Equity trading volume and volatility: Latent information arrivals and common long-run dependencies
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1999-01-01
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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.
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Bollerslev, T, and D Jubinski (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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Tim Bollerslev
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 announcement effects, and the pricing of volatility risk. Recent reviews of his work are available in the two Handbook chapters "Volatility and Correlation Forecasting” (with Torben G. Andersen, Peter Christoffersen and Francis X. Diebold), Handbook of Economic Forecasting, (eds. Graham Elliott, Clive W.J. Granger and Allan Timmermann), 2006, and "Parametric and Nonparametric Volatility Measurement” (with Torben G. Andersen and Francis X. Diebold), in Handbook of Financial Econometrics, (eds. Yacine Aït-Sahalia and Lars P. Hansen), 2009.
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