Investing Research Articles

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

Can machine learning (ML) algorithms improve stock picking? In the May 2020 version of their paper entitled “Stock Picking with Machine Learning”, Dominik Wolff and Fabian Echterling apply ML to insights from financial research to assess stock picking abilities of different ML algorithms at a weekly horizon. Their potential return predictor inputs include equity factors… Keep Reading

The Trading Calendar presents cumulative return visualizations for the S&P 500 Index across the calendar year and across each calendar month. Three alternative perspectives on U.S. stock market performance by calendar month are: (1) percentage of positive returns; (2) ratio of average return to standard deviation of returns; and, (3) distribution of returns. Using monthly… Keep Reading

Below is a weekly summary of our research findings for 7/6/20 through 7/10/20. 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.

Most stock data sources present Total Return (TR), 100% reinvestment of dividends with no participation in firm rights issuances and share issuances/repurchases, as representative of investment performance. An alternative perspective is Total Return for All Shareholders (TRAS), the return for an investor who maintains a constant fraction of issued shares (see the table below). Can… Keep Reading

Do interest rate effects explain/predict the poor performance of value stocks over the past decade, and especially during 2017 through early 2020? In their May 2020 paper entitled “Value and Interest Rates: Are Rates to Blame for Value’s Torments?”, Thomas Maloney and Tobias Moskowitz investigate interactions between equity value factors and the interest rate environment…. Keep Reading