Asymmetries in Conditional Mean and Variance: Modelling Stock Returns by asMA-asQGARCH
AbstractThe asymmetric moving average model (asMA) is extended to allow forasymmetric quadratic conditional heteroskedasticity (asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We introduce a framework fortesting asymmetries in theconditional mean and the conditional variance, separately or jointly.Some of the new model's moment properties are also derived. Empiricalresults are given for the daily returns of the compositeindex of the New York Stock Exchange. There is strong evidence ofasymmetry in both the conditional mean and conditional variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk forecasting.
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Bibliographic InfoPaper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 00-049/4.
Date of creation: 09 Jun 2000
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Other versions of this item:
- Jan G. De Gooijer & Kurt Brännäs, 2004. "Asymmetries in conditional mean and variance: modelling stock returns by asMA-asQGARCH," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(3), pages 155-171.
- Brännäs, Kurt & de Gooijer, Jan G., 2000. "ASYMMETRIES IN CONDITIONAL MEAN AND VARIANCE: MODELLING STOCK RETURNS BY asMA-asQGARCH," UmeÃ¥ Economic Studies 535, Umeå University, Department of Economics.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
This paper has been announced in the following NEP Reports:
- NEP-ALL-2000-07-27 (All new papers)
- NEP-ECM-2000-07-27 (Econometrics)
- NEP-ETS-2000-07-27 (Econometric Time Series)
- NEP-FIN-2000-07-27 (Finance)
- NEP-FMK-2000-07-27 (Financial Markets)
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