A Jump-Diffusion Model with Stochastic Volatility and Durations

Wei Wei and Denis Pelletier

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: 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.

Keywords: Durations; Stochastic Volatility; Price jumps; High-frequency data; Bayesian inference (search for similar items in EconPapers)
JEL-codes: C1 C5 G1 (search for similar items in EconPapers)
Pages: 44
Date: 2015-08-06
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-mst and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2015-34

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