Essays · Operations Intelligence, AI and Quant
Hossein Narimani — Writing
In-depth writing on quant system design, operational AI, SaaS architecture, data, forecasting and founder execution systems.
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 of the most destructive failure modes sits much lower in the stack: market data quality.A strategy built on...
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Complete Guide to OHLCV Data Cleaning in Big Data Pipelines: Frameworks, Failure Modes, and Production-Grade Implementation
Most quantitative trading failures do not begin with the model. They begin with the data. OHLCV datasets sit underneath backtesting engines, alpha...
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