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.
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 rises. It is good because its decision logic, execution, and risk controls remain coherent under real market...
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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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Deep Learning Prediction Models for Stock OHLCV Data: A System Design Framework
The Real Problem: Why Deep Learning on OHLCV Data Usually DisappointsMost teams building deep learning models for stock prediction start with the...
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How Much Does It Cost to Build a Quant System? A Realistic Cost Model for Founders and Operators
Most pricing conversations about quant systems start in the wrong place. They treat strategy code, research, execution, and risk control as if...
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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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