Quant trading glossary

Quantitative trading

An approach to trading that uses mathematical models, data, and rules — rather than intuition alone — to identify and act on market opportunities.

Trade signal

A data-driven indication to buy, sell, hold, or exit a position, often accompanied by a confidence score and the reasoning behind it.

Backtesting

Testing a trading strategy against historical market data to estimate how it would have performed — before risking any real capital.

Sharpe ratio

A measure of risk-adjusted return: how much excess return a strategy earns per unit of volatility. Higher generally means a better reward-for-risk profile.

Maximum drawdown

The largest peak-to-trough decline in equity, expressed as a percentage. One of the clearest measures of how much pain a strategy can put you through.

Win rate

The percentage of trades that close profitably. Note: a high win rate alone doesn't guarantee profit without sensible position sizing and risk control.

Slippage

The gap between the price you expected and the price you actually got, usually caused by fast-moving markets or thin liquidity.

Walk-forward analysis

A validation method that repeatedly optimizes a strategy on one window of data and tests it on the next, unseen window — a strong defense against overfitting.

Monte Carlo simulation

Running many randomized scenarios to estimate the range of outcomes a strategy might produce, and how robust its edge really is.

Overfitting

When a strategy is tuned so tightly to past data that it learns noise instead of a real edge — and then falls apart on new data.

Market regime

A persistent market environment — such as trending, ranging, or high-volatility — that determines which kinds of strategies tend to thrive.

Momentum

The tendency of assets that have been rising (or falling) to keep moving in the same direction for a while. The basis of trend-following strategies.

Mean reversion

The tendency of prices to snap back toward an average after stretching to an extreme — the basis of many counter-trend strategies.

Confidence score

A numeric estimate (often 0–100%) of how strongly the available data supports a given trade signal. Useful for sizing positions.

Position sizing

Deciding how much capital to put behind a trade, typically based on your risk tolerance, the asset's volatility, and your account size.

Out-of-sample testing

Evaluating a strategy on data it was never optimized on, to get an honest preview of how it might perform in the real world.

PVSRA

Price, Volume, Support & Resistance Analysis — colours candles by volume and spread to flag "vector candles" where large players are likely active. The signal core of the Traders Reality hybrid system.

Vector candle

A PVSRA candle whose volume and spread reach a climax (e.g. volume ≥ 2× the recent average), read as a footprint of large-player activity.

Volume Spread Analysis (VSA)

Tom Williams' method, building on Wyckoff, of reading the relationship between price spread and volume to infer professional buying and selling.

Beat the Market Maker (BTMM)

Steve Mauro's market-maker-cycle method describing how price is engineered through accumulation, manipulation and distribution across the week.

Market-maker cycle

The idea that price moves through repeating phases — accumulation, manipulation/stop-hunt, distribution — tied to sessions and the trading week.

Liquidity sweep

A push beyond a prior high or low to trigger resting stop orders, then a reversal — read as large players harvesting liquidity.

Risk of ruin

The probability that a run of losses draws an account down to a point from which it can't practically recover. A core survival metric.

CVaR (expected shortfall)

Conditional Value at Risk — the average loss in the worst tail of outcomes; a more honest tail-risk measure than VaR alone.

Fractional Kelly

Betting a fixed fraction of the full Kelly-optimal stake to cut volatility and drawdown — capped, in Kudbee's case, for safety.

Prediction market

A market (such as Polymarket) where contracts pay out based on real-world event outcomes, with prices interpretable as implied probabilities.

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