Empirical Analysis of Affine vs. Non-Affine Variance Specifications in Jump-Diffusion Models for Equity Indices
Seeger, N.J., Rodrigues, P.J.M. & Ignatieva, K. (2015). Empirical Analysis of Affine vs. Nonaffine Variance Specifications in Jump-Diffusion Models for Equity Indices. Journal of Business and Economic Statistics, 33(1), 68-75. 10.1080/07350015.2014.922471
49 Pages Posted: 16 Feb 2009 Last revised: 13 Feb 2015
Date Written: March 25, 2012
How to model the variance process driving stock returns is a major research questions in finance. The specification of a variance model has implications for, e.g., risk management decisions, portfolio allocation or derivative pricing. This paper analyzes several crucial questions for setting up a variance model. (i) Are jumps an important model ingredient even when using a non-affine specification? (ii) How do affine specifications perform when compared to non-affine models. (iii) How should non-linearities be modeled? We find that, first, jump models clearly outperform pure stochastic volatility models. Second, non-affine specifications outperform affine models, even after including jumps. And finally, we find that the polynomial specification of the drift term, that has also been used in short rate models, is the best non-affine model under consideration.
Keywords: Stochastic volatility, Markov Chain Monte Carlo (MCMC), Bayesian inference Deviance information criteria (DIC), Bayes factor
JEL Classification: G11, G12
Suggested Citation: Suggested Citation