evaluate performance before deploying with real capital.

We backtest strategies over 20 years of market data to assess robustness.

Balance of Payments is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Balance of Payments alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Barrier Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Barrier Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Basis Point Value is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Basis Point Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

One hundredth of a percent (0.01%). Used to describe small changes in interest rates, bond yields, and fees.

A fund fee increase of 25 basis points is a 0.25% increase.

Basis Trade is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Basis Trade alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Bayes Factor is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Bayes Factor alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Bayesian Allocation is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies bayesian allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Bayesian Alpha is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies bayesian alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Bayesian Attribution is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies bayesian attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Bayesian Updating is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Bayesian Updating alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Extended period when securities prices are falling and investor sentiment is negative.

2008 financial crisis was a severe bear market with 50%+ declines.

Behavioral Allocation is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies behavioral allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Behavioral Alpha is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies behavioral alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Behavioral Attribution is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies behavioral attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Benchmark is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Benchmark alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from setting price benchmarks that others follow.

Dominant firms in commodity markets can influence global pricing.

Measure of a security's volatility relative to the market. Beta of 1.0 means it moves with the market; >1.0 is more volatile; <1.0 is less volatile.

A stock with beta of 1.5 is expected to move 1.5% for every 1% market movement.

Difference between the bid price (buyer price) and ask price (seller price) for a security.

A stock with bid of $99.50 and ask of $99.75 has a 0.25 spread.

Mathematical model for pricing European options based on stock price, volatility, and time to expiration.

The Black-Scholes formula determines option prices from market conditions.

Block is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Block alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Block Reward is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Block Reward alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Block Time is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Block Time alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Blockchain is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Blockchain alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Bond Convexity is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Bond Convexity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Bond Duration is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Bond Duration alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Bond Ladder is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Bond Ladder alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Total assets minus total liabilities, representing the company's equity on balance sheet.

A company with $1B in assets and $300M in liabilities has $700M book value.

Book-to-Market Ratio is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Book-to-Market Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Bootstrapping is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Bootstrapping alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Borrow Rate is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Borrow Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Borrow Utilization is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Borrow Utilization alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage created when consumers trust and prefer a brand due to reputation and quality perception.

Coca-Cola's brand trust allows premium pricing despite commodity-like product.

Price level where a position has zero profit or loss, often used for options.

A call option with strike 100 and premium 5 has breakeven at price 105.

Bridge is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Bridge alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Bridge Volume is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Bridge Volume alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Extended period when securities prices are rising and investor sentiment is positive.

The 2010-2020 period was a long bull market with rising stock prices.

Business Cycle is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Business Cycle alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Buyback Yield is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Buyback Yield alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Calendar Spread is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Calendar Spread alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Contract giving the holder the right (but not obligation) to buy an asset at a specified price.

A call option on Apple stock with $150 strike gives the right to buy AAPL at $150.

Callable Bond is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Callable Bond alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from limited production capacity that controls supply in market.

TSMC's limited chip manufacturing capacity creates pricing power.

Moat from economies of scale in capital-intensive manufacturing with technical expertise.

Samsung's massive chip fabrication plants lower per-unit costs vs competitors.

Capital Allocation is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies capital allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Capital Alpha is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies capital alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Capital Attribution is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies capital attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Capital Expenditure is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Capital Expenditure alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Capital Intensity Barrier is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Capital Intensity Barrier alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Capital Preservation is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Capital Preservation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Carry and Roll is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Carry and Roll alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Carry Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Carry Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Cash Flow from Operations is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Cash Flow from Operations alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Cash-Settled Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Cash-Settled Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Circulating Supply is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Circulating Supply alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from controlling payment clearing and settlement systems.

Visa and Mastercard control critical payment infrastructure.

Closing Auction is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Closing Auction alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Ratio of standard deviation to mean return, measuring risk per unit of return.

Portfolio with 10% return and 5% volatility has CV of 0.5.

Coin Days Destroyed is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Coin Days Destroyed alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Cointegration is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Cointegration alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Cold Storage is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Cold Storage alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Collar is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Collar alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Buy protective put and sell covered call to reduce downside risk while capping upside gains.

Own 100 shares, buy put to protect against 10 percent drop, sell call to limit gains to 10 percent profit.

Collateral Factor is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Collateral Factor alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Collateralization Ratio is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Collateralization Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Commercial Paper is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Commercial Paper alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Common Shares Outstanding is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Common Shares Outstanding alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Common-Size Statement is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Common-Size Statement alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Community Governance Moat is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Community Governance Moat alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Comparable Company Analysis is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Comparable Company Analysis alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from existing compliance infrastructure that competitors must replicate.

Banks with established regulatory frameworks make it hard for fintech competitors.

Annualized rate of growth accounting for compounding over multiple periods.

An investment growing from $10,000 to $20,000 in 5 years has 14.9% CAGR.

Concentration Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Concentration Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from government-granted exclusive rights or concessions.

