Skip to main content
A backtest is only as useful as your confidence in it. When AskFutures turns your plain-English strategy into rules and replays them over real historical prices, you shouldn’t have to take the results on faith. This guide covers the three ways to check the work, from a quick visual once-over to a full audit of the raw numbers.
The numbers themselves come from a fixed, deterministic simulator — the AI never invents performance figures (see Is the backtest real?). Validation is about the layer above that: confirming the rules being simulated are the strategy you meant, and that each trade behaved the way you intended.

​
1. Inspect every trade visually

Open your strategy card and click the Trades tab. Every trade from the backtest is there — entry and exit times, long or short, time in trade, P&L, and how far each trade moved against you (MAE) and in your favor (MFE). Sort the whole backtest by entry time, exit time, duration, P&L, or drawdown, or filter to just longs or shorts. Click any trade and it opens full-screen on a candlestick chart of the market around it:
  • Entry and exit markers are placed at the exact fill timestamps — not snapped to the nearest bar — with dashed lines at your entry and exit prices, so you can see precisely where each trade got in and out relative to the price action.
  • The header shows the trade’s direction, its signed P&L, and why it exited — stop, target, trailing stop, session close, or signal, among others — so you can check that your risk rules behaved the way you intended.
  • Each chart includes about 20 bars of context before the entry and after the exit, so you see the setup and the follow-through, not just the trade. Hovering any bar shows its open, high, low, close, and volume.
  • Use the arrow keys to step through trades one by one.
Pair this with the exit-reason breakdown in extended metrics: if a number there looks off (say, everything exits on session close), stepping through a few of those trades on the chart usually shows you why.

​
2. Audit the exported data

For a deeper check, click “Download trades with signal info” on your backtested strategy card. You get a CSV file — it opens directly in Excel or Google Sheets — built so that every trade can be independently verified:
  • One row per trade, straight from the simulator’s trade log: entry and exit timestamps, the filled prices and the raw source prices before tick rounding, direction, and the exit reason (stop, target, trailing stop, session close, signal, and so on), plus the stop and target levels that were live on the trade.
  • P&L, itemized. Each row shows gross P&L, the deducted costs (slippage plus commissions, combined in one cost column), and net P&L separately — so you can recompute the result yourself from the prices and the contract’s tick value, by hand or with a formula.
  • The market state at entry, attached. Each trade row is joined with the strategy’s computed indicator and signal columns from the latest available bar at or before the entry. You don’t just see that a trade happened — you can compare the market state the strategy saw at entry against the rules you described.
  • MAE and MFE per trade, so you can sanity-check stop and target placement against how trades actually behaved.
Because the engine is deterministic, the export always reconciles to the headline metrics — the same rules, data, and simulation settings reproduce the same results. See Exportable artifacts.

​
3. The automated rules review

The step you never see is the one that matters most: making sure the rules that get backtested are the strategy you actually described. After your request is parsed into executable rules — and before anything is backtested — an independent review pass audits the translation:
  • Your request is first split into a ledger of fragments — verbatim quotes of your own words (“go long when the 20 EMA crosses above the 50”, “stop at 10 ticks”, …). The parser must declare which rule covers each fragment.
  • A fresh review call — with no memory of writing the rules, and not allowed to edit them — then compares each quoted fragment against the actual parsed rules: same signal, same data series, same direction, same level, same units. It’s given the contract’s tick size and tick value so unit conversions are checked arithmetically. A claim of coverage isn’t accepted as evidence — the reviewer verifies the rule really expresses your clause.
  • Every fragment gets a verdict, and anything short of a faithful match — a rule that says something different from your words, a clause that never made it into the rules, or one written off as unsupported when it shouldn’t have been — automatically sends the strategy back to be re-parsed with the specific problems spelled out.
  • If a rule is still known to be wrong after that, the strategy is not built and nothing is backtested — we’d rather stop than show you results for a strategy you didn’t ask for. Anything that couldn’t be fully supported is surfaced as an explicit caveat in the chat.
The review catches translation errors, not strategy design flaws. A faithfully-translated bad idea still backtests badly — that’s what the numbers in Run and read a backtest are for.
Backtest results are hypothetical and simulated — no real trades were placed. Simulated results are designed with the benefit of hindsight and can under- or over-state live outcomes. Past performance does not guarantee future results. Always test before you trade.

​
Next steps

Run and read a backtest

Every chart and number a backtest produces, and how to read them.

Is the backtest real?

Where the AI stops and the deterministic math begins.

Iterate and refine

Found something off? Change one rule and re-run.

Backtesting

How the simulation works, what’s modeled, and the exportable artifacts.