Skip to main content
You optimize a strategy by chatting — “sweep the stop between 10 and 50 points” or “test the EMA period from 10 to 50.” AskFutures runs a backtest for every value in the range, ranks them by the metric you care about, and shows you which combination scored best. You then promote the winner into a new version with one more sentence.
Every run in a sweep is a normal, deterministic backtest — same real prices, same modeled costs. Optimization just runs many of them and compares the numbers. The AI doesn’t decide what’s “best”; the simulator does the math and the metric does the ranking. See optimization.

​
Before you sweep

Optimize a strategy that already backtests cleanly and shows a plausible edge — to refine it, not to rescue it. If the strategy fails to run, takes a handful of trades, or loses across the board, no range of stop sizes will fix it. Fix the logic in chat first (see iterate and refine), then sweep.

​
Run a sweep by chatting

1

Say what to sweep and over what range

Name a tunable number on the strategy card and give it a range. Plain English is enough:
  • “Optimize the stop between 10 and 50 points.”
  • “Sweep the EMA period from 10 to 50, step 5.”
  • “Try targets from 200to200 to 600 in $100 steps.”
If you don’t give a step, AskFutures picks a sensible number of evenly spaced test points and tells you how many runs that is.
2

Pick the metric to optimize

Tell it what “better” means for this idea — “rank by average P&L per trade,” “best total P&L,” or “best win rate.” If you don’t say, AskFutures will confirm the metric before it runs.
3

Check the size of the job, then run it

The strategy card shows the job before you commit — something like “1 parameter · 9 runs.” Two ranges multiply: a 5-value stop sweep crossed with a 4-value target sweep is 20 backtests. When it looks right, let it run.
4

Read the results and promote the winner

AskFutures backtests every combination, ranks them by your metric, and reports the winning parameter set. Like the look of it? Ask to apply it — the chosen values become a new saved version of the strategy.
An AskFutures optimization sweep showing a scatter chart and ranked results

​
Sweep one parameter or two

“Sweep the stop from 10 to 50 points in steps of 5.”AskFutures runs nine backtests — one per stop value — and ranks them. This is the fastest, clearest way to ask “what’s the best value for this one knob?”
Want a big sweep without a long wait? Wide ranges on stops and targets are cheap — the engine reuses the indicators and just re-simulates the exits. Wide ranges on indicator lengths (EMA, RSI, ATR windows) are slower because every value recomputes the indicators. Keep indicator ranges to a handful of values. See why some sweeps are faster.

​
Reading the scatter and the ranking

Each sweep finishes as a labelled batch — for example “Optimization 1 · Completed · 9 combinations · Best: $-2.97 avg” — naming the winning parameters and their score on your chosen metric.

The scatter chart

Each dot is one combination: the parameter value (or pair of values) against its score. Look for a broad cluster of strong results, not a single dot floating above the rest.

The ranked table

Every combination, sorted by your metric, with the parameter values and the score for each. The top row is the winner; download the full table as a CSV to compare every run yourself.
Read the scatter for shape, not just the peak. A wide plateau of decent results is far more trustworthy than one tall spike surrounded by losers.

​
Don’t overfit

A sweep finds the parameters that fit the past best — which is not the same as the parameters that will work next. The more combinations you try, the more likely the “winner” is just the one that happened to line up with old noise. Treat the best result as a hypothesis, not a guarantee.Guard against it:
  • Prefer wide, robust plateaus over a single razor-thin peak. If only one exact value works and its neighbours fall apart, that’s a red flag.
  • Keep sweeps small and meaningful — one or two parameters, sensible ranges.
  • Re-test the winner on a different window (a more recent stretch you didn’t sweep over) before you trust it.
Past performance does not guarantee future results. Always test before you trade.

​
Promote the best combination

When you’ve found a winner you like, ask AskFutures to apply it — “use the best stop from that sweep” or “apply the winning parameters.” The chosen values become a new saved version of the strategy, with its own freshly-computed backtest. The version you swept from stays exactly as it was, so you can compare them and revert if the optimized version doesn’t hold up out of sample.

​
Next steps

Version & compare

Optimization (concept)

Iterate & refine

Run & read a backtest