We extend the common Poisson shock framework reviewed for example in Lindskog and McNeil [15] to a formulation avoiding repeated defaults, thus obtaining a model that can account consistently for single name default dynamics, cluster default dynamics and default counting process. This approach...

We study the response to perturbation of non-Poisson dichotomous fluctuations that generate super-diffusion. We adopt the Liouville perspective and with it a quantum-like approach based on splitting the density distribution into a symmetric and an anti-symmetric component. To accomodate the...

This paper uses ML and GMM techniques to estimate systems of stochastic differential equations that describe the behaviour of stock returns. We test restrictions implied by a continuous time asset pricing model that builds on the work of Chamberlain (1988). The stochastic differential equations...

Let d[gamma](k(t), t) be the Bayes estimate of the rate of a Poisson process with Gamma prior and loss function [gamma] - d[gamma], l [less-than-or-equals, slant] [gamma] < [infinity]. Let . It is shown that d[gamma] (k(t), t) is a submartingale for l < [gamma] < 2, a martingale for [gamma] = 2 and a supermartingale for [gamma] > 2 with respect to .