Analyzing and Modeling Multivariate Association
Julius Schnieders
Broschiertes Buch

Analyzing and Modeling Multivariate Association

Statistical Measures and Pair-Copula Constructions

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Many applications in quantitative finance, such as the estimation of the Value-at-Risk of a portfolio, require the modeling of dependencies of a large number of random variables. The most popular approach is Pearson¿s correlation coefficient, which is based on the covariance, i. e. the mixed second moments of the corresponding random variables. However, the correlation coefficient only captures linear dependencies and solely in case of a few distributions, such as the multivariate normal distribution, completely determines the dependence structure. Empirical data, unfortunately, is often non-...