Casino licenses limiting competition in specific jurisdictions.

Concession Rights is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Concession Rights alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Conditional Value at Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Conditional Value at Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Consensus Mechanism is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Consensus Mechanism alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Consumer Price Index is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Consumer Price Index alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Advantage from owning exclusive content rights and intellectual property.

Disney's content library creates durable competitive advantage for streaming.

Moat created by exclusive contracts that prevent competitors from accessing customers.

Exclusive distribution agreements give preferred access to key retailers.

Convexity Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Convexity Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Core Inflation is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Core Inflation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Core-Satellite Strategy is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Core-Satellite Strategy alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Statistical measure of how two assets move together. Ranges from -1 (inverse) to +1 (perfectly correlated).

Stocks and bonds typically have low or negative correlation, making them good portfolio diversifiers.

Correlation Allocation is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies correlation allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Correlation Alpha is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies correlation alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Correlation Breakdown is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Correlation Breakdown alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Statistical measure between -1 and +1 showing how two variables move together.

Stocks and bonds often have negative correlation, moving in opposite directions.

Moat from lower cost of capital due to creditworthiness or investor preference.

Apple's strong credit rating gives it lower borrowing costs than competitors.

Cost of Capital Advantage is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Cost of Capital Advantage alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Cost of Equity is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Cost of Equity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Counter-Positioning is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Counter-Positioning alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Counterparty Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Counterparty Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Annual interest rate paid by bond issuer, expressed as percentage of par value.

A bond with 4% coupon pays $40 annually on $1,000 par value.

Covered Call is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Covered Call alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Credit Default Swap is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Credit Default Swap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Credit Rating Migration is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Credit Rating Migration alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Credit Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Credit Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Credit Spread is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Credit Spread alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Cross-Asset Allocation is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies cross-asset allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Cross-Asset Alpha is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies cross-asset alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Cross-Asset Attribution is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies cross-asset attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Cross-Asset Portfolio is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Cross-Asset Portfolio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Cross-Chain Messaging is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Cross-Chain Messaging alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Cross-Validation is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Cross-Validation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Crossed Market is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Crossed Market alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Total gain or loss from investing over an entire period, not annualized.

An investment with 5% annual return for 2 years has 10.25% cumulative return.

Currency Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Currency Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Current Account is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Current Account alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Current Ratio is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Current Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Current Yield is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Current Yield alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Custody is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Custody alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat created by customized solutions tailored to specific customer needs, making switching difficult.

Specialized software built for a company's unique workflow creates switching costs.

Customer Habit is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Customer Habit alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Dark Pool is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Dark Pool alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Data Network Effect is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Data Network Effect alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from network effects where data value increases with network size.

Google's search improves as it collects more user data and search queries.

Data Snooping is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Data Snooping alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Advantage from accumulating customer data over time, making it difficult to switch platforms.

LinkedIn's value increases as users add more professional history and connections.

Moat from becoming the standard solution that others conform to.

Windows became the de facto standard for enterprise operating systems.

Decentralization is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Decentralization alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Advantage from controlling the default operating system or platform.

Apple iOS creates moat as default mobile OS for iPhone users.

Default Platform Status is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Default Platform Status alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Default Probability is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Default Probability alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Risk that a borrower will fail to make required interest or principal payments.

A bond from a company with weak financials has high default risk.

Deferred Revenue is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Deferred Revenue alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

DeFi Lending is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses DeFi Lending alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Deflation is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Deflation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Rate of change of option price relative to change in underlying asset price.

An option with delta 0.5 gains $0.50 for every $1 gain in the underlying.

Delta Hedging is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Delta Hedging alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Depreciation is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Depreciation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat created when a product becomes embedded in customer's design or engineering specifications.

Intel processors embedded in computer designs create switching costs for manufacturers.

Design-In Advantage is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Design-In Advantage alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Developer Ecosystem Moat is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Developer Ecosystem Moat alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

DEX is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses DEX alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Dex Aggregator is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Dex Aggregator alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Digital Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Digital Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Digital Wallet is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Digital Wallet alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Diluted EPS is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Diluted EPS alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat where value increases directly with network size.

Facebook becomes more valuable as more users join the network.

Discounted Cash Flow is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Discounted Cash Flow alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Disinflation is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Disinflation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from controlling distribution channels and logistics.

Coca-Cola's extensive distribution network makes it difficult for competitors to reach customers.

Distribution Shelf Space is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Distribution Shelf Space alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Diversification is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Diversification alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Ratio of weighted average volatility to portfolio volatility, measuring diversification benefit.

A ratio of 2.0 means portfolio volatility is half of average component volatility.

Dividend Discount Model is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Dividend Discount Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Dividend Payout Ratio is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Dividend Payout Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Annual dividend payment divided by stock price, expressed as percentage.

A stock trading at $100 paying $4 annual dividend has 4% dividend yield.

