Markov Processes and the Distribution of Volatility: A Comparison of Discrete and Continuous Specifications

Working Paper 99/001

Posted: 26 Feb 1999

See all articles by Stephen J. Taylor

Stephen J. Taylor

Lancaster University - Department of Accounting and Finance

Date Written: January 1999

Abstract

Two mixtures of Normal distributions, created by persistent changes in volatility, are compared as models for asset returns. A Markov chain with two states for volatility is contrasted with an autoregressive Gaussian process for the logarithm of volatility. The conditional variances of asset returns are shown to have a bimodal distribution for the former process when volatility is persistent, that contrasts with a unimodal distribution for the latter process. A test procedure based upon this contrast shows that a lognormal distribution for Sterling/Dollar volatility is far more credible than only two volatility states.

JEL Classification: C22, C52, F31, G15

Suggested Citation

Taylor, Stephen J., Markov Processes and the Distribution of Volatility: A Comparison of Discrete and Continuous Specifications (January 1999). Working Paper 99/001, Available at SSRN: https://ssrn.com/abstract=148989

Stephen J. Taylor (Contact Author)

Lancaster University - Department of Accounting and Finance ( email )

The Management School
Lancaster LA1 4YX
United Kingdom
+ 44 15 24 59 36 24 (Phone)
+ 44 15 24 84 73 21 (Fax)

HOME PAGE: http://www.lancs.ac.uk/staff/afasjt

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
1,134
PlumX Metrics