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Dokumenttyp:
Bachelorarbeit 
Autor(en):
Trinh, Mailan 
Titel:
Predicting VaR of portfolios based on time series analysis and copulas 
Abstract:
This note is devoted to the application of copulas and linear autoregressive stochastic processes in time series analysis. Common processes like ARMA (autoregressive moving average) and GARCH (generalized autoregressive conditional heteroskedasticity) processes are discussed concerning stationarity and estimation. Especially for ARMA processes asymptotic normality of coefficient estimators of the maximum likelihood method is proved. This note analyses daily data sets of the MSCI index of Europe,...    »
 
Betreuer:
PD Dr. Aleksey Min 
Gutachter:
PD Dr. Aleksey Min 
Jahr:
2011 
Hochschule / Universität:
Technische Universität München 
Format:
Text 
Annahmedatum:
15.06.2011