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Asymmetric multivariate normal mixture GARCH
Haas, Markus (contributor); Mittnik, Stefan (contributor);  … - 2008
Persistent link: https://www.econbiz.de/10003651581
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Multivariate regimeswitching GARCH with an application to international stock markets
Haas, Markus (contributor); Mittnik, Stefan (contributor) - 2008
Persistent link: https://www.econbiz.de/10003651587
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A study of value-at-risk on portfolio in stock return using DCC multivariate GARCH
Lee, Mingchih; Chiou, Jer-shiou; Lin, Cho-min - In: Applied financial economics letters 2 (2006) 3, pp. 183-188
Persistent link: https://www.econbiz.de/10003326276
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Multivariate normal mixture GARCH
Haas, Markus (contributor); Mittnik, Stefan (contributor);  … - 2006
Persistent link: https://www.econbiz.de/10003351679
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A component GARCH model with time varying weights
Bauwens, Luc (contributor); Storti, G. (contributor) - 2007
Persistent link: https://www.econbiz.de/10003462056
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A component GARCH model with time varying weights
Bauwens, Luc (contributor); Storti, G. (contributor) - 2007
Persistent link: https://www.econbiz.de/10003432749
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Estimating dynamic copula dependence using intraday data
Grossmass, Lidan; Poon, Ser-Huang - In: Studies in nonlinear dynamics and econometrics : SNDE ; … 19 (2015) 4, pp. 501-529
Persistent link: https://www.econbiz.de/10011339412
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Construction and backtesting of a multi-factor stress-scenario for the stock market
Boldyrev, Kirill; Andrianov, Dmitry; Ivliev, Sergey - In: Financial econometrics and empirical market microstructure, (pp. 37-45). 2015
Persistent link: https://www.econbiz.de/10011326724
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Value-at-Risk analysis in the presence of asymmetry and long memory : the case of Turkish Stock Market
Balibey, Mesut; Turkyilmaz, Serpil - In: International journal of economics and financial issues … 4 (2014) 4, pp. 836-848
Persistent link: https://www.econbiz.de/10010528502
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GARCH models, tail indexes and error distributions : an empirical investigation
Šopov, Boril; Horváth, Roman - 2015
We perform a large simulation study to examine the extent to which various generalized autoregressive conditional heteroskedasticity (GARCH) models capture extreme events in stock market returns. We estimate Hill's tail indexes for individual S&P 500 stock market returns ranging from 1995-2014...
Persistent link: https://www.econbiz.de/10010529886