Testing a Stock Factor with Daily Cross-Sectional Regressions

Summary

This example tests whether market capitalization is associated with next-day stock returns using repeated cross-sectional ordinary least squares regressions. It joins Chinese stock factor data to daily bars, calculates forward returns from the next close, standardizes market capitalization within each date, and fits a separate regression for every date. The resulting intercepts and factor slopes are collected for descriptive analysis across time.

The document provides code and a method, but no regression output, significance tests, or investment performance results. Its preprocessing also warrants care: missing raw market-cap and return values are filled with overall sample means after the standardized factor is created, so missing standardized values may remain. The example does not discuss survivorship, outliers, trading costs, or whether the forward-return alignment and data availability avoid look-ahead bias. The procedure is therefore a basic research template, not evidence that the factor predicts returns.

Key ideas

• The example joins Chinese stock factor observations to daily bar data and constructs next-day returns.
• Market capitalization is standardized cross-sectionally within each date.
• A separate ordinary least squares regression estimates the factor slope for every date.
• The time series of regression coefficients can be summarized to assess coefficient behavior.
• No results are reported, and data cleaning and bias controls require further scrutiny.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.