Testing for Regime Changes in Portfolios with a Large Number of Assets: A Robust Approach to Factor Heteroskedasticity

45 Pages Posted: 6 Nov 2017 Last revised: 14 Oct 2019

Date Written: October 11, 2019

Abstract

We develop a new test for threshold-type regime changes in the risk exposures in portfolios with a large number of financial assets whose returns exhibit an approximate factor structure. Unlike existing procedures to detect discrete shifts in factor models, our test is robust to regime-specific second moment of the common factors. We rely on an auxiliary threshold regression: we take a weighted cross-sectional average of the factor model; we estimate the factors from the original model under the null hypothesis of no regime changes; we construct a Lagrange multiplier statistic to test for threshold effect in the auxiliary regression. Numerical results show the good finite sample properties of our procedure. The empirical analysis uncovers the dynamics of portfolio weights and diversification benefits in factor mimicking portfolios across different regimes.

Keywords: Large Factor Model, Portfolio Choice, Threshold Model, Linearity Testing, Principal Component Analysis

JEL Classification: C12, C38, G11

Suggested Citation

Massacci, Daniele, Testing for Regime Changes in Portfolios with a Large Number of Assets: A Robust Approach to Factor Heteroskedasticity (October 11, 2019). Available at SSRN: https://ssrn.com/abstract=3064615 or http://dx.doi.org/10.2139/ssrn.3064615

Daniele Massacci (Contact Author)

King's College London ( email )

United Kingdom

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
112
Abstract Views
711
rank
264,642
PlumX Metrics