MODELING STNOCK MARKET INDEXES WITH COPULA FUNCTIONS (Zastosowanie funkcji kopuli w modelowaniu indeksów gieldowych)

• Authors: Leskow Jacek , Mokrzycka Justyna , Krawiec Kamil
• Languages of publication: EN

Abstracts

EN

Contemporary financial risk management is significantly based on the analysis of time series of returns. One of the most significant errors frequently committed by analysts is the predominant use of normal distributions when it is clear that the returns are not normal. Copula models and models for non-normal multivariate distributions provide new tools to solve the problem because the obtained results are immediately applicable in portfolio management, option pricing and measuring risk without assuming normality. Therefore, both a theoretician and a practitioner are interested in multivariate models for returns and copula functions. The copula function models provide an effective and interesting technique of constructing multivariate distribution starting from marginal ones. Due to Sklar's result established in 1959, we can present any multivariate distribution with a help of corresponding marginal distributions and a selected copula function. In this work we present an application of copula function to construct multivariate conditional distributions of times series. In the last part of this paper dynamic models such as DCC-MVGARCH and conditional copula are analyzed. Moreover, we also present an application of bootstrap in the context of copula function. This work is appended by examples showing practical application of our work.

Discipline

• ECONOMICS: ECONOMICS

• Publisher: Wyższa Szkoła Informatyki i Zarządzania z siedzibą w Rzeszowie
• Journal: Finansowy Kwartalnik Internetowy e-Finanse
• Year: 2011
• Volume: 7
• Issue: 2
• Pages: 1-16
• Document type: ARTICLE

Contributors

author

Leskow Jacek

author

Mokrzycka Justyna

author

Krawiec Kamil

• Dr hab. Jacek Leskow, Wyzsza Szkola Biznesu National-Louis University in Nowy Sacz, ul. Zielona 27, 33-300 Nowy Sacz, Poland

Identifiers

CEJSH db identifier

11PLAAAA09664