Empirical Asset Pricing

This repository documents Python code implementations for Empirical Asset Pricing (Bali, 2016). The code covers various topics including portfolio analysis and Fama-MacBeth regression analysis. The implementations are organized in the order they appear in the book.

Contents

1. Univariate Portfolio Analysis
2. Bivariate Independent-Sort Analysis
3. Bivariate Dependent-Sort Analysis

Overview

This repository serves as a resource for those interested in studying empirical asset pricing using Python. The code examples provided here follow the concepts presented in Empirical Asset Pricing by Bali (2016).

For the open-source PDF version of Empirical Asset Pricing, please refer to this link.

References

• Bali, T. G. (2016). Empirical Asset Pricing. John Wiley & Sons.

Feel free to explore the code and utilize it for your own research or learning purposes! If you have any questions or suggestions, please don't hesitate to reach out.