Dollar Duration is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Dollar Duration alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Dollar Liquidity is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Dollar Liquidity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Dormancy is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Dormancy alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Technical chart pattern where price reaches the same resistance level twice, often predicting decline.

Stock reaching $100 twice with decline in between may indicate bearish reversal.

Downside Deviation is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Downside Deviation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Peak-to-trough decline during a specific period. Maximum drawdown is the largest loss from peak to trough.

A portfolio that went from $1M to $800K experienced a 20% drawdown.

Drawdown Recovery Time is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Drawdown Recovery Time alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Measure of bond's sensitivity to interest rate changes, weighted average time to cash flows.

A bond with 5-year duration loses 5% in value if interest rates rise 1%.

Duration Gap is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Duration Gap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Dynamic Allocation is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies dynamic allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Dynamic Alpha is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies dynamic alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Dynamic Attribution is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies dynamic attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Company's net income divided by number of outstanding shares.

A company with $100M net income and 10M shares has $10 EPS.

Earnings Surprise is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Earnings Surprise alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Earnings Yield is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Earnings Yield alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

EBIT is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses EBIT alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

EBITDA is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses EBITDA alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

EBITDA Margin is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses EBITDA Margin alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Economic Allocation is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies economic allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Economic Alpha is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies economic alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Economic Attribution is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies economic attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Economic Value Added is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Economic Value Added alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Economies of Scope is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Economies of Scope alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from ecosystem of complementary products and services.

Apple's ecosystem of hardware, software, and services creates strong moat.

Ecosystem Lock-In is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Ecosystem Lock-In alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Set of optimal portfolios offering the highest expected return for a given level of risk.

Modern Portfolio Theory uses the efficient frontier to identify ideal asset allocations.

Theory that asset prices fully reflect available information, making consistent outperformance impossible.

If EMH is true, active management cannot consistently beat the market.

Ensemble Model is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Ensemble Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Enterprise Value is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Enterprise Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Enterprise Value to EBITDA is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Enterprise Value to EBITDA alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Enterprise Value to Sales is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Enterprise Value to Sales alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Entity-Adjusted Volume is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Entity-Adjusted Volume alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Equal Weighting is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Equal Weighting alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Equity Risk Premium is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Equity Risk Premium alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

European Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses European Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Event-Driven Allocation is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies event-driven allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Event-Driven Alpha is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies event-driven alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Event-Driven Attribution is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies event-driven attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Exchange Inflow is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Exchange Inflow alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Exchange Net Position Change is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Exchange Net Position Change alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Exchange Outflow is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Exchange Outflow alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Exchange Reserve is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Exchange Reserve alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Exclusive Content Rights is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Exclusive Content Rights alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Execution Allocation is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies execution allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Execution Alpha is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies execution alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Exit Multiple is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Exit Multiple alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Expected Loss is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Expected Loss alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Expected Shortfall is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Expected Shortfall alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moving average that gives more weight to recent prices than older prices.

A 20-day EMA responds faster to price changes than simple 20-day moving average.

Exposure Drift is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Exposure Drift alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Extraordinary Item is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Extraordinary Item alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Factor Allocation is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies factor allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Factor Alpha is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies factor alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Factor Attribution is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies factor attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Factor Model is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Factor Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Factor Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Factor Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Factor Tilts is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Factor Tilts alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Fair Value is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Fair Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Feature Engineering is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Feature Engineering alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Feature Importance is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Feature Importance alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Feature Leakage is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Feature Leakage alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Federal Funds Rate is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Federal Funds Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Fee Revenue is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Fee Revenue alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Fill Rate is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Fill Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Fiscal Deficit is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Fiscal Deficit alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Flash Loan is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Flash Loan alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Float is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Float alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Advantage from receiving cash from customers before delivering products/services.

Insurance companies invest premium float before paying claims.

Floating Rate Note is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Floating Rate Note alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Fork is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Fork alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Advantage from proprietary formats that are difficult or costly to convert to competing standards.

Adobe PDF format became so standard that alternatives struggle to compete.

Forward Allocation is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies forward allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Forward Alpha is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies forward alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Forward Attribution is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies forward attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Forward Contract is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Forward Contract alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Forward Guidance is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Forward Guidance alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Forward P/E is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Forward P/E alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Cash generated by operations minus capital expenditures, available to investors.

A company with $500M operating cash flow and $100M capex has $400M FCF.

Free Cash Flow Margin is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Free Cash Flow Margin alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Free Cash Flow Yield is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Free Cash Flow Yield alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Free Float is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Free Float alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Fully Diluted Valuation is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Fully Diluted Valuation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Funding Rate is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Funding Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Funding Skew is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Funding Skew alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Futures Contract is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Futures Contract alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

GAAP Earnings is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses GAAP Earnings alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Rate of change of delta relative to change in underlying asset price.

An option with high gamma has delta that changes rapidly with price moves.

