Research
Code & Kapital research is written for readers who want more than a polished chart. The focus is on evidence, system design, and the practical details that determine whether a strategy survives beyond the notebook.
Philosophy
Point-in-time data handling before performance interpretation.
Validation that survives turnover, cost, and capacity assumptions.
Implementation detail treated as part of the research, not cleanup.
Clear documentation of model scope, limits, and decision rules.
Showing 6 of 8 articles in All Research.
Learn everything you need to know about margin and leverage in a portfolio construction setting, from volatility matching and implied margin to the way funding costs reshape the result in Python.
Minimum variance weighting minimizes total portfolio volatility by using the full covariance matrix, making diversification a system-level optimization problem rather than a one-asset-at-a-time rule.
A step-by-step derivation of the portfolio variance formula, showing why portfolio risk is written as wᵀΣw and why correlations matter as much as individual asset volatility.
The FRED API makes macro metadata, current observations, and revision-aware history unusually accessible, but the real step up comes from handling release timing and vintages with more discipline.
Why ticker-based systems fail, how OpenFIGI creates a stable identity layer, and where FIGI belongs inside a research-grade data pipeline.
Inverse volatility weighting changes portfolio behavior by scaling risk instead of capital, revealing how construction decisions reshape returns in systematic strategies.
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