Lillestøl, Jostein () (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration)
Abstract
The univariate Normal Inverse Gaussian (NIG) distribution is found useful for modelling financial return data exhibiting skewness and fat tails. Multivariate versions exists, but may be impractical to implement in finance. This work explores some possibilities with links to the mixing representation of the NIG distribution by the IG-distribution. We present two approaches for constructing bivariate NIG distribution that take advantage of the correlation between the univariate latent IG-variables that characterizes the marginal NIG-distribution. These are readily available from the marginal estimation, either by maximum likelihood via the EM-algorithm or by Bayesian estimation via Markov chain Monte Carlo methods. A context for implementation in finance is given.
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Publisher Info
Paper provided by Department of Finance and Management Science, Norwegian School of Economics and Business Administration in its series Discussion Papers with number
2007/1.
Length: 29 pages Date of creation: 08 Jan 2007 Date of revision: Handle: RePEc:hhs:nhhfms:2007_001
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Find related papers by JEL classification: C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Econometric and Statistical Methods; Specific Distributions
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