Gap Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Gap Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Gas is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Gas alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Gas Usage is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Gas Usage alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Genesis Block is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Genesis Block alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Geographic Monopoly is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Geographic Monopoly alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from natural geographic advantages like proximity to raw materials or customers.

Aluminum smelters near hydroelectric power have massive cost advantage.

Measure of statistical dispersion, sometimes used to assess portfolio return distribution inequality.

Portfolios with unequal return distributions have higher Gini coefficients.

Global Allocation is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies global allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Global Alpha is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies global alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Global Attribution is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies global attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Technical pattern when short-term moving average crosses above long-term moving average.

50-day MA crossing above 200-day MA is considered a bullish signal.

Goodwill is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Goodwill alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Gordon Growth Model is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Gordon Growth Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Governance Attack is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Governance Attack alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from long-term government contracts and established relationships.

Defense contractors maintain moats through established government contracts.

Set of metrics (Delta, Gamma, Vega, Theta, Rho) measuring option sensitivity to various factors.

Options traders monitor Greeks to understand their position risks.

Gross Domestic Product is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Gross Domestic Product alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Gross Margin is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Gross Margin alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Growth Allocation is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Growth Allocation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Growth Stock is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Growth Stock alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from habitual usage patterns where customers default to familiar solutions.

Users default to Google for search due to habit, making competitor adoption difficult.

Hard Landing is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Hard Landing alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Hash Rate is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Hash Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Chart pattern with three peaks (head higher than shoulders) indicating bearish reversal.

Head and shoulders pattern often precedes significant price declines.

Position taken to offset potential losses in another position.

Buying put options on stocks you own hedges against downside risk.

Hedged Portfolio is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Hedged Portfolio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Taking a position to offset potential losses in another position. Reduces risk but often at a cost.

Buying put options on stocks you own is a hedge against downside risk.

Hierarchical Allocation is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies hierarchical allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Hierarchical Alpha is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies hierarchical alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Hierarchical Attribution is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies hierarchical attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Hierarchical Risk Parity is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Hierarchical Risk Parity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

High-Yield Bond is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses High-Yield Bond alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Volatility calculated from past price changes, often measured as standard deviation.

A stock with 20% historical volatility has moved ±20% from its mean.

HODL Waves is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses HODL Waves alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Hot Wallet is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Hot Wallet alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Hurst Exponent is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Hurst Exponent alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Hyperparameter Tuning is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Hyperparameter Tuning alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Idiosyncratic Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Idiosyncratic Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Impairment Charge is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Impairment Charge alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Impermanent Loss is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Impermanent Loss alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Implementation Shortfall is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Implementation Shortfall alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Implied Allocation is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies implied allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Implied Alpha is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies implied alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Implied Attribution is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies implied attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Implied Growth Rate is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Implied Growth Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Implied Volatility is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Implied Volatility alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Implied Volatility Surface is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Implied Volatility Surface alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

In-the-Money Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses In-the-Money Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Income Allocation is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Income Allocation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Basket of securities representing a market segment or asset class.

S&P 500 index comprises 500 large-cap US companies.

Installed Base is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Installed Base alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from customers locked into buying replacement consumables for installed products.

Printer manufacturers create loyalty by selling ink cartridges to existing printer owners.

Institutional Allocation is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies institutional allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Institutional Alpha is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies institutional alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Institutional Attribution is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies institutional attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Intangible Assets is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Intangible Assets alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Interest Coverage is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Interest Coverage alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Interest Rate Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Interest Rate Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Interoperability is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Interoperability alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from being the central hub that others must connect to.

Credit card networks require merchants to connect for payment processing.

Fundamental value of a security based on discounted future cash flows.

A stock trading at $50 might have intrinsic value of $60 based on DCF analysis.

Inventory Write-Down is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Inventory Write-Down alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Investment-Grade Bond is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Investment-Grade Bond alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from controlling essential intellectual property or patents.

Qualcomm's patent portfolio in mobile chips creates licensing moat.

Iron Condor is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Iron Condor alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Isolated Margin is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Isolated Margin alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Issuer Call Risk is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Issuer Call Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Risk-adjusted excess return compared to a market benchmark.

A fund with positive Jensen's alpha outperforms its benchmark after adjusting for risk.

Probability that two events occur together.

Probability of interest rates rising AND stock market declining is their joint probability.

Business practice of receiving inventory just before it's needed, minimizing storage costs.

Dell computers uses just-in-time inventory to reduce holding costs.

Kalman Filter is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Kalman Filter alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Mathematical formula for optimal position sizing based on win rate and payoff ratios.

Kelly Criterion determines the ideal percentage of capital to risk on each trade.

Key Rate Duration is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Key Rate Duration alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Advantage from controlling a critical component that others depend on.

Intel's dominance in CPU design gives them power over PC manufacturers.

Statistical measure of tail risk. High kurtosis indicates greater likelihood of extreme events.

Assets with high kurtosis experience more frequent extreme price movements.

