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.
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 on the future?" Short answer: technically yes, reliably no.Why This Question Actually MattersEvery day,...
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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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Hybrid Quant System Architecture: Integrating Risk Management, Position Sizing, and Execution in a Unified Framework
Most quant systems that fail in production don't have a signal problem. They have an architecture problem. Their signals work. Their backtests are...
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