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Stochastic Volatility Models for Ordinal Valued Time Series with Application to Finance

Claudia CzadoGernot Müller

出版	Techn. Univ., Sonderforschungsbereich Statistische Analyse Diskreter Strukturen, 2006
URL	http://books.google.com.hk/books?id=EYwhyAEACAAJ&hl=&source=gbs_api

註釋

In this paper we introduce two stochastic volatility models where the response variable takes on only finite many ordered values. Corresponding time series occur in high-frequency finance when the stocks are traded on a coarse grid. For parameter estimation we develop an efficient Grouped Move Multigrid Monte Carlo (GM-MGMC) sampler. We apply both models to price changes of the IBM stock in January, 2001 at the NYSE. Dependencies of the price change process on covariates are quantified and compared with theoretical considerations on such processes. we also investigate whether this data set requires modeling with a heavy-tailed Student-t distribution. -- Grouped move ; High-frequency finance ; Markov chain Monte Carlo ; Multigrid Monte Carlo ; Price process