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Title:Measuring financial risk and portfolio optimization with a non-Gaussian multivariate model PDF Logo
Authors:Kim, Young Shin
Giacometti, Rosella
Rachev, Svetlozar T.
Fabozzi, Frank J.
Mignacca, Domenico
Issue Date:2012
Series/Report no.:Working Paper Series in Economics, Karlsruher Institut für Technologie (KIT) 44
Abstract:In this paper, we propose a multivariate market model with returns assumed to follow a multivariate normal tempered stable distribution. This distribution, defined by a mixture of the multivariate normal distribution and the tempered stable subordinator, is consistent with two stylized facts that have been observed for asset distributions: fat-tails and an asymmetric dependence structure. Assuming infinitely divisible distributions, we derive closed-form solutions for two important measures used by portfolio managers in portfolio construction: the marginal VaR and the marginal AVaR. We illustrate the proposed model using stocks comprising the Dow Jones Industrial Average, first statistically validating the model based on goodness-of-fit tests and then demonstrating how the marginal VaR and marginal AVaR can be used for portfolio optimization using the model. Based on the empirical evidence presented in this paper, our framework offers more realistic portfolio risk measures and a more tractable method for portfolio optimization.
Subjects:portfolio risk
portfolio optimization
portfolio budgeting
marginal contribution
fat-tailed distribution
multivariate normal tempered stable distribution
JEL:C58
C61
G11
G32
Persistent Identifier of the first edition:urn:nbn:de:swb:90-293075
Document Type:Working Paper
Appears in Collections:Working Paper Series in Economics, Karlsruher Institut für Technologie (KIT)

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