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-0.1.8.tar.gz
(16.0 MB
view details)
File details
Details for the file anomalylab-0.1.8.tar.gz.
File metadata
- Download URL: anomalylab-0.1.8.tar.gz
- Upload date:
- Size: 16.0 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.10.15
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 04481f2222a6f48158d6254349b8fc5bbc34af7c39a7cacde691e8c688189de4 |
|
| MD5 | b5e61b4ee9d4a2821edc4db0d0d08388 |
|
| BLAKE2b-256 | 3f9328f81b9178c6ced853763f51edb91ce3225c0d8eb8e805299fd087f0c61e |
