# How to backtest a stock scan, no code needed

> A five-step method for testing any screener scan against history: pick a horizon, replay the signal, read hit rate and payoff separately, and the three biases that fake good results.

Canonical: https://patternsradar.com/blog/how-to-backtest-a-stock-scan

Published 2026-08-15. Related scans: https://patternsradar.com/screener/golden-cross.md, https://patternsradar.com/screener/volume-breakout.md, https://patternsradar.com/screener/rsi-oversold-turn.md

Every scan is a claim. "RSI crossing above 30 in an uptrend" *claims* that such stocks tend to rise afterward. Run the scan without testing the claim and you are trading folklore; test it and you are trading evidence. The difference costs about ten minutes.

This is the method, whether you use the built-in replay here or a spreadsheet and patience.

## Step 1: State the claim precisely

"Finds good stocks" is not testable. **"Stocks matching this scan outperform over the next 10 sessions"** is. Fix three things before looking at any results: the exact conditions, the holding horizon (a swing scan tested on 6-month returns tells you nothing), and what counts as success — beating zero? beating the index?

## Step 2: Replay, don't remember

For each trading day in your test window: run the scan *as of that day*, record the matches, record their forward return over your horizon. Every scan page on this site does this automatically for the past year — the hit-rate panel on, say, the [golden cross](https://patternsradar.com/screener/golden-cross.md) is exactly this replay. What matters is that the signal list for each historical day was computed from data available *on that day*. Which brings us to the ways this silently goes wrong.

## Step 3: Know the three result-fakers

**Survivorship bias.** Testing only on stocks that exist *today* flatters every strategy — the delisted losers are precisely the stocks your scan would have matched on the way down. The dataset here keeps them; a hand-built test in a spreadsheet usually cannot.

**Lookahead bias.** Any condition computed with information from after the signal date — an adjusted price series that didn't exist yet, a "top 500 by turnover" list drawn from today's rankings. Subtle versions of this inflate results by a few percent, which is more than most real edges.

**Overfitting.** Tune thresholds until last year looks perfect and you have memorised last year, not learned a pattern. The tell is fragility: if `rsi < 32` tests beautifully and `rsi < 30` tests poorly, you have curve-fit noise. Real effects are threshold-tolerant.

## Step 4: Read hit rate and payoff as a pair

A 45% hit rate with winners twice the size of losers is a good system; a 70% hit rate that gives it all back on the losers is a famous way to bleed. Neither number means anything alone. When you replay [a volume breakout scan](https://patternsradar.com/screener/volume-breakout.md), the question is not "how often was it green?" but "what did the average win pay, against the average loss?" — and whether *enough signals* exist per month for the edge to matter in practice.

## Step 5: Respect the regime

One year of replay is one market regime. A momentum scan tested across a trending year will flatter itself; the same scan in a sideways year pays whipsaw tax. Read results as "how this signal behaved in *this* regime," check the failure clusters — do losses bunch in specific months? — and prefer scans whose edge is explainable over ones that merely test well. [RSI oversold turning up in an uptrend](https://patternsradar.com/screener/rsi-oversold-turn.md) has a mechanism (one-sidedness resolving in favourable ground); a mechanism is what you fall back on when the recent numbers wobble.

## Make it a habit

The workflow that compounds: build the scan in [the query language](https://patternsradar.com/docs/sift.md), or start from [a preset](https://patternsradar.com/scans.md); replay it before running it live; keep it only if the claim survives; retest when the regime changes. No code at any step — the replay panel does the bookkeeping. The scans that survive this process are few, and they are yours in a way no copied scan ever is: you know *why* you run them, and you know what their failure looks like before it arrives.