Autor/Autorin: Davedeen Neelesh
I have recently graduated in BSc Business Statistics with Economics and I am currently mastering in MSc Applied Statistics with specialisation in Actuarial Science. I have worked as a Research Analyst on a freelance basis for a market research company.
This book investigates the volatility in the foreign exchange rate (forex) market using USD/MUR and EUR/MUR return series for the past ten years from October 2004 to October 2014. Both USD and EUR series exhibit volatility clustering and fat-tailed behaviours as shown by the results of the preliminary analysis. Furthermore, the presence of ARCH effects (conditional heteroscedasticity) in the residuals of both series validates the application of GARCH-type models for modelling the volatility of USD and EUR return series. Hence, the modelling proceeded with the use of the symmetric GARCH (1, 1) and asymmetric EGARCH (1, 1) models under two different innovations distribution (normal and Student-t). The factual results showed that the symmetric GARCH (1, 1) models are more appropriate to model the volatility of USD and EUR return series in the Mauritian Forex market. Moreover, GARCH (1, 1) with normal innovations and GARCH (1, 1) with Student-t innovations were deduced to be the best fitted model for USD and EUR return series respectively based on model selection criteria and model diagnostics results.
Über den Autor
I have recently graduated in BSc Business Statistics with Economics and I am currently mastering in MSc Applied Statistics with specialisation in Actuarial Science. I have worked as a Research Analyst on a freelance basis for a market research company.
Klappentext
This book investigates the volatility in the foreign exchange rate (forex) market using USD/MUR and EUR/MUR return series for the past ten years from October 2004 to October 2014. Both USD and EUR series exhibit volatility clustering and fat-tailed behaviours as shown by the results of the preliminary analysis. Furthermore, the presence of ARCH effects (conditional heteroscedasticity) in the residuals of both series validates the application of GARCH-type models for modelling the volatility of USD and EUR return series. Hence, the modelling proceeded with the use of the symmetric GARCH (1, 1) and asymmetric EGARCH (1, 1) models under two different innovations distribution (normal and Student-t). The factual results showed that the symmetric GARCH (1, 1) models are more appropriate to model the volatility of USD and EUR return series in the Mauritian Forex market. Moreover, GARCH (1, 1) with normal innovations and GARCH (1, 1) with Student-t innovations were deduced to be the best fitted model for USD and EUR return series respectively based on model selection criteria and model diagnostics results.
