Informative Covariates, False Discoveries and Mutual Fund Performance

Event details

This event will discuss the implementation of a new multiple-hypotheses testing method on mutual funds performance.

Abstract

We develop a novel multiple hypothesis testing method named the multivariate functional False Discovery Rate (mfFDR). The method incorporates multiple informative covariates (and new information they carry) in estimating the False Discovery Rate (FDR) of predictive models' ``conditional" performance.

Our simulations show that the new method controls well under various settings of dependencies and estimation errors that are typical in financial data. We see that the more covariates that we use, the higher power we gain. Aiming to use the new method to picking out-performing mutual funds, we introduce a procedure, namely, the multivariate functional False Discovery Rate ``plus" (mfFDR+).

In our simulation based on mutual fund returns, the mfFDR+ controls well the FDR and gains considerable power over prior methods that do not account for extra information. Its advantage remains under different alpha distributions, balanced and unbalanced data structure, and cross-sectional dependent and independent error terms. In further empirical analyses, we construct portfolios based on several covariates and show that they enhance the performance of mutual fund portfolios, highlighting the value of extra information in the multiple hypothesis testing framework.

Biography

Professor Georgios Sermpinis joined the Adam Smith Business School in September 2011 where he is currently Professor of Finance. He holds degrees from the National Kapodistrian University of Athens and the Liverpool John Moores University. He previously worked at the University of Bedfordshire and Liverpool John Moores University. Georgios has offered consultancy and provided seminars for major banks such as Goldman Sachs, BNP Paribas, Santander and Societe Generale. He has published more than 50 research papers in peer review journals and acts as editor on some of the most well-respected journals in Finance and Business Analytics.

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