Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-Risk

Lee, Sharon X. and McLachlan, Geoffrey J. (2013). Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-Risk. In: J. Piantadosi, R. S. Anderssen and J. Boland, Proceedings of the 20th International Congress on Modelling and Simulation. International Congress on Modelling and Simulation, Adelaide, SA, Australia, (1128-1234). 1/12/2013/6/12/2013.

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Author Lee, Sharon X.
McLachlan, Geoffrey J.
Title of paper Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-Risk
Conference name International Congress on Modelling and Simulation
Conference location Adelaide, SA, Australia
Conference dates 1/12/2013/6/12/2013
Proceedings title Proceedings of the 20th International Congress on Modelling and Simulation
Journal name 20Th International Congress On Modelling and Simulation (Modsim2013)
Place of Publication Melbourne, Australia
Publisher Modelling and Simulation Society of Australia and New Zealand
Publication Year 2013
Year available 2013
Sub-type Fully published paper
Open Access Status File (Publisher version)
ISBN 97809872143131
Editor J. Piantadosi
R. S. Anderssen
J. Boland
Start page 1128
End page 1234
Total pages 7
Language eng
Abstract/Summary Value-at-Risk (VaR) is a widely used statistical measure in financial risk management for quantifying the level of risk associated with a specific investment portfolio. It is well-known that historical return data exhibit non-normal features, such as heavy tails and skewness. Current analytical (parameteric) calculation of VaR typically assumes the distribution of the portfolio return to be a normal or log-normal distribution, which results in underestimation and overestimation of the VaR at high and low confidence levels, respectively, when a normal distribution is assumed.
Keyword Mixture model
Skew distributions
Skew t-mixture model
Generalized hyperbolic distribution
EM algorithm
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Conference Paper
Sub-type: Fully published paper
Collection: School of Mathematics and Physics
 
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Created: Tue, 21 Jun 2016, 00:04:53 EST by Professor Geoff Mclachlan on behalf of Mathematics