Approximation of Asymmetric Multivariate Return Distributions
We develop a new method to approximate the asymmetric multivariate probability density function (pdf) of financial asset returns by using series expansions; a rate of convergence for the mean absolute error of this approximation is also provided. We then propose the method of maximum likelihood and the generalized method of moments to estimate the parameters of the approximated pdf. A Monte-Carlo experiment corroborates the feasibility of our approach. Copyright Springer Science+Business Media, LLC. 2012
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Volume (Year): 19 (2012)
Issue (Month): 3 (September)
Pages: 293-318
| Handle: | RePEc:kap:apfinm:v:19:y:2012:i:3:p:293-318 |
| DOI: | 10.1007/s10690-011-9150-8 |
| Contact details of provider: | Web page: http://www.springer.com Web page: http://www.jafee.gr.jp/
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| Order Information: | Web: http://www.springer.com/finance/journal/10690/PS2 |
References listed on IDEAS
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- Andrew J. Patton, 2004.
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- Knight, J.L. & Stachell, S.E. & Tran, K.C., 1995. "Statistical Modeling of Asymetric Risk in Asset Returns," Papers 95-3, Saskatchewan - Department of Economics.
- Chu, Ba, 2011. "Recovering copulas from limited information and an application to asset allocation," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1824-1842, July.
- Okimoto, Tatsuyoshi, 2008. "New Evidence of Asymmetric Dependence Structures in International Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(03), pages 787-815, September. Full references (including those not matched with items on IDEAS)
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