# Estimation of the Parameters of Multivariate Stable Distributions

## TL;DR

This paper introduces a new hybrid method for estimating parameters of univariate and multivariate stable distributions, demonstrating improved efficiency and accuracy through simulations and financial data applications.

## Contribution

A novel hybrid estimation method for stable distributions that enhances accuracy and simplicity over existing techniques.

## Key findings

- The new method outperforms traditional approaches in simulations.
- It provides reliable parameter estimates for financial data.
- The approach is computationally efficient and easy to implement.

## 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.