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3542 Research Articles

Weekly Summary of Research Findings: 2/26/24 – 3/1/24

Below is a weekly summary of our research findings for 2/26/24 through 3/1/24. 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.

Test of Some Motley Fool Public Stock Picks

A reader asked: “I am wondering how come you have not rated Motley Fool guys. Any insight?” To augment the test of Motley Fool public stock picks in “‘Buy These Stocks for 2019’ Forward Test”, we look at three more lists of stock picks: “10 Top Stocks That Will Make You Richer in 2021” published… Keep Reading

Substitute QQQ for SPY in SACEVS and SACEMS?

Subscribers asked whether substituting Invesco QQQ Trust (QQQ) for SPDR S&P 500 (SPY) in the Simple Asset Class ETF Value Strategy (SACEVS) and the Simple Asset Class ETF Momentum Strategy (SACEMS) improves outcomes. To investigate, we substitute monthly QQQ dividend-adjusted returns for SPY dividend-adjusted returns in the two model strategies. We then compare the modified… Keep Reading

20 Great Stock Ideas for 2023?

In late 2022, Forbes “tapped Morningstar to identify top-performing fund managers who have either beat their benchmarks this year or on a longer-term basis over three-year, five-year or ten-year periods. Here are their best stock ideas for the coming year…” as published at the beginning of January 2023 in “20 Great Stock Ideas for 2023… Keep Reading

ChatGPT Prediction of News-related Stock Market Returns

Is ChatGPT useful for predicting stock market returns based on financial news headlines? In the December 2023 version of their paper entitled “ChatGPT, Stock Market Predictability and Links to the Macroeconomy”, Jian Chen, Guohao Tang, Guofu Zhou and Wu Zhu investigate whether ChatGPT 3.5 can predict U.S. stock market (S&P 500 Index) returns based on… Keep Reading

Equity Factor Timing from Deep Neural Networks

Can enhanced machine learning models accurately time popular equity factors? In their January 2024 paper entitled “Multi-Factor Timing with Deep Learning”, Paul Cotturo, Fred Liu and Robert Proner explore equity factor timing via a multi-task neural network model (MT) to capture the commonalities across factors and a dynamic multi-task neural network model (DMT) to extract… Keep Reading

Weekly Summary of Research Findings: 2/20/24 – 2/23/24

Below is a weekly summary of our research findings for 2/20/24 through 2/23/24. 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.

Exploitable Commodity Futures Factor Momentum?

Do published commodity futures factors exhibit exploitable momentum? In their December 2023 paper entitled “Factor Momentum in Commodity Futures Markets”, Yiyan Qian, Xiaoquan Liu and Ying Jiang examine factor momentum in fully collateralized nearest-rolled contracts of various commodity futures. They consider ten factors: Market –S&P Goldman Sachs Commodity Index.  Basis -slope of futures term structure…. Keep Reading

ChatGPT Interpretation of Firm Earnings Calls

Can ChatGPT find red flags in firm earnings calls? In their January 2024 paper entitled “Unusual Financial Communication – Evidence from ChatGPT, Earnings Calls, and the Stock Market”, Lars Beckmann, Heiner Beckmeyer, Ilias Filippou, Stefan Menze and Guofu Zhou test the ability of ChatGPT-4 Turbo to identify and analyze unusual content and tone aspects of… Keep Reading

Profitable Machine Learning Stock Picking Strategies?

Can machine learning models pick stocks that unequivocally generate alpha out-of-sample? In their November 2023 paper entitled “The Expected Returns on Machine-Learning Strategies”, Vitor Azevedo, Christopher Hoegner and Mihail Velikov assess expected net returns and alphas of machine learning-based anomaly trading strategies. They use nine machine learning models to predict next-month stock returns based on… Keep Reading