Statistical measure of tail behavior, indicating likelihood of extreme events.

High-kurtosis distributions experience more frequent extreme returns.

Labor Force Participation is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Labor Force Participation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Large Cap is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Large Cap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Latency Arbitrage is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Latency Arbitrage alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Latent Allocation is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies latent allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Latent Alpha is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies latent alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Latent Attribution is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies latent attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Layer 1 is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Layer 1 alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Layer 2 is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Layer 2 alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Learning Curve Advantage is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Learning Curve Advantage alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from improving yields and efficiency through accumulated production experience.

Samsung improves chip yields faster than competitors due to manufacturing experience.

Lease Liability is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Lease Liability alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Leverage Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Leverage Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Limit Order is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Limit Order alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Liquidation is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Liquidation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Liquidation Heatmap is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Liquidation Heatmap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Liquidation Threshold is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Liquidation Threshold alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Liquidation Value is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Liquidation Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Ability to buy or sell an asset quickly without significantly affecting its price.

Stocks are generally more liquid than real estate or private equity.

Liquidity Allocation is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies liquidity allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Liquidity Alpha is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies liquidity alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Liquidity Attribution is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies liquidity attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Liquidity Mining is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Liquidity Mining alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Liquidity Pool is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Liquidity Pool alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Liquidity Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Liquidity Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Liquidity Sleeve is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Liquidity Sleeve alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Lit Venue is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Lit Venue alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Loan-to-Value is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Loan-to-Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Locked Market is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Locked Market alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Ownership of a security, benefiting from price appreciation.

Owning 100 shares of Apple means you have a long position.

Long Straddle is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Long Straddle alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Long Strangle is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Long Strangle alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from multi-year contracts that lock customers into exclusive relationships.

Telecom companies use multi-year contracts to retain subscribers.

Long-Term Contracts is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Long-Term Contracts alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Long-Term Holder Supply is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Long-Term Holder Supply alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Look-Ahead Bias is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Look-Ahead Bias alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Exotic option that pays based on the optimal price achieved during the holding period.

A lookback call option pays the difference between current price and the lowest price during the period.

Tendency to feel loss pain more acutely than equivalent gain pleasure.

Investors hold losing positions too long due to loss aversion.

Lot Size is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Lot Size alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Macaulay Duration is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Macaulay Duration alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Macro Allocation is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies macro allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Macro Alpha is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies macro alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Macro Attribution is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies macro attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Maker Fee is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Maker Fee alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Maker-Taker Model is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Maker-Taker Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Margin Call Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Margin Call Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Margin of Safety is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Margin of Safety alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Margin Requirement is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Margin Requirement alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Market Allocation is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies market allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Market Alpha is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies market alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Market Attribution is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies market attribution rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Market Cap (Crypto) is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Market Cap (Crypto) alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Market Capitalization is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Market Capitalization alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Market Order is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Market Order alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Market Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Market Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Market-Cap Weighting is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Market-Cap Weighting alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Largest peak-to-trough decline experienced during a specific period.

A portfolio that dropped from $1M to $600k had a 40% maximum drawdown.

Theory that prices tend to move back toward their average over time.

A stock trading far below its historical average may revert upward.

Mean-Variance Optimization is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Mean-Variance Optimization alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Mega Cap is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Mega Cap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Mempool is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Mempool alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Mid Cap is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Mid Cap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Miner Balance is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Miner Balance alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Miner Extractable Value is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Miner Extractable Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Minimum Variance Portfolio is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Minimum Variance Portfolio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Mnemonic Phrase is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Mnemonic Phrase alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Model Drift is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Model Drift alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Model Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Model Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Modified Duration is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Modified Duration alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Monetary Easing is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Monetary Easing alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Monetary Tightening is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Monetary Tightening alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Monte Carlo Simulation is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Monte Carlo Simulation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Mortgage-Backed Security is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Mortgage-Backed Security alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Multi-Factor Allocation is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies multi-factor allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Multi-Factor Alpha is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies multi-factor alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Multi-Manager Portfolio is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Multi-Manager Portfolio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Municipal Bond is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Municipal Bond alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

MVRV Ratio is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses MVRV Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Negative Convexity is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Negative Convexity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from business model where customers pay before inventory must be purchased.

Amazon receives payment before paying suppliers, funding growth with no debt.

Negative Working Capital Model is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Negative Working Capital Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Net Asset Value is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Net Asset Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Net Debt is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Net Debt alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Net Margin is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Net Margin alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Net Unrealized Profit/Loss is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Net Unrealized Profit/Loss alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Net Working Capital is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Net Working Capital alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Network Effects is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Network Effects alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Node is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Node alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Non-GAAP Earnings is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Non-GAAP Earnings alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Nonce is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Nonce alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Nonlinear Allocation is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies nonlinear allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Nonlinear Alpha is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies nonlinear alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

NVT Ratio is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses NVT Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

OAS (Option-Adjusted Spread) is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses OAS (Option-Adjusted Spread) alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

On-Chain Governance is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses On-Chain Governance alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Opening Auction is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Opening Auction alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Operating Cash Flow is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Operating Cash Flow alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Operating Income is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Operating Income alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Operating Margin is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Operating Margin alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from superior operational efficiency and cost management.

