In a new study, Prof. Olivier Scaillet develops and implements methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for prospect investors.
Scaillet and his co-authors formulate a new testing procedure for prospect spanning for two nested portfolio sets based on sub-sampling and Linear Programming. In an application, they use the prospect spanning framework to evaluate whether well-known anomalies are spanned by standard factors.
They find that of the strategies considered, a few of them expand the opportunity set of the prospect type
investors, 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 paper is co-authored with Stelios Arvanitis and Nikolas Topaloglou and is forthcoming in the prestigious Management Science journal.
Feb 4, 2023