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Free backtesting platform: honest or pretty?
A backtesting platform is only as good as the lies it refuses to tell you. Before trusting any free platform's numbers, check five things: data, costs, validation, transparency, and survivorship. This guide walks through each check, so you can evaluate any tool — including this one.
- Data: real bars with source and date range stated — not synthetic fillers
- Costs: spread, slippage and swap modeled, with a visible cost assumption
- Validation: out-of-sample windows and walk-forward built into the workflow
- Transparency: every strategy shows its rules, its data, its exact window
- Survivorship: a library that only shows winners hides the losers — check the full funnel
Check 1 — Data quality
Free platforms often cut corners on data: short windows, cleaned bars with gaps filled silently, or synthetic prices that never existed. Ask three questions: which market and timeframe, from which source, and over what date range? If the platform cannot answer, the data is probably the catch.
For meaningful results you want years, not months, of raw bars — and the platform should state exactly what was used, because a backtest is only as honest as its input series.
Check 2 — Cost modeling
The most common way free platforms flatter you is by ignoring costs. A strategy that makes 2 pips per trade is dead after a 1-pip spread — the model must subtract spread, swap and slippage on every single trade, not just mention them in a footnote.
Look for a visible cost assumption you can change: if you cannot set spread or slippage yourself, assume the tool is hiding something.
Check 3 — Out-of-sample validation
A platform that shows one full-sample equity curve is showing you the test set your strategy was optimized on. The honest workflow splits history: optimize on one part, verify on another, and repeat forward — walk-forward analysis is the gold standard.
If out-of-sample or walk-forward results are missing from the interface, every number on the platform is potentially curve-fit.
Check 4 — Transparency
Every strategy should show its exact rules, its data window, its cost assumptions and its validation results — including failures. Tools that only expose winners, or that summarize results without letting you inspect the rules, are designed to sell you hope, not evidence.
Check 5 — Survivorship
If a strategy library only displays strategies that made money, you are looking at a curated highlight reel. The honest number is the funnel: how many strategies were generated, how many passed each gate, and how many reached deployable status. EasyQuant publishes this honesty aggregate publicly.
How EasyQuant compares
EasyQuant is free to start (50 backtests and the robustness checks per day), uses real bars with stated sources, models costs conservatively by default, and forces out-of-sample validation through a fixed pipeline. The transparency report shows the library-wide honesty aggregate — how many strategies passed versus were flagged. We are not saying you should trust us because we say so; we are saying the checks above are all publicly inspectable on this platform.
FAQ
- What is the catch with free backtesting platforms?
- Usually data quality, hidden costs, or a biased showcase of results. A good free platform stays transparent about assumptions and shows failures as clearly as successes.
- How much data do I need for a meaningful free backtest?
- Years, not months. If a platform only offers short windows, treat every result as unvalidated.
- Can free platforms be trusted for real money decisions?
- Trust the process, not the promise: cross-check one strategy on a second platform and paper trade before real money. Healthy skepticism is the best tool.
- Is free backtesting software good enough to learn with?
- Yes — the best free tools are excellent for learning the workflow and for rough validation. Just never skip the five checks before treating a free result as evidence.
- What makes a backtesting platform 'honest'?
- Look-ahead-free bars, visible and adjustable cost assumptions, out-of-sample validation, transparent rules, and a survivorship-aware view of the strategy funnel.
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Not investment advice. Historical results do not guarantee future performance. EasyQuant is a research factory — you execute on accounts you control.