An equity curve is a time series of cumulative profit and loss plotted over time.
An equity curve is a time series of cumulative profit and loss plotted over time. It shows the running value of a trading account, portfolio, or backtest as gains and losses accumulate. In practice, it is the raw path behind many summary statistics used to evaluate a strategy.
The construction is straightforward. Start with a sequence of periodic returns or profit and loss observations from a strategy. Add each period’s result to the running total, or compound returns into portfolio value, and place those cumulative values against time. The resulting line is the equity curve. When the line rises, cumulative profit and loss is increasing. When it falls, the strategy is in a drawdown from a prior peak.
This is why the equity curve is more informative than a single endpoint. Two strategies can finish at the same final value while following very different paths. One may advance steadily with shallow setbacks. Another may alternate between sharp gains and deep losses. The curve makes those differences visible because it preserves sequence, depth, and duration.
Drawdown is read directly from the curve. Max drawdown is the largest peak to trough decline before a new high is reached. The Sonar Sciences fundamentals material presents max drawdown as a core risk measure in backtesting and performance evaluation. Because drawdown depends on the path, not just the ending result, the equity curve is the natural object from which it is computed. A long flat recovery after a loss also appears clearly on the curve even when a summary statistic compresses that experience into one number.
The same underlying time series also supports return and risk statistics. Sonar Sciences defines the Sharpe ratio as a standardized return measure that relates excess return to volatility, and the deflated Sharpe ratio as a correction intended to account for multiple testing and non normal effects when evaluating discovered strategies. Those metrics summarize properties of the return series, while the equity curve shows the realized accumulation of those returns through time. Used together, they separate two questions: how attractive the return distribution appears in aggregate, and how the path behaved on the way there.
In research practice, the equity curve is often inspected alongside robustness checks. The Backtest Overfitting Audit is presented by Sonar Sciences as a way to assess whether an apparent result may be explained by overfitting rather than durable signal. In that context, a smooth curve by itself is not proof of validity. It is one diagnostic view that should be interpreted with the strategy’s test design, drawdown profile, and adjusted performance statistics.
The key use of an equity curve is therefore descriptive. It visualizes cumulative profit and loss through time and reveals periods of growth, stagnation, and drawdown. Performance metrics such as max drawdown and Sharpe ratio are derived from the same underlying data, but the curve remains the most direct representation of the strategy’s path.
Covered in depth in the Strategy research fundamentals pillar hub.