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Trading volume in models of financial derivatives

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  • Sam Howison
  • David Lamper
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    Abstract

    This paper develops a subordinated stochastic process model for an asset price, where the directing process is identified as information. Motivated by recent empirical and theoretical work, the paper makes use of the under-used market statistic of transaction count as a suitable proxy for the information flow. An option pricing formula is derived, and comparisons with stochastic volatility models are drawn. Both the asset price and the number of trades are used in parameter estimation. The underlying process is found to be fast mean reverting, and this is exploited to perform an asymptotic expansion. The implied volatility skew is then used to calibrate the model.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/13504860110074163
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Mathematical Finance.

    Volume (Year): 8 (2001)
    Issue (Month): 2 ()
    Pages: 119-135

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    Handle: RePEc:taf:apmtfi:v:8:y:2001:i:2:p:119-135

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    Related research

    Keywords: Trading Volume; Subordinated Process; Stochastic Volatility; Option Pricing;

    References

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    Cited by:
    1. Leonenko, N.N. & Petherick, S. & Sikorskii, A., 2012. "A normal inverse Gaussian model for a risky asset with dependence," Statistics & Probability Letters, Elsevier, vol. 82(1), pages 109-115.
    2. Emanuel Derman, 2002. "The Perception of Time, Risk and Return During Periods of Speculation," Papers cond-mat/0201345, arXiv.org.

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