BFS 2002

Poster Presentation

Extremes of Multivariate Stationary Diffusions in Finance: A Data Analysis

Andreas Kunz

In finance, multivariate stationary diffusions play an important role, e.g. they are used to model the dynamics of a portfolio of financial instruments or the term structure of interest rates. For an investigation of several risk factors, the dependence structure is of high importance. From the point of view of risk management it is important to know about the large fluctuations of these models. Based on theoretical results derived in Kunz (2002) we suggest methods to asses the goodness-of-fit of a multivariate stationary diffusion model comparing the theoretical asymptotic behavior of its maximum with the empirical maximum of a dataset. These test are applied for a bivariate Vasicek model and a bivariate diffusion model with stationary gamma distribution first to simluated data. Portfolios of interest rate swaps are also analysed.