Forecasting US Equity Market Returns with Machine Learning (Alpha Architect)

Shiller’s CAPE ratio is a popular and useful metric for measuring whether stock prices are overvalued or undervalued relative to earnings. Recently, Vanguard analysts Haifeng Wang, Harshdeep Singh Ahluwalia, Roger A. Aliaga-Díaz, and Joseph H. Davis have written a very interesting paper on forecasting equity returns using Shiller’s CAPE and machine learning: “The Best of Both Worlds: Forecasting US Equity Market Returns using a Hybrid Machine Learning – Time Series Approach“, which effectively applies machine learning to an import investing problem. Image source: Improving U.S. stock return forecasts: A “fair-value” CAPE approach, Joseph Davis, et al. (2017)

Originally Published at Alpha Architect:

Forecasting US Equity Market Returns with Machine Learning

By Druce Vertes

January 7, 2020

Tags: Research Insights, Machine Learning