Zastosowanie miar zależności zmiennych losowych oraz kopuli Claytona i Gumbel-Hougaarda do szacowania wartości zagrożonej
Application of Random Variables Dependence Measures and Clayton and Gumbel-Hougaard Copulas for Estimating Value at Risk
Author(s): Andrzej StryjekSubject(s): Economy, Financial Markets
Published by: Główny Urząd Statystyczny
Keywords: risk management; Value at Risk; copula; Monte Carlo simulations
Summary/Abstract: This paper shows the opportunities of copula for estimating Value at Risk (VaR). The author presents results of empirical research carried out for portfolios of stocks from Warsaw Stock Exchange. Efficiency of classical covariance method was compared with other well known in the literature and also new methods proposed by author using Clayton and Gumbel-Hougaard copulas.
Journal: Przegląd Statystyczny. Statistical Review
- Issue Year: 56/2009
- Issue No: 3-4
- Page Range: 67-80
- Page Count: 14
- Language: Polish