Stochastic Volatility: Univariate and Multivariate Extensions

Eric Jacquier (), Nicholas G. Polson () and Peter Rossi ()
Additional contact information
Eric Jacquier: Boston College
Nicholas G. Polson: University of Chicago

No 112, Computing in Economics and Finance 1999 from Society for Computational Economics

Abstract: Discrete time stochastic volatility models (hereafter SVOL) are noticeably more difficult to estimate than the successful ARCH family of models. In this paper we demonstrate efficient estimation and prediction for a number of univariate and multivariate SVOL models. Namely, we model fat-tailed and skewed conditional distributions, correlated errors distributions (leverage effect), and two multivariate models, a stochastic factor-structure model and a stochastic discount dynamic model. These extensions to the basic model are needed if one wants, for example, to compare SVOL models with ARCH-style models or to implement option pricing and portfolio selection under stochastic volatility. We specify the models as a hierarchy of conditional probability distributions: Pr(data | volatilities), Pr(volatilities | parameters) and Pr(parameters). This conceptually simple methodology provides a natural environment for the construction of stochastic volatility models that depart from standard distributional assumptions. Given a model and the data, inference and prediction are based on the joint posterior distribution of the volatilities and the parameters that we simulate via Markov chain Monte Carlo (MCMC) methods. Our approach also provides a sensitivity analysis for parameter inference and an outlier diagnostic. We estimate the model for several financial time series and find that the extensions considered are indeed needed. For the SVOL model we find strong evidence of non-normal conditional distributions for stock returns and exchange rates. We also find evidence of correlated errors for stock returns.

Date: 1999-03-01
New Economics Papers: this item is included in nep-ets and nep-fin
References: Add references at CitEc
Citations: View citations in EconPapers (29)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: Stochastic Volatility: Univariate and Multivariate Extensions (1999)
Working Paper: Stochastic Volatility: Univariate and Multivariate Extensions
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf9:112

Access Statistics for this paper

More papers in Computing in Economics and Finance 1999 from Society for Computational Economics CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().