Estimation of the Parameters of Multivariate Stable Distributions

2019/02/26 by Sathe, Aastha M., Upadhye, Neelesh. S.
#60E07 #62F10 #Computation (stat.CO) #FOS: Computer and information sciences

paper · doi:10.48550/arxiv.1902.09796

Abstract

In this paper, we begin our discussion with some of the well-known methods available in the literature for the estimation of the parameters of a univariate/multivariate stable distribution. Based on the available methods, a new hybrid method is proposed for the estimation of the parameters of a univariate stable distribution. The proposed method is further used for the estimation of the parameters of a strictly multivariate stable distribution. The efficiency, accuracy, and simplicity of the new method is shown through Monte-Carlo simulation. Finally, we apply the proposed method to the univariate and bivariate financial data.

Related

• Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models
• Estimation of Parameters of Stable Distributions
• alphastable: An R Package for Modelling Multivariate Stable and Mixture of Symmetric Stable Distributions
• Multivariate Mixed Tempered Stable Distribution
• Estimation of stable distribution parameters from a dependent sample