Lower Tail Independence of Hitting Times of Two-Dimensional Diffusions
MetadataShow full item record
The coefficient of tail dependence is a quantity that measures how extreme events in one component of a bivariate distribution depend on extreme events in the other component. It is well known that the Gaussian copula has zero tail dependence, a shortcoming for its application in credit risk modeling and quantitative risk management in general. We show that this property is shared by the joint distributions of hitting times of bivariate (uniformly elliptic) diffusion processes.
Cite this version of the work
David Saunders, Lung Kwan Tsui, Satish Iyengar (2018). Lower Tail Independence of Hitting Times of Two-Dimensional Diffusions. UWSpace. http://hdl.handle.net/10012/20089