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handle: 10016/191 , 10016/5042
In this paper, unobserved component models with GARCH disturbances are extended to allow for asymmetric responses of conditional variances to positive and negative shocks. The asymmetric conditional variance is represented by a member of the QARCH class of models. The proposed model allows to distinguish whether the possibly asymmetric conditional heteroscedasticity affects the short run or the long-run disturbances or both. We analyse the statistical properties of the new model and derive the asymptotic and finite sample properties of a QML estimator of the parameters. We propose to identify the conditional heteroscedasticity using the correlogram of the squared auxiliary residuals. Its finite sample properties are also analysed. Finally, we ilustrate the results fitting the model to represent the dynamic evolution of daily series of financial returns and gold prices, as well as of monthly series of inflation. The behaviour of volatility in both types of series is different. The conditional heteroscedasticity mainly affects the short run component in financial returns while in the inflation series, the heteroscedastic ity appears in the long-run component. We find asymmetric effects in both types of variables.
GARCH, leverage effect, structural time series models, auxiliary residuals, EstadÃstica, Inflation, Economic time series analysis, Time series, auto-correlation, regression, etc. in statistics (GARCH), Financial series, financial series, Structural time series models, inflation, Leverage effect, QARCH, Applications of statistics to economics, Auxiliary residuals
GARCH, leverage effect, structural time series models, auxiliary residuals, EstadÃstica, Inflation, Economic time series analysis, Time series, auto-correlation, regression, etc. in statistics (GARCH), Financial series, financial series, Structural time series models, inflation, Leverage effect, QARCH, Applications of statistics to economics, Auxiliary residuals
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