Academic Finance Research and Insights

Using Machine Learning Programs to Forecast the Equity Risk Premium

By |May 10th, 2024|Research Insights, Factor Investing, Larry Swedroe, Guest Posts, AI and Machine Learning, Other Insights, Macroeconomics Research|

To date, the best metric we have for forecasting future equity returns and the ERP is current valuations. An interesting question is whether more complicated methods using newly developed machine learning models can provide superior forecasts.

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Can Machine Learning Improve Factor Returns? Not Really

By |April 29th, 2024|Research Insights, Factor Investing, Basilico and Johnsen, Academic Research Insight, AI and Machine Learning|

Can AI models improve on the failures in predicting returns strictly from a practical point of view?  In this paper, the possibilities are tested with a battery of AI models including linear regression, dimensional reduction methods, regression trees and neural networks.  These machine learning models may be better equipped to address the multidimensional nature of stock returns when compared to traditional sorting and cross-sectional regressions used in factor research. The authors hope to overcome the drawbacks and confirm the results of traditional quant methods. As it turns out, those hopes are only weakly fulfilled by the MLM framework.

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Social Media, Analyst Behavior and Market Efficiency

By |April 26th, 2024|Larry Swedroe, Research Insights, Guest Posts, Other Insights, Behavioral Finance|

Hibbert, Kang, Kumar and Mishra provided us with yet another explanation: social media is providing analysts with information that reduces their forecasting errors. The result has been an increase in market efficiency, leading to a reduction in the PEAD anomaly. The bottom line is that the ability to generate alpha continues to be under assault—trying to outperform the market by stock selection is becoming even more of a loser’s game.  

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