Amazon's logistics efficiency creates cost advantage over traditional retailers.

Operational Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Operational Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Option Assignment is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Option Assignment alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Option Premium is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Option Premium alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Oracle is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Oracle alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Oracle Manipulation is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Oracle Manipulation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Order Book Depth is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Order Book Depth alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Order Flow Allocation is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies order flow allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Order Flow Alpha is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies order flow alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Other Comprehensive Income is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Other Comprehensive Income alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Out-of-Sample Test is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Out-of-Sample Test alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Out-of-the-Money Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Out-of-the-Money Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Output Gap is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Output Gap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Overcollateralization is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Overcollateralization alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Overfitting is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Overfitting alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Overlay Strategy is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Overlay Strategy alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

P-Value is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses P-Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Panel Regression is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Panel Regression alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Par Value is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Par Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Parameter Stability is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Parameter Stability alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Participation Rate is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Participation Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

PEG Ratio is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses PEG Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Permissionless is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Permissionless alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Advantage from holding permits or rights necessary for operation.

Utility companies hold permits making new entrants difficult.

Permutation Test is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Permutation Test alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Perpetual DEX is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Perpetual DEX alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Perpetual Futures is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Perpetual Futures alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Perpetual Open Interest is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Perpetual Open Interest alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from dense physical networks that are expensive to replicate.

Electric utility networks are expensive to duplicate due to physical infrastructure.

Policy Rate is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Policy Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Portable Alpha is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Portable Alpha alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Portfolio Allocation is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies portfolio allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Portfolio Alpha is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies portfolio alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Portfolio Beta is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Portfolio Beta alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Portfolio Turnover is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Portfolio Turnover alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Position Limit is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Position Limit alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Precedent Transactions is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Precedent Transactions alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Prediction Interval is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Prediction Interval alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Predictive Allocation is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies predictive allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Predictive Alpha is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies predictive alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Advantage from preferential access to key inputs or raw materials.

De Beers' control of diamond supply sources creates pricing power.

Prepaid Expense is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Prepaid Expense alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Prepayment Float is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Prepayment Float alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Price Impact is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Price Impact alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Price to Free Cash Flow is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Price to Free Cash Flow alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Price-to-Book Ratio is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Price-to-Book Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Price-to-Earnings Ratio is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Price-to-Earnings Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Price-to-Sales Ratio is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Price-to-Sales Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Principal Component Analysis is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Principal Component Analysis alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Private Key is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Private Key alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Pro Forma Earnings is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Pro Forma Earnings alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Probabilistic Allocation is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies probabilistic allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Probabilistic Alpha is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies probabilistic alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Process Complexity is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Process Complexity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from the difficulty and cost of changing established procurement processes.

Businesses reluctant to change established vendor relationships despite better alternatives.

Productivity Growth is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Productivity Growth alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Proof of Stake is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Proof of Stake alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Proof of Work is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Proof of Work alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Proprietary Data is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Proprietary Data alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Protective Put is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Protective Put alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Protocol Revenue is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Protocol Revenue alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Protocol Standardization is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Protocol Standardization alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Protocol-Owned Liquidity is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Protocol-Owned Liquidity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Public Key is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Public Key alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Purchasing Managers' Index is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Purchasing Managers' Index alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Put Option is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Put Option alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Quant Allocation is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies quant allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Quant Alpha is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies quant alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Quantitative Easing is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Quantitative Easing alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Quantitative Tightening is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Quantitative Tightening alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Queue Position is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Queue Position alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Quick Ratio is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Quick Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Real Interest Rate is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Real Interest Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Real Wage Growth is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Real Wage Growth alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Real Yield is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Real Yield alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Realized Cap is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Realized Cap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Realized Price is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Realized Price alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Rebalancing is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Rebalancing alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Recovery Rate is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Recovery Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Regime Allocation is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies regime allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Regime Alpha is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies regime alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Regime Detection is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Regime Detection alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Regime Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Regime Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Regression to the Mean is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Regression to the Mean alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from regulatory standards that favor established players.

Banking regulations create barriers for new fintech entrants.

Regulatory License is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Regulatory License alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Reinvestment Risk is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Reinvestment Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Relative Valuation is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Relative Valuation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Replacement Cost is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Replacement Cost alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Reputation Flywheel is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Reputation Flywheel alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from positive review accumulation that attracts new customers.

Amazon sellers with thousands of 5-star reviews gain trust-based advantage.

