Calibrating and Simulating Copula Functions in Financial Applications

Frontiers in Applied Mathematics and Statistics

Claudio Romano¹  Annalisa Di Clemente² 

[1] Rome, Italy;null;

关键词: Copula functions;    dependence structure;    multivariate distribution function;    extreme joint co-movements;    financial applications;    stock market;   

DOI  :  10.3389/fams.2021.642210

来源: Frontiers

【 摘 要 】

Copula functions can be utilized in financial applications to determine the dependence structure of the financial asset returns in the portfolio. Empirical evidence has proved the inadequacy of the multi-normal distribution, traditionally adopted to model the financial asset returns distribution. Copula functions can be employed in a flexible way for building efficient algorithms and to simulate a more adequate distribution of the financial assets. This paper aims to describe some simple statistical procedures currently employed to calibrate the copula functions to the financial market data. Furthermore, we present some useful methods for choosing which copula function better fits the real financial data. Also, some algorithms to simulate random variates from certain types of copula functions are illustrated. Finally, for illustration purposes, the previous procedures described are applied to two Italian equities. In particular, we show how to generate efficient Monte Carlo scenarios of equity log-returns in the bivariate case using different types of copula functions.

【 授权许可】

CC BY