Equity trading volume and volatility: Latent information arrivals and common long-run dependencies
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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.
Published Version (Please cite this version)10.1080/07350015.1999.10524793
Publication InfoBollerslev, 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.
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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