A Score Test for Discreteness in GARCH Models
AbstractThe standard continuous-state GARCH model is misspecified if applied to returns calculated from discrete price series. We propose a modi?cation of the above model for handling such cases, by modeling the dependent variable as an unobservable stochastic variable with certain observed outcomes. We further construct a score test that can be used to check if the proposed model differ significantly from the one we would have if all variables were observed, i.e. an underlying latent GARCH model. Using price data from some Australian stocks with high tick size to price ratios, we find the important result that in no case does the proposed model differ significantly from an unobservable continuous-state GARCH model.
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Bibliographic InfoPaper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 76.
Date of creation: 01 Mar 2002
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GARCH; latent variables; generalized residuals; score test;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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