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-0.2.6.tar.gz
(16.0 MB
view details)
File details
Details for the file anomalylab-0.2.6.tar.gz.
File metadata
- Download URL: anomalylab-0.2.6.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 |
8e0aea79593bfd665e46a77b0b6395c07eddf588089518d2932752065ae3e781
|
|
| MD5 |
c231f952c93867977893fadde11757da
|
|
| BLAKE2b-256 |
e2c7d5b278ae9722be89df1d1f660967a6afff35fbc076e8e3c51c20c8d0836a
|
