Trading glossary
Key terms and concepts for algorithmic trading and backtesting. Clear definitions for traders of all experience levels.
40 terms
Strategy & Backtesting
Backtesting
The process of testing a trading strategy against historical market data to evaluate how it would have performed. Backtesting helps traders validate their ideas before risking real capital.
Walk-Forward Optimization
A technique for reducing overfitting in strategy development. The historical data is divided into in-sample (training) and out-of-sample (testing) periods, and the strategy is optimized on each in-sample period and tested on the subsequent out-of-sample period.
Overfitting
When a strategy is too closely tuned to historical data, capturing noise rather than genuine market patterns. Overfitted strategies perform well in backtests but fail in live trading. Walk-forward testing and out-of-sample validation help detect overfitting.
Algorithmic Trading
The use of computer programs to execute trading strategies according to predefined rules. Algorithmic trading removes emotional bias from decision-making and enables strategies to operate at speeds and frequencies impossible for human traders.
Survivorship Bias
A form of selection bias that occurs when backtests only include instruments that have survived to the present day, excluding those that were delisted, went bankrupt, or merged. This inflates backtest performance by removing the worst-performing assets from the dataset.
Look-Ahead Bias
A backtesting error that occurs when a strategy uses information that would not have been available at the time of the trading decision. This makes backtest results unrealistically optimistic because the strategy effectively has access to future data.
Paper Trading
Simulated trading using real-time market data but without risking real capital. Paper trading serves as a bridge between backtesting and live deployment, allowing traders to verify that their strategy works correctly in real market conditions.
Curve Fitting
The process of adjusting a strategy's parameters too closely to historical data, resulting in a model that describes past noise rather than future-relevant patterns. Curve fitting is the mechanism by which overfitting occurs and is one of the most common traps in strategy development.
Monte Carlo Simulation
A statistical technique that runs thousands of simulated scenarios by randomly resampling or perturbing a strategy's historical trade outcomes. Monte Carlo simulation estimates the range of possible future performance, including worst-case scenarios that may not appear in a single backtest.
Performance Metrics
Sharpe Ratio
A risk-adjusted performance metric calculated as the ratio of excess return (return above the risk-free rate) to standard deviation of returns. A higher Sharpe ratio indicates better risk-adjusted performance. Generally, a Sharpe ratio above 1 is considered acceptable, above 2 is very good.
Sortino Ratio
Similar to the Sharpe ratio but only penalizes downside volatility. It uses downside deviation instead of standard deviation, making it a more relevant measure for traders who care about loss risk rather than overall volatility.
Maximum Drawdown
The largest peak-to-trough decline in a portfolio or strategy value. It measures the worst-case loss an investor would have experienced. For example, a 20% maximum drawdown means the portfolio fell 20% from its highest point before recovering.
Alpha
The excess return of a strategy relative to a benchmark index. Positive alpha indicates the strategy outperformed the market on a risk-adjusted basis. Generating consistent alpha is the primary goal of algorithmic trading.
Beta
A measure of a strategy or portfolio's sensitivity to market movements. A beta of 1 means the strategy moves in line with the market, less than 1 means less volatile, and greater than 1 means more volatile.
Calmar Ratio
The ratio of annualized return to maximum drawdown. It measures how much return a strategy generates per unit of drawdown risk. A higher Calmar ratio indicates more efficient risk-taking.
Risk-Adjusted Return
A return metric that accounts for the risk taken to achieve it. Raw returns can be misleading — a 20% return with 50% drawdown is very different from 20% return with 10% drawdown. Sharpe, Sortino, and Calmar ratios are all risk-adjusted metrics.
Equity Curve
A graphical representation of a trading strategy or portfolio value over time. The equity curve shows cumulative performance and reveals patterns such as drawdown periods, recovery times, and whether returns are consistent or concentrated in specific periods.
Benchmark
A reference standard, typically a market index like the S&P 500, against which a trading strategy or portfolio performance is measured. Outperforming the benchmark on a risk-adjusted basis is the goal of active trading strategies.
