How to spot a curve-fit indicator: 5 questions before you buy an algo

Almost every indicator looks incredible in the screenshot — a tidy equity curve, a 90%-something win rate, arrows that always seem to land on the low and the high. Then you run it live and it falls apart. Nine times out of ten, the reason has a name: curve-fitting.

Curve-fitting (or over-optimization) is what happens when a strategy is tuned until it looks perfect on one specific slice of history — the exact data it was tested on. Every parameter is nudged to dodge that period's losing trades. The result isn't an edge; it's a very detailed memory of the past. The moment the market shows the tool something it hasn't seen, the illusion breaks — and your account, not the vendor's, pays for it.

You can't audit someone else's code before you buy. But you can ask five questions that a curve-fit product almost never survives.

1. Was it tested on data it was never tuned on?

This is the single most important question. A backtest on the same data a strategy was built on proves nothing — of course it looks good, it was designed to. What matters is out-of-sample performance: results measured on data the model never saw during development.

• Good answer: the vendor separates a training period from a hold-out period they never touched while tuning, and reports the hold-out numbers openly.
• Red flag: a single glorious backtest over “all history,” with no mention of what was held back. If everything was used to tune, nothing was left to test.

2. Does it repaint?

A repainting indicator quietly redraws its own history, so the arrows on your screen line up with hindsight that wasn't available in real time. It makes any backtest meaningless. Ask directly, and know that you can verify it yourself — you don't have to take anyone's word for it.

• Good answer: “Non-repainting — signals are fixed once the bar closes,” plus a way to check.
• Red flag: vague reassurance, or a demo that only ever shows historical bars where repainting is invisible.

3. Are trading costs included?

Spread, commission, and slippage are the difference between a strategy that works on paper and one that works in an account. A high-frequency signal that ignores costs can look wildly profitable and lose money the instant it's traded for real.

• Good answer: results are reported after realistic costs, and the vendor says so plainly.
• Red flag: frictionless, cost-free backtests — the more trades the strategy takes, the more this matters.

4. Can you see every trade — including the losers?

A curated highlight reel of winners tells you nothing. A real edge is visible in the losses too: how often they happen, how big they are, and whether the wins genuinely outweigh them over time. The only honest version of a track record is the complete one.

• Good answer: a public, ongoing record where every trade appears — wins and losses — the moment it closes.
• Red flag: hand-picked winning screenshots and a headline win rate with no way to check it.

5. Does it ever tell you to do nothing?

Markets spend a lot of time in noise where no edge exists. A tool that always has a signal ready is optimizing for engagement, not for your results. The discipline to say “stay out” is a feature, not a gap — and it's often the most valuable call a tool can make.

• Good answer: the tool is selective and explicitly flags when conditions don't support a trade.
• Red flag: a constant stream of signals on every symbol, every timeframe, all day.

None of this guarantees a profit — nothing does. But these five questions reliably separate a tool built to be measured from one built to be sold. Ask them before you pay.