Master Thesis GARCH – Modelling Theoretical Survey, Model Implementation and Robustness Analysis
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چکیده
In this thesis we survey GARCH modelling with special focus on the fitting of GARCH models to financial return series. The robustness of the estimation of the parameters in the model is examined with three different distributional assumptions for the innovations; Gaussian distribution, Student-t distribution and GED (Generalised Error Distribution). Both the Student-t distribution and the GED have fat tails. The maximum-likelihood approach is used for the parameter estimation. Using backtesting, the related residuals under the three different distributional assumptions are examined. Furthermore, some fundamental concepts of financial time series analysis will be explained and some " stylised facts " of real returns will be examined. 4 Acknowledgements I would like to thank Peter Alaton and Robert Thorén at Algorithmica Research AB for giving me the opportunity of doing this thesis and for their help and contributions with real-world financial knowledge. Finally, I would like to thank my family and girlfriend for their support during the whole project. Especially, I would like to express my deepest gratitude to my mother and sister for their endless love, support and encouragement.
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تاریخ انتشار 2003