Statistical analysis of empirical pairwise copulas for the S&P 500 stocks
Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
It is of great importance to find an analytical copula that will represent the empirical lower tail dependence. In this study, the pairwise empirical copula are estimated using data of the S&P 500 stocks during the period 2007-2010.Different optimization methods and measures of dependence have been used to fit Gaussian, t and Clayton copula to the empirical copulas, in order to represent the empirical lower tail dependence. These different measures of dependence and optimization methods with their restrictions, point at different analytical copulas being optimal. In this study the t copula with 5 degrees of freedom is giving the most fulfilling result, when it comes to representing lower tail dependence. The t copula with 5 degrees of freedom gives the best representation of empirical lower tail dependence, whether one uses the 'Empirical maximum likelihood estimator', or 'Equal Ƭ' as an approach.
Place, publisher, year, edition, pages
2012. , 73 p.
Trita-MAT, ISSN 1401-2286 ; 2012:23
Tail dependence, Tail concentration function, Measure of similarity, Copula, Archimedean, Kendall's tau, Spearman's rho, Gaussian, t copula, Clayton
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:kth:diva-103086OAI: oai:DiVA.org:kth-103086DiVA: diva2:558590
Master of Science in Engineering - Vehicle Engineering
UppsokPhysics, Chemistry, Mathematics
Pavlenko, Tatjana, Universitetslektor