Reserve Factor is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Reserve Factor alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Residual Income Model is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Residual Income Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Residual Return is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Residual Return alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Restaking is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Restaking alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Retained Earnings is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Retained Earnings alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Return on Equity is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Return on Equity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Return on Invested Capital is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Return on Invested Capital alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Revenue Growth is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Revenue Growth alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Revenue Recognition is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Revenue Recognition alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Reverse Split is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Reverse Split alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Rho is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Rho alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Rights-of-Way is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Rights-of-Way alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Risk Allocation is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies risk allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Risk Alpha is a structured concept in quantitative investing used to improve asset allocation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies risk alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Risk Budget is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Risk Budget alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Risk Contribution is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Risk Contribution alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Risk of Ruin is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Risk of Ruin alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Risk Parity is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Risk Parity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Risk-Adjusted Return is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Risk-Adjusted Return alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Robustness Check is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Robustness Check alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Same-Store Sales is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Same-Store Sales alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Satellite Position is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Satellite Position alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Scale Economies is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Scale Economies alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from lower per-unit costs at higher volumes.

Larger retailers achieve lower inventory costs than smaller competitors.

Scenario Analysis is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Scenario Analysis alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from leveraging shared assets across multiple product lines or markets.

Conglomerates achieve efficiency by sharing R&D, manufacturing, and distribution.

Seasonal Allocation is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies seasonal allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Seasonal Alpha is a structured concept in quantitative investing used to improve investment strategy decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies seasonal alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Sector Allocation is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Sector Allocation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Segment Reporting is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Segment Reporting alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Competitive advantage from extensive service network that competitors can't easily replicate.

Caterpillar's global service network supports equipment sales and creates loyalty.

Service Network Density is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Service Network Density alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Settlement Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Settlement Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Shareholder Yield is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Shareholder Yield alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Risk-adjusted return metric. Excess return per unit of risk taken. Higher is better.

A strategy with 1.5 Sharpe Ratio generates 1.5% excess return per 1% of risk.

Short Interest is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Short Interest alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Short Interest Ratio is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Short Interest Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Short-Term Holder Supply is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Short-Term Holder Supply alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Signal Allocation is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies signal allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Signal Alpha is a structured concept in quantitative investing used to improve quantitative investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies signal alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Signal Decay is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Signal Decay alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Signal-to-Noise Ratio is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Signal-to-Noise Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Skewness is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Skewness alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Slashing is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Slashing alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Slippage Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Slippage Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Small Cap is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Small Cap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Smart Contract is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Smart Contract alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Smart Contract Audit is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Smart Contract Audit alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Soft Landing is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Soft Landing alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

SOPR is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses SOPR alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Sortino Ratio is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Sortino Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Sovereign Bond is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Sovereign Bond alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Sovereign Risk is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Sovereign Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Spent Output Age Bands is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Spent Output Age Bands alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Spread Duration is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Spread Duration alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Stable Swap is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Stable Swap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Stablecoin is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Stablecoin alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Stablecoin Inflow is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Stablecoin Inflow alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Stablecoin Supply Ratio is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Stablecoin Supply Ratio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Stagflation is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Stagflation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Staking is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Staking alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Staking Derivative is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Staking Derivative alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Measure of dispersion around the mean. Quantifies volatility and variability of returns.

Returns with a standard deviation of 15% are more dispersed than those with 10%.

Advantage from controlling standards or registries others depend on.

ICANN controls domain name registry, creating dependency moat.

State Space Model is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses State Space Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Stationarity is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Stationarity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Statistical Allocation is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies statistical allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Statistical Alpha is a structured concept in quantitative investing used to improve systematic trading decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies statistical alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Stock Split is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Stock Split alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Stock-Based Compensation is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Stock-Based Compensation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Strategic Asset Allocation is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Strategic Asset Allocation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Stress Testing is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Stress Testing alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from bundling multiple products together, making it costly to switch from partial suite.

Microsoft Office suite is harder to replace than individual apps.

Sum-of-the-Parts is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Sum-of-the-Parts alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from owning or controlling parts of the supply chain.

Vertical integration of mining and refining gives aluminum producers cost advantage.

Survivorship Bias is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Survivorship Bias alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Switching Costs is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Switching Costs alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Broad category of costs (financial, time, psychological) that make switching to competitors difficult.

Enterprise software switching costs can exceed $1M in implementation and training.

Systematic Allocation is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies systematic allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Systematic Alpha is a structured concept in quantitative investing used to improve portfolio management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies systematic alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Tactical Allocation is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies tactical allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Tactical Alpha is a structured concept in quantitative investing used to improve risk management decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies tactical alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Tactical Asset Allocation is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Tactical Asset Allocation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Tail Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Tail Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Taker Fee is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Taker Fee alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Tangible Book Value is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Tangible Book Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Target Volatility is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Target Volatility alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Tax Shield is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Tax Shield alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Term Premium is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Term Premium alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Term Structure is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Term Structure alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Term Structure Allocation is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies term structure allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Term Structure Alpha is a structured concept in quantitative investing used to improve alpha generation decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies term structure alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Terminal Value is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Terminal Value alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Theta is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Theta alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Tick Size is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Tick Size alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Time-Series Momentum is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Time-Series Momentum alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Token is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Token alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Token Burn is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Token Burn alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Token Emission is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Token Emission alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Token Unlock is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Token Unlock alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Tokenomics is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Tokenomics alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Total Return Swap is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Total Return Swap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Total Shareholder Return is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Total Shareholder Return alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Tracking Error is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Tracking Error alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Tracking Portfolio is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Tracking Portfolio alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from the organizational complexity and cost of retraining staff on new solutions.

