Rewriting the code in "Machine Learning for Factor Investing" in Python
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Updated
Feb 9, 2021 - Jupyter Notebook
Rewriting the code in "Machine Learning for Factor Investing" in Python
众人的因子回测框架 stock factor test
Value or Momentum? Comparing Random Forests, Support Vector Machines, and Multi-layer Perceptrons for Financial Time Series Prediction & Tactical Asset Allocation
Calculate technical factors for stocks in an efficient, maintainable and correct way
Web dashboard to visualize equity factor dynamics using solely publicly available data.
In this study, I empirically and statistically investigate the credibility of common asset pricing beliefs using data from S&P 500® constituents from January 2010–December 2020.
Data Science Project: Replication of "Forest Through the Trees: Building Cross-Sections of Stock Returns" - creation of assets to test validity of factor models with Python
VAR vs. LSTM: Multivariate Forecasting of Factor Returns
Machine Learning for Factor Investing: Python Version
A project to estimate a stock's risk with a linear regression model in Python, using the Fama-French Carhart model and live data from Yahoo Finance.
University Project: constructing portfolios by blending different types of factor portfolios (low-beta, value, and momentum). We investigate different techniques to weight our portfolio and calculating a combined score.
Risk Premia Estimation (FamaMacbeth and Three-pass)
Computing Index Prices and Returns from prices/returns of financial assets
Python code for Swade et al. (2023) "Why Do Equally Weighted Portfolio Beat Value-Weighted Ones?" The Journal of Portfolio Management, 49 (5), 167–187.
This code compiles the Dick-Nielsen (2012) filters to clean the Enhanced TRACE data set. It only compromises data cleaning steps. I did not provide parts where he suggests removing agency transactions.
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