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A new bivariate Archimedean copula with application to the evaluation of VaR

Topcu Guloksuz Cigdem and Kumar Pranesh ()
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Kumar Pranesh: Department of Mathematics and Statistics, University of Northern British Columbia, 3333 University Way, Prince George, BC V2N 4Z9, Canada

Studies in Nonlinear Dynamics & Econometrics, 2022, vol. 26, issue 2, 273-285

Abstract: In this paper, a new generator function is proposed and based on this function a new Archimedean copula is introduced. The new Archimedean copula along with three representatives of Archimedean copula family which are Clayton, Gumbel and Frank copulas are considered as models for the dependence structure between the returns of two stocks. These copula models are used to simulate daily log-returns based on Monte Carlo (MC) method for calculating value at risk (VaR) of the financial portfolio which consists of two market indices, Ford and General Motor Company. The results are compared with the traditional MC simulation method with the bivariate normal assumption as a model of the returns. Based on the backtesting results, describing the dependence structure between the returns by the proposed Archimedean copula provides more reliable results over the considered models in calculating VaR of the studied portfolio.

Keywords: Archimedean copula; dependence; generator function; Monte Carlo simulation; stock prices; value at risk (search for similar items in EconPapers)
JEL-codes: C02 C15 C18 C40 C46 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1515/snde-2019-0096

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