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Predictive Inference for Integrated Volatility

  • Norman R. Swanson

    ()

    (Rutgers University)

  • Valentina Corradi

    ()

    (University of Warwick)

  • Walter Distaso

    ()

    (Queen Mary)

In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive den- sities and con¯dence intervals for integrated volatility. In this paper, we propose nonparametric estimators of the aforementioned quantities, based on model free volatility estimators. We establish consistency and asymptotic normality for the feasible estimators and study their ¯nite sample properties through a Monte Carlo experiment. Finally, using data from the New York Stock Exchange, we provide an empirical application to volatility directional predictability.

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Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 201109.

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Length: 20 pages
Date of creation: 15 May 2011
Date of revision:
Handle: RePEc:rut:rutres:201109
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