Analyst Expectations
Forecasted Earnings Per Share
An analyst-estimates signal that ranks stocks by the level of their forward consensus earnings per share.
Code & Kapital
A quantitative research operation built like a serious investment firm.
Code & Kapital publishes applied work on signals, portfolio construction, strategy behavior, and systematic investing, supported by the data discipline, backtesting framework, and research controls required for real capital.
Current themes
Signal research with allocator-grade standards
Portfolio construction under real-world constraints
Strategy behavior across regimes and market environments
Research systems built for repeatability and auditability
Positioning
Built for quantitative researchers, engineers, PMs, allocators, and sophisticated investors who care about process quality as much as outcomes.
Featured Signals
The signal library is the main body of work.
Core signal reports are published as standalone research objects with definitions, portfolio formation context, and validation sections that expand over time.
Risk Exposures
Liquidity Beta
A liquidity-risk signal that measures how strongly a stock's returns load on changes in aggregate market illiquidity.
Risk Exposures
CAPM Beta
The classic market-beta signal that estimates how strongly a stock amplifies or dampens broad market moves.
Featured Research
Research is the core product.
Recent work spans signal research, strategy evaluation, portfolio construction, and implementation-aware quantitative investing. Each piece is written to stand on evidence, not presentation.
Portfolio Construction
Leverage and Margin in Python: Scaling Minimum Variance to Equal Weight Risk
A raw minimum variance portfolio often looks safer because it is simply running less risk. A better comparison is to scale it up to the volatility of equal weight, then make the borrowing cost explicit.
By Code & Kapital Research
Read articlePortfolio Construction
Minimum Variance Weighting: How Covariance Shapes Portfolio Risk
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.
Code & Kapital ResearchRead research
Portfolio Construction
How to Calculate Portfolio Volatility from the Covariance Matrix
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.
Code & Kapital ResearchRead research
Education
Video as an extension of the research.
Educational media carries the same implementation-focused editorial standard as the written research.
Signals
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Momentum Investing and Signal Research
An introduction to momentum as a quantitative signal, including the core intuition behind trend persistence and how momentum ideas fit into systematic research.
Portfolio Construction
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Leveraging and Applying Margin in Python
Learn how to lever a minimum variance portfolio up to the volatility of an equal weight portfolio and how to infer the implied margin behind that comparison.
Portfolio Construction
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Minimum Variance Weighting: How the Method Works
See how minimum variance weighting uses the covariance matrix to minimize total portfolio risk and why estimation choices materially affect the final allocation.
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