AlphaAudit is a live interactive strategy IDE built for quantitative traders and researchers who are tired of discovering their backtest was a lie. Quant strategies are uniquely dangerous code. They don't throw errors when they're wrong — they just lose money. Look-ahead bias, survivorship bias, overfitting, incorrect Sharpe calculations — these bugs are invisible to standard code review but catastrophic in live trading. Senior quants catch them. Everyone else doesn't. AlphaAudit changes that. Paste your Python backtesting strategy into the editor, hit Run Audit, and within seconds IBM Bob — acting as a senior quant reviewer — identifies every statistical and logical flaw in your code, explains why each one is dangerous in plain English, and suggests a one-click fix. The equity curve visualizer makes the impact tangible: two diverging lines showing your reported backtest performance versus the adjusted reality after bias correction. The gap between those lines is the cost of your mistakes. Built during the IBM Bob Hackathon in May 2026, AlphaAudit demonstrates what happens when AI understands both code and domain. Bob doesn't just read syntax — it understands that a negative shift means look-ahead bias, that a static ticker list means survivorship bias, that seven optimized parameters with no out-of-sample test means overfitting. This is the tool every quant researcher wishes existed during code review. Now it does.
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