. Time series models with GARCH errors are also considered. Based on formal econometrics tests, this study shows that the …

original empirical time series, but also with the simulated results from the corresponding Brownian Motion and GARCH processes … wavelet scalograms, we demonstrate that the MMAR outperforms both the GBM and GARCH(1,1) in time-frequency comparisons, in … attributes of the empirical distributions, while the simulated GBM and GARCH(1,1) processes cannot preserve the thick-tails, high …

December 1993. Second, using various GARCH models to account for heteroskedasticity show that Gaussian models can be misleading …

security returns for stochastic beta and GARCH effects, may very well cause researchers to draw inappropriate conclusions. …

diagnostic tool to determine the adequacy of the GARCH model in describing the returns generating process of Malaysia’s stock …, while GARCH model is commonly applied to financial time series, this model cannot provide an adequate characterization for … the presence of episodic non- stationarity in the data, which could not be captured by any kind of ARCH or GARCH model …

This paper examines the forecasting performance of GARCH’s models used with agricultural commodities data. We compare … containing a genuine stock index also. The implied goal is to find out if the GARCH models are more fitted for stock indices than …

measuring abnormal returns by OLS, we used ARCH and GARCH models over 70% of the sample. The results show signs of insider … the issue. The results are consistent with the extant empirical literature and show that ARCH/GARCH estimation of abnormal …

financial time series and use it to improve the short-term forecasts from GARCH models. We study different generalizations of … GARCH that allow for several time scales. On our holding sample, none of the considered models can fully exploit the …

properties of adaptive tail index estimators under the class of student-t marginal distribution functions including GARCH and …