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Investing Research Articles

3598 Research Articles

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

SACEMS with Inverse VIX-based Lookback Intervals

One concern about simple momentum strategies is data snooping bias impounded in selection of the lookback interval(s) used to measure asset momentum. To circumvent this concern, we consider the following argument: The CBOE Volatility Index (VIX) broadly indicates the level of financial markets distress and thereby the tendency of investors to act complacently (when VIX… Keep Reading

Weekly Summary of Research Findings: 2/12/24 – 2/16/24

Below is a weekly summary of our research findings for 2/12/24 through 2/16/24. 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.

SACEVS and SACEMS Strategy Momentum?

A subscriber suggested that the Simple Asset Class ETF Value Strategy (SACEVS) and the Simple Asset Class ETF Momentum Strategy (SACEMS) may each exhibit return momentum at the strategy level, such that an investor holding both as in Combined Value-Momentum Strategy (SACEVS-SACEMS) may want to tilt each month toward the one with stronger recent returns…. Keep Reading

Doom and the Stock Market

Is proximity to doom good or bad for the U.S. stock market? To measure proximity to doom, we use the Doomsday Clock “Minutes-to-Midnight” metric, revised intermittently in late January via the Bulletin of the Atomic Scientists, which “warns the public about how close we are to destroying our world with dangerous technologies of our own… Keep Reading

Actual Retail Option Trading/Returns

Given wide bid-ask spreads, do retail option traders systematically bear large losses? In their January 2024 paper entitled “An Anatomy of Retail Option Trading”, Vincent Bogousslavsky and Dmitriy Muravyev characterize retail option trading in the U.S. by exploiting data from a trading journal that attracts retail investors by offering advanced tracking/performance verification tools. When users subscribe… Keep Reading