Equity Curve Analyzer
Analyze your equity curve for drawdown patterns, winning streaks, and regime changes. Enter values for instant results with step-by-step formulas.
Formula
Sharpe = (Avg Return - Rf) / StdDev x sqrt(12) | Max DD = (Peak - Trough) / Peak
The Sharpe Ratio measures risk-adjusted return by dividing excess return over the risk-free rate by the standard deviation of returns, annualized by multiplying by the square root of 12 for monthly data. Maximum drawdown measures the largest percentage decline from a peak to a subsequent trough in the equity curve.
Worked Examples
Example 1: 12-Month Trading Performance Analysis
Problem: A trader starts with $100,000 and records monthly returns of 5%, 3%, -2%, 4%, 6%, -1%, 3%, 5%, -3%, 2%, 4%, 7%. Risk-free rate is 5%.
Solution: Final Balance: $100,000 compounded through 12 months = ~$137,656\nTotal Return: 37.66%\nAvg Monthly Return: 2.75%\nMax Drawdown: occurs at the -3% month after peak\nSharpe Ratio: (2.75% - 0.417%) / 3.11% x sqrt(12) = ~2.60\nWin Months: 9 | Lose Months: 3\nBest Month: 7% | Worst Month: -3%\nMax Win Streak: 2 (months 4-5) | Max Lose Streak: 1
Result: Total Return: 37.66% | Sharpe: 2.60 | Max DD: 3.0% | Recovery Factor: high
Example 2: Volatile Strategy with Deep Drawdown
Problem: Starting balance $50,000 with monthly returns of 8%, -5%, 12%, -8%, 6%, -10%, 15%, -4%, 3%, -6%, 9%, 5%. Risk-free rate is 5%.
Solution: The high volatility creates large swings in the equity curve\nAvg Monthly Return: 2.08%\nStd Dev: ~8.2% (very high)\nSharpe Ratio: approximately 0.72 (below 1.0 = poor risk-adjusted)\nMax Drawdown: occurs during the -10% month sequence\nThis strategy is profitable but inefficient due to excessive volatility\nSortino Ratio will be higher since upside months are large
Result: Profitable but volatile | Sharpe: ~0.72 | Needs smoothing via position sizing
Frequently Asked Questions
What is an equity curve and what does it reveal about trading performance?
An equity curve is a graphical representation of your trading account balance over time, plotting each data point after every trade or at regular time intervals such as daily or monthly. The shape and characteristics of your equity curve reveal far more about your trading quality than simple profit and loss numbers alone. A smooth, upward-sloping equity curve indicates consistent profitability with manageable drawdowns, while a jagged or volatile curve suggests inconsistent results even if the endpoint shows a profit. Professional fund managers and prop firms evaluate traders primarily by their equity curve characteristics, including the smoothness of returns, depth and duration of drawdowns, and whether the curve shows consistent upward momentum or relies on a few large winning trades.
How do I interpret the maximum drawdown from my equity curve?
Maximum drawdown measures the largest peak-to-trough decline in your equity curve, expressed as a percentage. If your account grew from $100,000 to $120,000 and then dropped to $105,000 before recovering, the maximum drawdown is ($120,000 - $105,000) / $120,000 = 12.5%. This metric is critical because it represents the worst historical loss experience and indicates how much pain a strategy can inflict. Industry standards consider drawdowns below 10% as excellent, 10-20% as acceptable, and above 30% as high risk. Remember that maximum drawdown only tells you about the worst case so far, and future drawdowns could be deeper. Many risk managers apply a multiplier of 1.5x to 2x to expected maximum drawdown when planning for worst-case scenarios.
What is the Calmar Ratio and why is it useful for equity curve analysis?
The Calmar Ratio divides annualized return by maximum drawdown, providing a measure of return relative to the worst historical loss. A Calmar Ratio of 2.0 means your annualized return is twice your maximum drawdown, which is considered good. For example, a strategy returning 24% annually with a 12% maximum drawdown has a Calmar Ratio of 2.0. Values above 3.0 are excellent, indicating the strategy generates returns efficiently without deep drawdowns. The Calmar Ratio is particularly useful for evaluating strategies over longer time periods (3+ years) where maximum drawdowns have had sufficient time to manifest. Unlike the Sharpe Ratio which uses standard deviation, the Calmar Ratio directly addresses the worst-case scenario, making it more intuitive for risk-conscious traders who want to understand the relationship between reward and maximum pain.
How do I identify regime changes in my equity curve?
Regime changes occur when market conditions shift significantly, causing a previously profitable strategy to underperform or vice versa. You can identify regime changes by looking for inflection points in your equity curve where the slope changes noticeably, clusters of losing months that follow extended winning periods, significant changes in average monthly return comparing rolling 3-month periods, and breakdowns in the typical relationship between your strategy and market volatility. A simple method is to calculate a rolling 3-month average return and compare it to your overall average. When the rolling average drops more than one standard deviation below the overall average for two or more consecutive months, a regime change may be occurring. Professional traders use more sophisticated methods including analyzing the autocorrelation of returns and monitoring changes in market volatility regimes.
How many months of data do I need for reliable equity curve analysis?
For reliable equity curve analysis, a minimum of 12 months of data is recommended, with 24 to 36 months being ideal. With fewer than 12 months, your metrics are highly sensitive to individual months and may not capture the full range of market conditions your strategy will face. The Sharpe Ratio stabilizes after approximately 24 monthly observations. Maximum drawdown calculations require even longer periods because drawdowns tend to get deeper over time as more market regimes are encountered. A strategy with 6 months of data showing a 5% maximum drawdown should not assume this is representative of future worst-case scenarios. Many quantitative analysts recommend out-of-sample testing periods equal to at least half the in-sample period to validate that observed performance characteristics are genuine rather than artifacts of specific market conditions.
Is my data stored or sent to a server?
No. All calculations run entirely in your browser using JavaScript. No data you enter is ever transmitted to any server or stored anywhere. Your inputs remain completely private.