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Investing Research Articles

3516 Research Articles

Equity Factor Performance Following Positive and Negative Market Returns

Do stock return anomalies perform differently after positive and negative monthly market returns? In their July 2023 paper entitled “The Market State, Mispricing and Asset Pricing Anomalies”, Michael Di Carlo and Ilias Tsiakas examine the role of the overall market state in estimating returns for stock return anomalies, specifying the market state as positive (negative)… Keep Reading

Robustness and Exploitability of Intraday Stock Return Prediction

Are intraday stock market exchange-traded funds (ETF), stock sector ETFs and individual stock returns exploitably predictable at short horizons? In their June 2023 paper entitled “Intraday Stock Predictability Everywhere”, Fred Liu and Lars Stentoft study intraday U.S. equity return predictability using machine learning methods. Specifically, they: Consider the market portfolio represented by SPDR S&P 500… Keep Reading

Weekly Summary of Research Findings: 7/17/23 – 7/21/23

Below is a weekly summary of our research findings for 7/17/23 through 7/21/23. 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.

Machine Learning Guided to Avoid Overfitting

What modeling techniques help avoid biases/overfitting in use of machine learning to predict stock returns? In his July 2023 paper entitled “Less is More? Reducing Biases and Overfitting in Machine Learning Return Predictions”, Clint Howard explores how modeling choices affect machine learning as applied to predicting next-month stock returns, as follows: He considers 11 machine… Keep Reading

Predicted Firm Default Spikes and Future Asset Returns

Does an expectation of an unusually large number of firm defaults in the coming year usefully predict stock and bond market returns? In their May 2023 paper entitled “Systematic Default and Return Predictability in the Stock and Bond Markets”, Jack Bao, Kewei Hou and Shaojun Zhang apply an iterative process to estimate the probability that… Keep Reading

Are iShares Core Allocation ETFs Attractive?

The four iShares Core Asset Allocation exchange-traded funds (ETF) offer exposures to U.S. stocks, global stocks and bonds semiannually rebalanced to fixed weights, as follows. iShares Core Conservative Allocation (AOK) – 30% stocks and 70% bonds (30-70). iShares Core Moderate Allocation (AOM) – 40% stocks and 60% bonds (40-60). iShares Core Growth Allocation (AOR) –… Keep Reading

SACEMS Portfolio-Asset Addition Testing

Does adding an exchange-traded fund (ETF) or note (ETN) to the Simple Asset Class ETF Momentum Strategy (SACEMS) boost performance via consideration of more trending/diversifying options? To investigate, we add the following 25 ETF/ETN asset class proxies one at a time to the base set and measure effects on the Top 1, equally weighted (EW)… Keep Reading

SACEMS Portfolio-Asset Exclusion Testing

Are all of the potentially trending/diversifying asset class proxies used in the Simple Asset Class ETF Momentum Strategy (SACEMS) necessary? Might one or more of them actually be harmful to performance? To investigate, we each month rank the nine SACEMS assets based on past return with one excluded (nine separate test series) and reform the… Keep Reading

Weekly Summary of Research Findings: 7/10/23 – 7/14/23

Below is a weekly summary of our research findings for 7/10/23 through 7/14/23. 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.

GPT-4 as Financial Advisor

Can state-of-the-art artificial intelligence (AI) applications such as GPT-4, trained on the text of billions of web documents, provide sound financial advice? In their June 2023 paper entitled “Using GPT-4 for Financial Advice”, Christian Fieberg, Lars Hornuf and David Streich test the ability of GPT-4 to provide suitable portfolio allocations for four investor profiles: 30… Keep Reading