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Equity R-Squared

Trading Intelligence

9 min read

equityR2

Measure how closely your equity curve follows a straight line of growth — the simplest indicator of strategy consistency.

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Equity R-Squared (R²) measures how closely your equity curve follows a straight line. It answers a deceptively simple question: how consistent is your strategy's growth?

Definition

R² is the coefficient of determination from a linear regression of your cumulative equity curve against trade number (or time).

Calculation:

  1. Plot your equity curve: X-axis = trade number (1, 2, 3, ..., N), Y-axis = cumulative equity
  2. Fit a linear regression line through these points
  3. R² = 1 - (SS_residual / SS_total)

Where:

  • SS_residual = sum of squared deviations from the regression line
  • SS_total = sum of squared deviations from the mean equity

R² ranges from 0 to 1:

  • R² = 1.0: The equity curve is a perfect straight line
  • R² = 0.0: The equity curve has no linear trend whatsoever

Interpreting R²

R² ValueQualityDescription
0.95 - 1.00ExcellentNear-linear growth, very consistent
0.85 - 0.95GoodSteady growth with manageable variation
0.70 - 0.85ModerateNoticeable drawdowns but overall upward trend
0.50 - 0.70WeakSignificant equity volatility, questionable consistency
<0.50PoorEquity curve is essentially random noise around a trend

Why R² Matters

1. Consistency Over Magnitude

Consider two strategies:

  • Strategy A: +200% return, R² = 0.45
  • Strategy B: +80% return, R² = 0.92

Strategy A made more money, but its equity curve was chaotic — periods of huge gains followed by deep drawdowns. Strategy B's equity grew steadily. Which would you trust with real capital?

Strategy B is almost always the better choice. A high-R² strategy is psychologically easier to trade, more predictable for risk management, and more likely to be genuinely robust rather than lucky.

2. Curve-Fitting Detection

If a strategy has excellent returns in a backtest but low R², the returns likely came from a few outsized trades. Remove those trades and the strategy may be unprofitable. A high R² means the edge is distributed across many trades, not concentrated in outliers.

3. Position Sizing Confidence

With high R², you can size more aggressively because the equity path is predictable. With low R², even optimal Kelly sizing becomes dangerous because the equity volatility makes drawdowns deeper and less predictable than the formula assumes.

4. Strategy Comparison

R² allows fair comparison between strategies with different return profiles. A strategy with moderate returns but R² = 0.90 may be preferable to one with high returns and R² = 0.60, especially when you factor in the psychological cost of drawdowns.

The R² vs Sharpe Ratio Relationship

R² and Sharpe Ratio are related but not identical:

  • Sharpe Ratio measures risk-adjusted return (mean return / standard deviation)
  • R² measures the linearity (consistency) of cumulative growth

A strategy can have a high Sharpe but moderate R² if returns are good on average but the equity curve has a curved (exponential) shape. Conversely, a strategy with a perfectly linear equity curve (R² = 1.0) will have a high Sharpe.

In practice, high R² almost always implies a respectable Sharpe, but the reverse is not always true.

Practical Calculation

For a quick approximation using your trade log:

  1. Number your trades 1 through N
  2. Calculate cumulative P&L after each trade
  3. Compute the Pearson correlation (r) between trade numbers and cumulative P&L
  4. Square it: R² = r²

Most spreadsheet tools and programming languages have built-in functions for this.

Improving R²

If your equity R² is low, investigate:

  1. Remove outlier trades: If R² improves dramatically, your strategy depends on rare events — not a sustainable edge.
  2. Segment by setup: Different setup types may have very different equity curves. A combined equity curve with low R² might contain two sub-strategies, each with high R².
  3. Reduce position sizing: Excessive sizing amplifies drawdowns, reducing linearity.
  4. Add a regime filter: If your strategy only works in certain conditions, adding a filter to sit out unfavorable periods can improve R².
  5. Check for time decay: A strategy that worked initially but degraded over time will have low R² — the regression line does not fit a curve well.

Common Pitfalls

  • Too few trades: R² is meaningless with <30 trades. Random sequences can show high R² over short samples.
  • Ignoring compounding: If you use percentage-based sizing, the equity curve should be exponential, not linear. In this case, run the regression on log(equity) instead.
  • Confusing R² with edge: R² = 0.95 on a declining equity curve still means you are consistently losing money. Always check the slope of the regression line too.

Interactive: Equity Curve Quality

Experiment with different win rates and payoff ratios to see how they affect equity curve smoothness. A high R² strategy produces a near-linear equity curve — consistent and predictable.

Equity Curve Simulator
34.8k28.6k22.4k16.2k10.0k0100200Trades
Final: $34281 (+242.8%)

Final Thought

Equity R² is the simplest and most intuitive measure of strategy quality. It answers the question every trader should ask: "Is my growth consistent, or am I just getting lucky?" A strategy with R² above 0.85 and a positive slope is one you can trade with confidence — not because it guarantees profits, but because its behavior is predictable enough to manage.