A Python package for empirical asset pricing analysis.
Project description
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:
pip install anomalylab
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
anomalylab-0.3.6.tar.gz
(16.0 MB
view details)
File details
Details for the file anomalylab-0.3.6.tar.gz.
File metadata
- Download URL: anomalylab-0.3.6.tar.gz
- Upload date:
- Size: 16.0 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.10.15
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ec32af55554eda096d0ac1608ad1bc99e1df5cdc57f1846f3b8d1f6320af324b
|
|
| MD5 |
75cdf6361de26327a4327af8a8a56f51
|
|
| BLAKE2b-256 |
195159f95548c263ea3ac405cc573ed8e3eb0fca274a48dd37334d6c246128f9
|
