Logo
Munich Personal RePEc Archive

Nonparametric Dynamic Conditional Beta

Maheu, John M and Shamsi, Azam (2016): Nonparametric Dynamic Conditional Beta.

Warning
There is a more recent version of this item available.
[thumbnail of MPRA_paper_73764.pdf]
Preview
PDF
MPRA_paper_73764.pdf

Download (3MB) | Preview

Abstract

This paper derives a dynamic conditional beta representation using a Bayesian semiparametric multivariate GARCH model. The conditional joint distribution of excess stock returns and market excess returns are modeled as a countably infinite mixture of normals. This allows for deviations from the elliptic family of distributions. Empirically we find the time-varying beta of a stock nonlinearly depends on the contemporaneous value of excess market returns. In highly volatile markets, beta is almost constant, while in stable markets, the beta coefficient can depend asymmetrically on the market excess return. The model is extended to allow nonlinear dependence in Fama-French factors.

Available Versions of this Item

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.