Unlocking Value: Identifying and Evaluating Investment Anomalies through Prospect Spanning

GSEM Professor Olivier Scaillet has co-authored an article in the top-tier journal Management Science alongside Stelios Arvanitis and Nikolas Topaloglou. The article presents methods to assess whether introducing new securities or relaxing investment constraints improves the investment opportunity set for prospective investors. The authors propose a new testing procedure for prospect spanning, utilizing subsampling and linear programming. Their analysis evaluates the extent to which well-known anomalies are spanned by standard factors. Their findings reveal that certain strategies, such as stock issuance and momentum, offer real value to investors by expanding their investment choices. These results are consistent across multiple tests, suggesting that these strategies could lead to better financial outcomes.

ABSTRACT

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.

The study is available open access: Spanning Analysis of Stock Market Anomalies Under Prospect Stochastic Dominance

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