Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/259846 
Authors: 
Year of Publication: 
2001
Series/Report no.: 
Working Paper No. 2001:6
Publisher: 
Lund University, School of Economics and Management, Department of Economics, Lund
Abstract: 
The continuous-state GARCH model is misspecified if applied to returns calculated from discrete price series. This paper proposes modifications of the above model for handling such cases. The focus is on the AR-GARCH framework, but the same ideas could be used for other stochastic processes as well. Using Swedish stock price data and a stochastic optimization algorithm, simulated annealing, I compare the parameter estimates and asymptotic standard errors from the approximative model and the extended models. I find small deviations between the models for longer time series and small tick sizes, but larger differences for shorter series and for larger tick size to price ratios, mainly in the conditional variance parameter estimates. None of the models provide continuous residuals. By constructing generalized residuals, I show how valid residual diagnostic and specification tests can be performed in some cases.
Subjects: 
EM estimation
compass rose
stock return modeling
latent variables
generalized residuals
JEL: 
C35
C51
C52
Document Type: 
Working Paper

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