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.
Building a Market Regime Detection System with Hidden Markov Models and Bayesian Filtering
Most trading strategies are designed with one implicit assumption: market behavior is static. A model gets optimized on historical data, parameters get tuned, and the system goes to production. As long as the market regime hasn't changed, everything looks...
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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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Quant Research vs Quant Trading: Signal Discovery vs Capital Execution in Quantitative Systems
Most people treat Quant Research and Quant Trading as different labels for the same profession. Operationally, they are two separate layers of the...
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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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How Bad OHLCV Data Destroys Trading Strategies: A Practical Framework for Market Data Quality Assurance
Most trading strategy failures are blamed on poor signal design, weak indicators, overfitting, or flawed machine learning models. In practice, one...
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