Every strategy comes with a page of statistics designed to look impressive. Most of them can be improved by making the strategy worse, which is why knowing what each one actually measures is the difference between evaluating a system and admiring one.
The metrics, and what each hides
| Metric | What it measures | What it hides |
|---|---|---|
| Total return | How much it made overall | Everything — the path, the risk, the leverage |
| Win rate | How often it was right | Payoff size. A 90% win rate with one catastrophic loss is a disaster |
| Profit factor | Gross profit ÷ gross loss | Whether one enormous winner carried it |
| Sharpe ratio | Return per unit of volatility | Penalises upside volatility equally; flatters strategies that sell tail risk |
| Maximum drawdown | The worst peak-to-trough fall | How long it lasted, and how many times it nearly happened |
| MAR ratio | Annual return ÷ max drawdown | Little — this is one of the more honest single numbers |
The number most reports omit
Sample size. A strategy with a 2.4 Sharpe over 31 trades tells you almost nothing — that result is comfortably achievable by chance. The same Sharpe over 800 trades is a genuine claim.
Run the same win rate and payoff repeatedly and watch how different the outcomes look over small samples. That variation is exactly what a 30-trade report is showing you.
Drawdown is the number you actually live through
Return is what a report advertises; drawdown is what you experience. A strategy returning 40% a year with a 55% maximum drawdown is, for almost every human being, untradeable — because the drawdown arrives first and you stop.
- Maximum drawdown 18%
- Longest flat period 9 months
- MAR ratio 1.2
- Genuinely followable
- Maximum drawdown 52%
- Longest flat period 26 months
- MAR ratio 0.4
- Abandoned by most people before the recovery
A strategy shows a 2.6 Sharpe ratio over 34 trades. What is the correct conclusion?
Koi report dikhaye — 34% return, shaandaar ratio. Pehla sawaal: kitne trade pe? 30 trade ka matlab kuch nahi, woh kismat se bhi ho jaata hai. Doosra: sabse bade 5% trade hata do aur dobara chalao. Asli edge thoda kam hota hai; nakli edge poora gaayab ho jaata hai.
- Most strategy metrics can be improved by making the strategy worse.
- If you read only two numbers, read maximum drawdown and number of trades.
- Delete the best 5% of trades and rerun — a real edge degrades gracefully.
- Drawdown, not return, is what you actually live through.
- Indian backtests starting in 2003 or 2013 begin near a bottom and flatter everything.
Mark it done to track your progress through the curriculum.
Common questions
Short, direct answers to what people ask about this topic.
- profit factor meaning in a backtest
- Profit factor is gross profit divided by gross loss across every trade in the test, so a profit factor of 1.6 means the winners brought in 1.6 times what the losers gave away. Anything above 1 is profitable before costs are deducted. What the number hides is concentration — one enormous winner can carry it, so check whether the figure survives deleting the best few trades.
- annual return divided by maximum drawdown is known as
- The MAR ratio. It sets what a strategy earns in a year against the worst peak-to-trough fall it put you through, so 22% a year with an 18% maximum drawdown gives roughly 1.2, while the same 22% with a 52% drawdown gives about 0.4. It is one of the more honest single numbers on a strategy report, because unlike total return or win rate it is hard to flatter.
- is a high sharpe ratio over few trades meaningful
- Enough that the result cannot be explained by luck — a 2.6 Sharpe over 34 trades sits comfortably inside what randomness produces, while the same figure across several hundred trades is a genuine claim. Sample size is the precondition for every other metric mattering, and it is the number most often left out of a report. A useful companion test is to delete the best 5% of trades and rerun: a real edge degrades gracefully, a curve-fitted one collapses.
- what is a good sharpe ratio for a trading strategy
- There is no official threshold — above 1 is commonly described as good and above 2 as excellent, but the figure is meaningless without the trade count behind it. Sharpe measures return per unit of volatility and penalises upside volatility exactly as heavily as downside, which quietly flatters strategies that sell tail risk. Read it beside maximum drawdown and sample size rather than on its own.
- why do Indian equity backtests starting in 2003 look so good
- Because 2003 and 2013 both sit near the bottom of long bull runs, so almost any long-biased strategy tested from those dates looks excellent. Ask to see 2008, 2011, 2018 and 2020 broken out separately — a report showing only the aggregate is hiding the periods that decide whether the system is survivable. Live drawdowns also tend to run worse than backtested ones, because slippage widens precisely when markets move fastest.