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.
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 wrong question: "Which architecture gives the highest accuracy?" That question is a trap.The right question...
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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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What Is Edge in Quantitative Trading Systems? Calculation Methods, Practical Uses, and Common Failure Modes
Most traders believe edge is simply a high win rate. That assumption destroys more trading systems than market volatility.A strategy can win only...
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