Multivariate bilateral gamma, copulas, CoSkews and CoKurtosis

Dilip B. Madan and King Wang
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Dilip B. Madan: Robert H. Smith School of Business, University of Maryland, College Park, MD 20742, USA
King Wang: ��Derivative Product Strats, Morgan Stanley, 1585 Broadway, 5th Floor, New York, NY 10036, USA

International Journal of Financial Engineering (IJFE), 2022, vol. 09, issue 02, 1-20

Abstract: Correlation graphs are introduced to delineate the levels observed in data and models for return and squared return correlations. A sample of 2048 representative pairs of equity assets is selected from a possible collection of 381,501 pairs by quantization. Five copulas are estimated and simulated on these pairs of returns, the Gaussian, t-copula, Clayton, Gumbel and Frank. Additionally, the multivariate bilateral gamma (MBG) model that introduces dependence via common time changes is also fit and simulated. Results of fit statistics on returns, CoSkew and CoKurtosis pairs are reported. The general ordering of the models is MBG, t-copula, followed by the Gaussian, Frank, Gumbel and Clayton copulas.

Keywords: Multivariate variance gamma; tail probabilities; bivariate characteristic function estimation (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S2424786321500328

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