News and its Impact on Risk and Returns Around the World
How news and its context drive risk and returns around the world Charles Calomiris and Harry MamayskyJournal of Financial Economics, August 2019A version of this [...]
How To Design Machine Learning Models – A Market Timing Example
We at ENJINE are big believers in the potential of machine learning (or as some call, “artificial intelligence”) to transform asset management. However, it’s fair [...]
Predicting Bond Returns? Focus on GDP Growth and Inflation Indicators
Predicting Bond Returns: 70 Years of International Evidence Guido Baltussen, Martin Martens, Olaf PenningaWorking PaperA version of this paper can be found hereWant to read our [...]
Fascinating Research Alert: Earning Calls, Clichès, and Negative Abnormal Returns
When More or Less is Less: Managers' Clichès J. Klevak, J. Livnat, and K. SuslavaJournal of Financial Data Science, Summer 2019A version of this paper [...]
Machine Learning and Investing: Forecasting Fundamentals w/ Ensembles
Quantitative factor portfolios generally use historical company fundamental data in portfolio construction. The key assumption behind this approach is that past fundamentals proxy for elements [...]
Deep Reinforcement Learning for trading applications
This blog talks about reinforcement learning for trading applications. Once one of my pups found half a roast chicken in the corner of a parking [...]
Forecasting US Equity Market Returns with Machine Learning
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 [...]
Core Earnings: New Data and Evidence
Researchers love novel datasets--it gives them a new set of information to conduct studies and test theories. That brings us to this paper, titled "Core [...]
Alpha Architect Weekly Recap: Editorials on Machine Learning
You can watch the video via this link: https://www.youtube.com/embed/tVwwZ1-bThI This week Ryan and I discuss two editorials on machine learning and its impact and [...]
Machine Learning Classification Methods and Factor Investing
In the last post in our machine learning series, we showed how nonlinear regression algos might improve regression forecasting relative to plain vanilla linear regression (i.e., [...]
A Protocol to Prevent “Quants Gone Wild”
A Backtesting Protocol in the Era of Machine Learning Rob Arnott, Campbell Harvey, and Harry MarkowitzWorking paperA version of this paper can be found hereWant to [...]
Machine Learning for Financial Market Prediction — Time Series Prediction With Sklearn and Keras
Recently, Wes pointed me to this interesting paper by David Rapach, Jack Strauss, Jun Tu and Guofu Zhou: "Dynamic Return Dependencies Across Industries: A Machine [...]
Machine Learning for Investors: A Primer
If you are out to describe the truth, leave elegance to the tailor. — Albert Einstein Machine learning is everywhere now, from self-driving cars to [...]