Equity trading volume and volatility: Latent information arrivals and common long-run dependencies
Abstract
This article examines the behavior of equity trading volume and volatility for the
individual firms composing the Standard and Poor's 100 composite index. Using multivariate
spectral methods, we find that fractionally integrated processes best describe the
long-run temporal dependencies in both series. Consistent with a stylized mixture-of-distributions
hypothesis model in which the aggregate “news”-arrival process possesses long-memory
characteristics, the long-run hyperbolic decay rates appear to be common across each
volume-volatility pair. © 1999 Taylor & Francis Group, LLC.
Type
Journal articlePermalink
https://hdl.handle.net/10161/1879Published Version (Please cite this version)
10.1080/07350015.1999.10524793Publication Info
Bollerslev, T; & Jubinski, D (1999). Equity trading volume and volatility: Latent information arrivals and common long-run
dependencies. Journal of Business and Economic Statistics, 17(1). pp. 9-21. 10.1080/07350015.1999.10524793. Retrieved from https://hdl.handle.net/10161/1879.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Tim Bollerslev
Juanita and Clifton Kreps Distinguished Professor of Economics, in Trinity College
of Arts and Sciences
Professor Bollerslev conducts research in the areas of time-series econometrics, financial
econometrics, and empirical asset pricing finance. He is particularly well known
for his developments of econometric models and procedures for analyzing and forecasting
financial market volatility. Much of Bollerslev’s recent research has focused on
the analysis of newly available high-frequency intraday, or tick-by-tick, financial
data and so-called realized volatility measures, macroeconomic news annou

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