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Econometric Analysis of Realised Volatility and Its Use in Estimating Stochastic Volatility Models

Author

Listed:
  • Neil Shephard
  • Ole E. Barndorff-Nielsen
  • University of Aarhus
Abstract
The availability of intra-day data on the prices of speculative assets means that we can use quadratic variation like measures of activity in financial markets, called realised volatility, to study the stochastic properties of returns. Here we derive the moments and the asymptotic distribution of the realised volatility error - the difference between realised volatility and the actual volatility. These properties can be used to allow us to estimate the parameters of stochastic volatility models.

Suggested Citation

  • Neil Shephard & Ole E. Barndorff-Nielsen & University of Aarhus, 2001. "Econometric Analysis of Realised Volatility and Its Use in Estimating Stochastic Volatility Models," Economics Series Working Papers 71, University of Oxford, Department of Economics.
    • Handle: RePEc:oxf:wpaper:71
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    econometrics; higher order variation; Kalman filter; leverage; lévy process; OU process; quarticity; quadratic variation; realised volatility; square root process; stochastic volatility; subordination; superposition.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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