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Multipower Variation and Stochastic Volatility

Author

Listed:
  • Neil Shephard
  • Ole E. Barndorff-Nielsen
  • Department of Mathematical Sciences
  • University of Aarhus

Abstract

In this brief note we review some of our recent results on the use of high frequency financial data to estimate objects like integrated variance in stochastic volatility models. Interesting issues include multipower variation, jumps and market microstructure effects.

Suggested Citation

  • Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    • Handle: RePEc:oxf:wpaper:2004-fe-22
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    Cited by:

    1. Basel Awartani & Valentina Corradi, 2004. "Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average," Econometric Society 2004 North American Summer Meetings 487, Econometric Society.
    2. Inekwe John Nkwoma, 2014. "Business Cycle Variability and Growth Linkage," Monash Economics Working Papers 38-14, Monash University, Department of Economics.
    3. Chaboud, Alain P. & Chiquoine, Benjamin & Hjalmarsson, Erik & Loretan, Mico, 2010. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 212-240, March.

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