Essays · Operations Intelligence, AI and Quant
Hossein Narimani — Writing
In-depth writing on quant system design, operational AI, SaaS architecture, custom AI agents and founder execution systems.
Probability of Backtest Overfitting (PBO): How to Tell If Your Backtest Is Edge or Luck
The Probability of Backtest Overfitting (PBO) is the chance, from 0 to 1, that your best backtest falls below the median of its rivals out of sample. Test a hundred parameter sets, keep the best, and part of that "best" is luck. The question is not whether...
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What Makes an Automated Trading Strategy Good? Real Criteria Beyond a Beautiful Backtest
Most strategies that look excellent in a backtest were never designed to survive production.A trading bot is not good because its equity curve...
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Can Quant Trading Strategies Be Trained From OHLCV Data Alone?
Most people asking "can you train a strategy on OHLCV data" are really asking something else: "can I train a model on past prices and make money...
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Look-Ahead Bias in Backtesting: How Future Data Silently Contaminates Your Strategy Test
If your strategy backtest is showing brilliant results, there's a good chance something is wrong. Not because the strategy is bad — but because...
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Why Profitable Backtests Fail in Production: The Hidden Gap Between Backtesting and Reality
Every quantitative researcher eventually encounters the same paradox. A strategy looks exceptional in backtesting, produces attractive...
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