Investing Research Articles

How should investors evaluate the effectiveness of a safe haven asset? In their July 2020 paper entitled “A Safe Haven Index”, Dirk Baur and Thomas Dimpfl devise and apply a safe haven index (SHI) to evaluate over 20 individual potential safe haven assets. SHI consists of seven equal-weighted assets: gold, Swiss franc, Japanese yen, 2-year,… Keep Reading

Below is a weekly summary of our research findings for 7/27/20 through 7/31/20. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs. Subscribers: To receive these weekly digests via email, click here to sign up for our mailing list.

Will machine learning revolutionize asset management? In their January 2020 paper entitled “Can Machines ‘Learn’ Finance?”, Ronen Israel, Bryan Kelly and Tobias Moskowitz identify and discuss unique challenges in applying machine learning to asset return prediction, with the goal of setting realistic expectations for how much machine learning can improve asset management. Based on general… Keep Reading

Below is a weekly summary of our research findings for 7/20/20 through 7/24/20. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs. Subscribers: To receive these weekly digests via email, click here to sign up for our mailing list.

Is a 10-month simple moving average (SMA10) the best SMA for long-term crossing signals? If not, is there some other optimal SMA lookback interval? To check, we compare performance statistics for SMA crossing signals generated by lookback intervals ranging from 2 (SMA2) to 48 months (SMA48), as applied to the S&P 500 Index. Using monthly… Keep Reading

Do returns for “smart beta” indexes, constructed to exploit research on one or more factors that predict individual stock returns, reliably predict returns for exchange-traded funds (ETF) introduced to track them? In the June 2020 version of their preliminary paper entitled “The Smart Beta Mirage”, Shiyang Huang, Yang Song and Hong Xiang compare returns of… Keep Reading

Below is a weekly summary of our research findings for 7/13/20 through 7/17/20. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs. Subscribers: To receive these weekly digests via email, click here to sign up for our mailing list.

A subscriber, citing the weekly record of S&P 500 earnings growth estimates in the “FactSet Earnings Insight” historical series, wondered whether estimate trends/revisions are exploitable. To investigate, we collect S&P 500 quarterly year-over-year earnings growth estimates as recorded in this series. These data are bottom-up (firm by firm) aggregates, whether purely from analyst estimates (before any actual earnings releases),… Keep Reading

How should investors think about the interactions between working years (retirement account contributions) and retirement years (retirement account withdrawals)? In his June 2020 paper entitled “Retirement Planning: From Z to A”, Javier Estrada integrates working and retirement periods to estimate how much an individual should save and how they should invest to achieve a desired… Keep Reading

Are government bond returns exploitably predictable? In their June 2020 paper entitled “Predicting Bond Returns: 70 Years of International Evidence”, Guido Baltussen, Martin Martens and Olaf Penninga examine predictability of international 10-year government bond returns with emphasis on two subsamples, January 1950 through September 1981 (mostly rising interest rates) and October 1981 through May 2019… Keep Reading