Metadata-Version: 2.1
Name: AnomalyLab
Version: 0.1.6
Summary: A Python package for empirical asset pricing analysis.
Author: FinPhd
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: statsmodels
Requires-Dist: linearmodels
Requires-Dist: rich
Requires-Dist: tqdm
Requires-Dist: deprecated
Requires-Dist: openpyxl
Requires-Dist: seaborn
Requires-Dist: matplotlib

# AnomalyLab

## Authors

Chen Haiwei, Deng Haotian

## Overview

This Python package implements various empirical methods from the book *Empirical Asset Pricing: The Cross Section of Stock Returns* by Turan G. Bali, Robert F. Engle, and Scott Murray. The package includes functionality for:

- Summary statistics
- Correlation analysis
- Persistence analysis
- Portfolio analysis
- Fama-MacBeth regression (FM regression)

Additionally, we have added several extra features, such as:

- Missing value imputation
- Data normalization
- Leading and lagging variables
- Winsorization/truncation
- Transition matrix calculation

## Installation

The package can be installed via:

```bash
pip install anomalylab
```
