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Python
Python is where most of my quantitative research happens, using pandas for data manipulation, scipy for statistical tests, and Hypothesis for property-based testing. I write about using Python effectively for financial applications: structuring research code, avoiding common pitfalls with pandas, and leveraging the scientific Python ecosystem. These articles assume you know Python and want to apply it with the discipline that financial data demands.
2026-05
Quant
From Hypothesis to Production: A Quant's Productivity Toolkit
Productivity in quantitative work isn’t about doing things faster. It’s about knowing when to stop. A walkthrough of the tools and stages I use to take a trading strategy hypothesis from …