Computing Index Prices and Returns from prices/returns of financial assets
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Updated
Jul 4, 2019 - Julia
Computing Index Prices and Returns from prices/returns of financial assets
Calculate technical factors for stocks in an efficient, maintainable and correct way
Rewriting the code in "Machine Learning for Factor Investing" in Python
Web dashboard to visualize equity factor dynamics using solely publicly available data.
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.
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.
Machine Learning for Factor Investing: Python Version
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.
VAR vs. LSTM: Multivariate Forecasting of Factor Returns
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.
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
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.
Value or Momentum? Comparing Random Forests, Support Vector Machines, and Multi-layer Perceptrons for Financial Time Series Prediction & Tactical Asset Allocation
Risk Premia Estimation (FamaMacbeth and Three-pass)
众人的因子回测框架 stock factor test
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