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 summaries of academic finance papers? Check out our Academic Research Insight category [...]
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 can be found hereWant to read our summaries of academic finance [...]
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 of risk and/or systematic mispricing. However, what if we could [...]
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 lot and we had to visit that exact same corner [...]
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. [...]
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 Earnings: New Data and Evidence" by Ethan Rouen, Eric So, [...]
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 use within Research. The first paper is an Editorial by [...]
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., when underlying reality is nonlinear with complex interactions). In this [...]
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 read our summaries of academic finance papers? Check out our Academic [...]
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 Learning Approach." The paper presents a strategy that forecasts industry [...]
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 Siri and Google Translate, to news recommendation systems and, of [...]