Author: Garland Durham
Publisher:
ISBN:
Category :
Languages : en
Pages : 61
Book Description
Understanding both the dynamics of volatility as well as the shape of the distribution of returns conditional on the volatility state are important for many financial applications. A simple single-factor SV model appears to be sufficient to capture most of the dynamics; it is the shape of the conditional distribution that is the problem. This paper examines the idea of modeling this distribution as a discrete mixture of normals. The flexibility of this class of distributions provides a transparent look into the tails of the returns distribution. Model diagnostics suggest that the model, SV-mix, does a good job of capturing the salient features of the data. In a direct comparison against several affine-jump models, SV-mix is strongly preferred by Akaike and Schwarz information criteria.