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A multiplicative model for volume and volatility

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  • Rob Bauer
  • Fred Nieuwland

Abstract

We first present prima facie evidence for the predictions generated by the mixture of distributions hypothesis, using daily German stock returns and their corresponding daily trading volumes and number of trades. These last two variables are used as proxies for the stochastic rate of information arrival when one wishes to explain GARCH effects by adhering to the mixture of distributions hypothesis. We show that there is no need for these proxies when the stochastic rate of information arrival follows an inverted gamma distribution. Daily trading volume and the daily number of trades, however, empirically provide an explanation for the occurrence of conditional heteroskedasticity of the GARCH form. We estimate several specifications where daily trading volume is included in the conditional variance equation additively and multiplicatively. The new multiplicative specification clearly outperforms the additive specification.

Suggested Citation

  • Rob Bauer & Fred Nieuwland, 1995. "A multiplicative model for volume and volatility," Applied Mathematical Finance, Taylor & Francis Journals, vol. 2(3), pages 135-154.
    • Handle: RePEc:taf:apmtfi:v:2:y:1995:i:3:p:135-154
    DOI: 10.1080/13504869500000008
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    1. Singh, Manohar & Nejadmalayeri, Ali & Lucey, Brian, 2013. "Do U.S. macroeconomic surprises influence equity returns? An exploratory analysis of developed economies," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(4), pages 476-485.
    2. Senarathne, Chamil W & Jayasinghe, Prabhath, 2017. "Information Flow Interpretation of Heteroskedasticity for Capital Asset Pricing: An Expectation-based View of Risk," MPRA Paper 78771, University Library of Munich, Germany, revised 04 Apr 2017.

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