Large organizations reluctant to switch ERP systems due to massive training requirements.

Transaction Cost Model is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Transaction Cost Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Transaction Count is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Transaction Count alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Transfer Volume is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Transfer Volume alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Treasury Stock is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Treasury Stock alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Treasury Yield Curve is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Treasury Yield Curve alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Trend Allocation is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies trend allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Trend Alpha is a structured concept in quantitative investing used to improve factor investing decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies trend alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

TVL (Total Value Locked) is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses TVL (Total Value Locked) alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

TWAP is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses TWAP alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Moat from two-sided network effects connecting buyers and sellers.

Uber's value increases as more drivers and riders join the platform.

Two-Sided Marketplace is a core concept in moat used for durable competitive advantage analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Two-Sided Marketplace alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Ulcer Index is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Ulcer Index alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Under-Collateralized Loan is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Under-Collateralized Loan alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Advantage from pooling risk across large customer base.

Large insurance companies achieve better underwriting economics through pooling.

Unearned Revenue is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Unearned Revenue alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Unemployment Rate is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Unemployment Rate alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

UTXO Age is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses UTXO Age alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Validator is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Validator alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Validator Set is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Validator Set alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Valuation Multiple Compression is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Valuation Multiple Compression alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Valuation Multiple Expansion is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Valuation Multiple Expansion alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Maximum expected loss over a given period with a specified confidence level.

95% VaR of $100k means there's a 5% chance of losses exceeding $100k.

Value Stock is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Value Stock alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Variance Swap is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Variance Swap alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Vault Strategy is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Vault Strategy alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Vega is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Vega alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

veToken Model is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses veToken Model alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Measure of price fluctuations. Standard deviation of returns. Higher volatility means greater price swings.

A stock with 20% annualized volatility fluctuates significantly more than one with 10% volatility.

Volatility Allocation is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies volatility allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Volatility Alpha is a structured concept in quantitative investing used to improve market analysis decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies volatility alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Volatility Clustering is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Volatility Clustering alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Volatility Skew is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Volatility Skew alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Volatility Smile is a core concept in derivatives used for options and futures risk shaping. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Volatility Smile alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

VWAP is a core concept in market structure used for execution quality and liquidity management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses VWAP alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Walk-Forward Analysis is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Walk-Forward Analysis alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Weight Drift is a core concept in portfolio used for allocation design and rebalancing discipline. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Weight Drift alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Weighted Average Cost of Capital is a core concept in valuation used for fair-value estimation and entry timing. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Weighted Average Cost of Capital alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Weighted Average Shares is a core concept in equities used for equity analysis and stock selection. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Weighted Average Shares alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Whale is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Whale alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Whale Accumulation is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Whale Accumulation alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Whale Distribution is a core concept in on-chain used for blockchain activity interpretation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Whale Distribution alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Working Capital is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Working Capital alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Wrapped Token is a core concept in crypto used for digital-asset market structure analysis. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Wrapped Token alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Write-Off is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Write-Off alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Write-Up is a core concept in accounting used for financial statement quality assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Write-Up alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Wrong-Way Risk is a core concept in risk used for portfolio downside control and loss containment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Wrong-Way Risk alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Yield Allocation is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies yield allocation rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Yield Alpha is a structured concept in quantitative investing used to improve volatility decisions through measurable rules, repeatable testing, and clear risk controls.

Example: A team applies yield alpha rules to rebalance exposures when forecast confidence rises and correlation-adjusted risk stays within limits.

Yield Curve Inversion is a core concept in macro used for top-down regime assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Yield Curve Inversion alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Yield Farming is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Yield Farming alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Yield to Call is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Yield to Call alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Yield to Maturity is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Yield to Maturity alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Yield Tokenization is a core concept in defi used for decentralized finance protocol risk assessment. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Yield Tokenization alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Z-Score is a core concept in quant used for systematic research and model validation. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Z-Score alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.

Zero-Coupon Bond is a core concept in fixed income used for bond portfolio construction and rate-risk management. Analysts combine it with complementary metrics, regime context, and implementation constraints before making allocation decisions.

Example: The investment team uses Zero-Coupon Bond alongside risk limits and transaction-cost assumptions to refine position sizing and improve decision quality.