Please use this identifier to cite or link to this item:
Müller, Gernot J.
Czado, Claudia
Year of Publication: 
Series/Report no.: 
Discussion Paper 504
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
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
318.64 kB

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.