QuantProof Does Your Backtest Survive
Catch overfitted backtests before real money does
What it does
My Sharpe was 2.4. Win rate: 68%. Looked perfect until I traded it live. My entire edge was 3 lucky trades in 2020. So I built QuantProof. Upload your backtest CSV and find out if your edge is real or just luck. 38 checks in 2 seconds: overfitting detection, profit concentration, slippage sensitivity, alpha decay, regime testing, and 5 historical crash simulations. Connect Alpaca for broker-verified results. Free to validate. ₹999 for the full PDF + AI improvement plan
Does the same job
all alternatives →- HFHigh-frequency trading and market-making backtesting tool with examples2024 · github.com · ▲148
- QBQuantblocks - Backtest your trading strategies2012 · quantblocks.com · ▲99
We think backtesting is too difficult, this is our attempt to make it much easier and more fun - let us know what you think!
- BTBacktest Trading Strategies: A Quantopian Alternative2020 · tradytics.com · ▲35
- IBI built a tool to find trading signals that aren't just random luckSep 2025 · hikaro.app · ▲9
Hi HN, I'm a solo dev and for the last few months I've been building Hikaro, a tool to find statistically significant trading signals for [e.g., US equities, crypto, forex]. I built this to solve my own problem: I was tired of backtests that looked great on paper but failed in practice. Simple metrics like "win rate" can be misleading, so I wanted a way to quickly tell if a signal's performance was genuine or just noise. Hikaro ingests daily market data and runs statistical analysis on various trading signals. The goal is to surface signals with strong properties, like: Low p-value: Evidence…
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