Win Rate
The percentage of trades that are profitable. While intuitively appealing, win rate alone is a misleading metric because it does not account for the magnitude of wins and losses. A strategy with a 30% win rate can be highly profitable if its average win is much larger than its average loss.
Profit Factor
The ratio of gross profits to gross losses. A profit factor above 1.0 indicates a profitable strategy. For example, a profit factor of 1.5 means the strategy earns $1.50 for every $1.00 it loses.
Drawdown Duration
The length of time from a peak in portfolio value to the point where the portfolio recovers to that peak. Drawdown duration measures how long capital is tied up in a losing period and is a critical but often overlooked dimension of drawdown risk.
Risk Management
Position Sizing
The process of determining how much capital to allocate to each trade. Common approaches include fixed fractional, Kelly criterion, and volatility-based sizing. Proper position sizing is a key component of risk management.
Volatility
A statistical measure of the dispersion of returns for a given instrument or portfolio. Higher volatility means larger price swings and greater uncertainty. Volatility is central to risk management, position sizing, and options pricing.
Value at Risk (VaR)
A statistical measure that estimates the maximum expected loss of a portfolio over a specified time period at a given confidence level. For example, a one-day 95% VaR of $10,000 means there is a 95% probability the portfolio will not lose more than $10,000 in a single day.
Correlation
A statistical measure of how two assets or strategies move in relation to each other, ranging from -1 (perfect inverse) to +1 (perfect positive). Low or negative correlations between portfolio components provide diversification benefits and reduce overall risk.
Leverage
The use of borrowed capital or financial derivatives to increase the size of a trading position beyond what the trader's own capital would allow. Leverage amplifies both gains and losses, making risk management critically important.
Order Execution
Slippage
The difference between the expected price of a trade and the price at which it actually executes. Slippage occurs due to market volatility and liquidity constraints. Realistic slippage modeling is critical for accurate backtesting.
Fill
The execution of an order at a specific price and quantity. In backtesting, fill modeling determines how realistically orders are simulated — including partial fills, price impact, and queue position.
Bid-Ask Spread
The difference between the highest price a buyer is willing to pay (bid) and the lowest price a seller is willing to accept (ask). The spread represents a direct cost of trading and a source of profit for market makers.
Limit Order
An order to buy or sell at a specified price or better. A limit buy order executes at the limit price or lower, while a limit sell order executes at the limit price or higher. Limit orders provide price control but do not guarantee execution.
Market Order
An order to buy or sell immediately at the best available price. Market orders guarantee execution but not price, making them susceptible to slippage, especially in volatile or illiquid markets.
Stop-Loss Order
An order that triggers a market sell (or buy to cover) when the price reaches a specified level. Stop-loss orders are used to limit downside risk by automatically exiting a position when it moves against the trader by a predetermined amount.
Order Book
A real-time, continuously updated list of all outstanding buy and sell orders for a financial instrument on an exchange. The order book shows the price and quantity at each level, revealing the supply and demand dynamics that determine where and how orders will fill.
VWAP
Volume-Weighted Average Price, calculated as the sum of (price times volume) for each trade divided by total volume over a period. VWAP serves both as a benchmark for execution quality and as a technical indicator used in trading strategies.
Market Data
Market Microstructure
The study of how trading mechanisms affect price formation. Includes order book dynamics, bid-ask spreads, and trade execution mechanics. Accurate microstructure modeling is what separates realistic backtests from misleading ones.
Tick Data
The most granular level of market data, recording every individual trade or price change. Tick data provides the highest-fidelity backtesting but requires more storage and processing power than candlestick (OHLCV) data.
OHLCV (Candlestick Data)
A standard format for representing price data over a time period, recording the Open, High, Low, Close prices and Volume. OHLCV bars (also called candlesticks) are the most common data format in technical analysis and backtesting.
Trading Strategies
Momentum Trading
A strategy that buys assets that have been rising in price and sells assets that have been falling, based on the empirical observation that trends tend to persist over intermediate time horizons. Momentum is one of the most well-documented anomalies in financial markets.
Mean Reversion
A strategy based on the assumption that prices tend to return to their historical average after deviating from it. Mean reversion strategies buy when prices are unusually low and sell when prices are unusually high, profiting from the correction back toward the mean.