We run your strategy on about five years of historical data, with spread, commission and slippage included, and show you exactly how it would have performed, including where it struggled.
An illustrative demo strategy. Your report has the same parts, calculated from your own strategy's trades.
5 years to Sep 2026 · 0.5% risk per trade · after spread, commission and slippage
Starting balance
$50,000
Final balance
$89,179
Net profit
+78.4%
Annual return
+12.3%
Max drawdown
−6.5%
Trades
513
Win rate
44.8%
Profit factor
1.41
Average trade
+$76.37
Avg win : avg loss
1.77R : 1.02R
Sharpe ratio
1.86
Longest losing streak
9 trades
Monthly results
43 up · 17 down
Spread, commission and slippage are small on each trade, but over hundreds of trades they decide whether a strategy makes money.
The same 513 demo trades over 5 years. Costs of 0.08R a trade (spread, commission, slippage) take $20,283 off the result. Leave them out and almost any strategy looks better than it is.
A strategy tuned on all five years will always look good on those five years. Walk-forward testing tunes on one stretch, tests on the next, and repeats, so the results are honest.
The green test windows join up into 3 years of results from settings that never saw that data: a far more honest estimate than one backtest tuned on everything.
Backtests run on historical market data appropriate to the instrument and timeframe being tested.
Strategies are typically tested against approximately five years of data, measured backward from the current date.
Where appropriate, results are examined across different time windows to reduce overfitting to a single period.
Commissions and fees can be modeled into results for a more realistic picture of net performance.
Bid/ask spread assumptions are factored in, since they directly affect entry and exit pricing.
Estimated slippage can be applied to account for the gap between expected and actual execution price.
Peak-to-trough decline is tracked closely, since it reflects the real emotional and capital cost of a strategy.
How capital is allocated per trade shapes both return potential and risk exposure.
Sharpe ratio, Sortino ratio, and risk/reward are calculated to contextualize returns against volatility.
The equity curve visualizes how account value evolves over the test period, trade by trade.
Win rate, profit factor, average trade, and trade count round out a full performance picture.
We look at how sensitive results are to small changes in parameters or market conditions.
Each stage has to agree with the one before it before more money is put at risk.
Backtest
About 5 years of data, costs included
Demo account
4–8 weeks or 30–50 trades, no real money
Small live size
25–50% of the intended size
Full size
Only while results keep matching
About five years, counted back from today, where good data exists for the instrument and timeframe. Every report states the exact period.
Only if it's honest: real costs included, no peeking at future data, and results checked on data the settings weren't tuned on. We do all three, and still treat a backtest as evidence, not a promise.
At least 100, and more is better. Fewer trades leave too much room for luck to make a strategy look better, or worse, than it is.
Yes, once its rules are written exactly. That's the first step of every project.
Yes. Every report comes with the full list of trades, so you can check any result yourself.
Historical backtest results are hypothetical and do not guarantee future performance. Actual results may differ due to market conditions, liquidity, spreads, slippage, execution, fees, and other factors. Nothing on this website constitutes investment advice.
