A simple graphical method to explore tail-dependence in stock-return pairs

摘要: For a bivariate data set the dependence structure cannot only be measured globally, for example with Bravais–Pearson correlation coefficient, but can also analysed locally. In this article exploration of dependencies in tails distribution is discussed. graphical method which called chi-plot and was introduced by Fisher Switzer used. Examples simulated sets illustrate that suitable dependencies. This then used to examine stock-return pairs. The kind tail-dependence between returns has consequences, example, calculation value at risk should modelled carefully. application various daily pairs shows different structures found. graph therefore an interesting aid modelling returns.