Multivariate geometric stable distributions in financial applications

We describe a class of multivariate geometric stable laws that can be used in modeling multivariate financial portfolios of securities. These heavy tailed distributions are stable with respect to geometric summation and accommodate the possibility of market crashes. We look at bivariate currency exchange rates data and show that its main features, peakedness and heavy tails, are very well captured by the geometric stable model.