TY  - UNPD
A1  - Haas, Markus
A1  - Mittnik, Stefan
A1  - Paolella, Marc S.
T1  - Modeling and predicting market risk with Laplace-Gaussian mixture distributions
T2  - Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2005,11
N2  - While much of classical statistical analysis is based on Gaussian distributional assumptions, statistical modeling with the Laplace distribution has gained importance in many applied fields. This phenomenon is rooted in the fact that, like the Gaussian, the Laplace distribution has many attractive properties. This paper investigates two methods of combining them and their use in modeling and predicting financial risk. Based on 25 daily stock return series, the empirical results indicate that the new models offer a plausible description of the data. They are also shown to be competitive with, or superior to, use of the hyperbolic distribution, which has gained some popularity in asset-return modeling and, in fact, also nests the Gaussian and Laplace. Klassifikation: C16, C50 . March 2005.
T3  - CFS working paper series - 2005, 11 
KW  - GARCH
KW  - Hyperbolic Distribution
KW  - Kurtosis
KW  - Laplace Distribution
KW  - Mixture Distributions
KW  - Stock Market Returns
KW  - Marktrisiko
KW  - Laplace-Verteilung
KW  - Gauß-Funktion
Y1  - 2005
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/4405
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30-10872
IS  - March 2005
ER  -