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A worked example

The metrics below refer to this example: a Nifty options strategy backtested over three years with ₹10 lakh of starting capital.

Return metrics

Total return and CAGR

Total return is the overall gain as a percentage of starting capital. CAGR, the compound annual growth rate, converts it to a yearly rate so that strategies tested over different periods can be compared.

In the example, (15.2 / 10)^(1/3) − 1 = 15.0% a year. A CAGR means little on its own: 15% with a 14% drawdown is a different proposition from 15% with a 40% drawdown.

Expectancy

Expectancy is the average profit per trade after costs. It combines the win rate with the size of wins and losses.

In the example, 0.58 × 6,200 − 0.42 × 4,600 = ₹1,664 per trade. A positive expectancy is the minimum requirement for any strategy. Divide it by the average loss to get expectancy in units of risk: here about 0.36, meaning each trade earns on average 36% of a typical loss.

Risk metrics

Maximum drawdown

Maximum drawdown is the largest fall from a peak in the equity curve to the following trough, before a new peak. It is the worst experience a trader following the strategy would have had.

In the example, the account fell from a peak of ₹13.0 lakh to ₹11.15 lakh at one point, a drawdown of 14.2%. Ask whether you would have kept trading through that fall. Most traders overestimate their tolerance; a drawdown that reaches half your stated limit in live trading usually leads to abandoning the strategy. Our max drawdown calculator computes it from an equity series.

Drawdown duration matters too: how many months passed before the account made a new high. A strategy that spends a year under water is hard to follow even if the drawdown is shallow.

Volatility of returns

The standard deviation of periodic returns, usually monthly or daily, measures how bumpy the ride was. It is the denominator of the Sharpe ratio.

Largest loss and losing streaks

The largest single losing trade and the longest run of consecutive losses show what the strategy demands of your nerve and your margin. A strategy with a 58% win rate will have a streak of seven or more losses roughly once in 300 trades by chance alone, so a streak of seven in the example is normal, not a sign of failure.

Risk-adjusted ratios

Sharpe ratio

The Sharpe ratio is the return above the risk-free rate divided by the volatility of returns.

In India the risk-free rate is usually taken as the 91-day Treasury bill yield or the repo rate, around 6% to 6.5% in 2026. A strategy earning 15% with 8% volatility has a Sharpe of about 1.1. As a rough guide, a Sharpe above 1 is good for a retail strategy after costs, and above 2 is rare and deserves suspicion of overfitting. Our Sharpe ratio calculator does the arithmetic.

Sortino ratio

The Sortino ratio is the same as Sharpe but counts only downside volatility, since upside swings are not a problem. It is higher than Sharpe for strategies whose large moves are mostly gains, as with the example's 1.65.

Calmar ratio

Calmar divides CAGR by maximum drawdown: 15.0 / 14.2 = 1.06. It answers the question most traders ask first: how much return per unit of worst-case pain. A Calmar near or above 1 over three or more years is a reasonable bar.

Trade metrics

Win rate

The share of trades that made money. It is the most quoted metric and the least useful alone. Option-selling strategies often win 70% to 85% of the time and still lose money, because the losses are far larger than the wins. Trend-following strategies may win 35% of the time and make money because the wins are large.

Profit factor

Gross profit divided by gross loss. In the example, total winning trades of ₹11.22 lakh divided by total losing trades of ₹6.03 lakh gives 1.86. A profit factor below 1.2 leaves little room for costs and slippage that the backtest may have understated.

Average win and average loss

The reward-to-risk ratio of the strategy as traded, not as planned. A strategy designed with a 2:1 target-to-stop often shows 1.3:1 in the backtest because many trades exit early or get stopped at a worse price.

Number of trades

Statistical confidence depends on the sample. Thirty trades tell you little; three hundred, as in the example, give some confidence that the edge is not luck. Fewer than 100 trades is a warning sign, especially for strategies with many parameters.

Time in market

The share of time the strategy held a position. A strategy that is in the market 41% of the time earned its return with capital free the rest of the time, which matters when comparing it with a buy-and-hold index return.

Reading the equity curve

Numbers summarise; the equity curve shows. Look for:

• Steadiness. A curve that rises in steps across different market regimes is more trustworthy than one that made all its money in a single quarter.
• Regime dependence. Compare performance in trending and ranging years, and in high- and low-volatility periods such as 2020 and 2023.
• Recent performance. A strategy whose last year was flat may be losing its edge, whatever the three-year total says.
• Out-of-sample fit. If the backtest shows the period used to design the strategy and the period after it, the second part is the one that counts. See walk-forward testing.

The metrics that decide

For most retail strategies, three numbers settle the question:

1. Expectancy after realistic costs must be clearly positive, with at least 100 trades behind it.
2. Maximum drawdown must be one you would actually sit through, with margin to spare.
3. Calmar or Sharpe must hold up out of sample.

If all three pass, paper trading for a few weeks checks that live fills match the backtest's assumptions before any capital is at risk. Our guides on backtesting and common backtesting mistakes cover the process around the numbers.

Frequently asked questions