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Spanning Analysis of Stock Market Anomalies Under Prospect Stochastic Dominance

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We develop and implement methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for prospect investors. We formulate a new testing procedure for prospect spanning for two nested portfolio sets based on subsampling and linear programming. In an application, we use the prospect spanning framework to evaluate whether well-known anomalies are spanned by standard factors. We find that of the strategies considered, a few of them expand the opportunity set of the prospect type investors and thus have real economic value for them and involve absence of loss aversion. Those are the net stock issue anomaly under the FF-5 model, the momentum and net stock issue anomalies under the M-4 model, and the momentum anomaly under the q model. In-sample and out-of-sample results prove remarkably consistent in identifying genuine anomalies for prospect investors. This paper was accepted by Will Cong, finance. Supplemental Material: The data and online appendix are available at https://doi.org/10.1287/mnsc.2023.4953 .
Institute for Operations Research and the Management Sciences (INFORMS)
Title: Spanning Analysis of Stock Market Anomalies Under Prospect Stochastic Dominance
Description:
We develop and implement methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for prospect investors.
We formulate a new testing procedure for prospect spanning for two nested portfolio sets based on subsampling and linear programming.
In an application, we use the prospect spanning framework to evaluate whether well-known anomalies are spanned by standard factors.
We find that of the strategies considered, a few of them expand the opportunity set of the prospect type investors and thus have real economic value for them and involve absence of loss aversion.
Those are the net stock issue anomaly under the FF-5 model, the momentum and net stock issue anomalies under the M-4 model, and the momentum anomaly under the q model.
In-sample and out-of-sample results prove remarkably consistent in identifying genuine anomalies for prospect investors.
This paper was accepted by Will Cong, finance.
Supplemental Material: The data and online appendix are available at https://doi.
org/10.
1287/mnsc.
2023.
4953 .

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