Resources

A measure of risk-adjusted return that divides the excess return of a portfolio over the risk-free rate by its standard deviation. A Sharpe ratio above 1.0 is generally considered acceptable, above 2.0 is very good, and above 3.0 is excellent.

The largest peak-to-trough decline in portfolio value before a new peak is achieved. It measures the worst-case loss an investor would have experienced during a specific period.

The excess return of an investment relative to the return of a benchmark index. Positive alpha indicates the strategy has outperformed the market on a risk-adjusted basis.

A measure of a portfolio's sensitivity to market movements. A beta of 1.0 means the portfolio moves in lockstep with the market; below 1.0 indicates lower volatility than the market.

A trading strategy based on the statistical tendency of asset prices to revert to their historical mean. When prices deviate significantly from the mean, positions are taken expecting a return to average levels.

A strategy that buys assets with strong recent performance and sells those with weak recent performance, based on the empirical observation that trends tend to persist over medium-term horizons.

The process of testing a trading strategy on historical data to evaluate its performance before deploying it with real capital. A rigorous backtest accounts for transaction costs, slippage, survivorship bias, and look-ahead bias.

The danger of optimizing a strategy too closely to historical data, capturing noise rather than genuine signal. An overfit strategy performs excellently in backtests but fails in live trading.

The study of how exchanges operate, how orders are matched, and how prices are formed at the most granular level. Understanding microstructure is essential for high-frequency and execution-focused strategies.

A real-time, continuously updated list of buy and sell orders for a financial instrument, organized by price level. The order book reveals the supply and demand dynamics at each price point.

Autonomous AI systems that can perceive their environment, reason about complex situations, plan multi-step actions, and execute decisions without continuous human oversight. In trading, agentic AI manages the full loop from market analysis to order execution.

A machine learning paradigm where an agent learns optimal actions by interacting with an environment and receiving rewards or penalties. In trading, the agent learns to maximize cumulative returns while managing risk.

A validation technique that repeatedly optimizes a strategy on a rolling in-sample window, then tests it on the subsequent out-of-sample period. This simulates how the strategy would have been managed in real-time.

A computational technique that generates thousands of randomized scenarios to estimate the probability distribution of outcomes. In trading, it stress-tests strategies by shuffling trade sequences to assess robustness.

A statistical measure of the dispersion of returns for a given asset or portfolio. Higher volatility means greater uncertainty about future price movements. It is the most fundamental concept in risk management.

A market-neutral strategy that identifies two historically correlated assets, goes long the underperformer and short the outperformer when their spread diverges, profiting when the spread reverts to its mean.

The process of identifying distinct market states (regimes) such as trending, mean-reverting, high-volatility, or low-volatility periods. Different strategies perform optimally in different regimes.

The time delay between initiating an action (e.g., sending an order) and its completion (e.g., order acknowledged by exchange). In algorithmic trading, lower latency provides a competitive advantage.

An investment approach that targets specific drivers of return (factors) such as value, momentum, size, quality, and low volatility. Factor models decompose returns into systematic and idiosyncratic components.

A formula for determining the optimal fraction of capital to allocate to a bet or trade, given the probability of winning and the payoff ratio. It maximizes the long-term geometric growth rate of wealth.