Department of Economics and Business Economics

A Jump-Diffusion Model with Stochastic Volatility and Durations

Research output: Working paperResearch

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  • rp15_34

    Accepted manuscript, 1.06 MB, PDF document

  • Wei Wei
  • Denis Pelletier, North Carolina State University, United States
Market microstructure theories suggest that the durations between transactions carry information about volatility. This paper puts forward a model featuring stochastic volatility, stochastic conditional duration, and jumps to analyze high frequency returns and durations. Durations affect price jumps in two ways: as exogenous sampling intervals, and through the interaction with volatility. We adopt a bivariate Ornstein-Ulenbeck process to model intraday volatility and conditional duration. We develop a MCMC algorithm for the inference on irregularly spaced multivariate processes with jumps. The algorithm provides smoothed estimates of the latent variables such as spot volatility, conditional duration, jump times, and jump sizes. We apply this model to IBM data and find that volatility and conditional duration are interdependent. We also find that jumps play an important role in return variation, but joint modeling of volatility and conditional duration reduces significantly the need for jumps.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages44
Publication statusPublished - 10 Aug 2015
SeriesCREATES Research Papers
Number2015-34

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