Long Memory in Volatility and Trading Volume

Posted: 15 Nov 2010

See all articles by Jeff Fleming

Jeff Fleming

Rice University - Jesse H. Jones Graduate School of Business

Chris Kirby

UNC Charlotte - Belk College of Business

Multiple version iconThere are 2 versions of this paper

Date Written: November 1, 2010

Abstract

We use fractionally-integrated time-series models to investigate the joint dynamics of equity trading volume and volatility. Bollerslev and Jubinski (1999) show that volume and volatility have a similar degree of fractional integration, and they argue that this evidence supports a long-run view of the mixture-of-distributions hypothesis. We examine this issue using more precise volatility estimates obtained using high-frequency returns (i.e., realized volatilities). Our results indicate that volume and volatility both display long memory, but we can reject the hypothesis that the two series share a common order of fractional integration for a fifth of the firms in our sample. Moreover, we find a strong correlation between the innovations to volume and volatility, which suggests that trading volume can be used to obtain more precise estimates of daily volatility for cases in which high-frequency returns are unavailable.

Keywords: Realized volatility, Fractional integration, Strongly autocorrelated, Bivariate mixture model, Long-range dependence

JEL Classification: C32, C58, G12

Suggested Citation

Fleming, Jeff and Kirby, Chris, Long Memory in Volatility and Trading Volume (November 1, 2010). Journal of Banking and Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=1709044

Jeff Fleming

Rice University - Jesse H. Jones Graduate School of Business ( email )

6100 South Main Street
P.O. Box 1892
Houston, TX 77005-1892
United States
713-348-4677 (Phone)
713-348-5251 (Fax)

HOME PAGE: http://www.ruf.rice.edu/~jfleming

Chris Kirby (Contact Author)

UNC Charlotte - Belk College of Business ( email )

9201 University City Boulevard
Charlotte, NC 28223
United States

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