Dynamic Functional Regression with Application to the Cross-Section of Returns

• Activity Number: 135
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Section on Nonparametric Statistics
• Author(s): Bahaeddine Taoufik* and Piotr Kokoszka and Hong Miao and Matthew Reimherr
• Companies: Penn State and Colorado State University and Colorado State University and Penn State
• Keywords: functional data ; cross-section of returns ; functional linear models ; principal component analysis ; Hilbert space ; Weak dependence

Abstract

Over the last four decades, the study of the cross-section of returns has been widely developed in the field of finance and econometrics. In this work, we explore the relationship between market return and some financial factors by fitting functional regression models. We establish two estimation procedures based on the least squares and generalized least squares methods. We also present four hypothesis testing procedures on the functional coefficient regressors based on the space of squared integrable functions approach and the principal component analysis (PCA) approach for both least squares and generalized least squares methods. We establish a new asymptotic results which guarantee convergence and asymptotic normality of our estimates even under weak dependence.