At present, there is an explosion of practical interest in the pricing of interest rate (IR) derivatives. Textbook pricing methods do not take into account the leptokurticity of the underlying IR process. In this paper, such a leptokurtic behaviour is illustrated using LIBOR data, and a possible

Most structural models for credit pricing assume Geometric Brownian motion to describe the firm asset value. However, the underlying lognor-mal distribution does not match empirical distributions, typically skewed and leptokurtic. Moreover, defaults are usually driven by shocks, which

market and show that a minimal set of behavioural assumptions suffices to generate a leptokurtic distribution of short-term log-returns. This result supports the conjecture that the emergence of some statistical properties of financial time series is due to the microstructure of stock markets.

(1) The behaviour, microdistribution and dispersal of the meadow brown butterfly Maniolajurtina was investigated using mark-release-recapture techniques. (2) The main study site was a meadow at Hightown near Liverpool where a grid of 7-5 m squares was established. (3) Butterflies showed

are an augmentation of the GARCH class of models, but allow for conditionally normal inverse Gaussian and variance gamma distributed errors. As in previous studies, this new approach permits a distinction between conditional heteroskedasticity and a conditionally leptokurtic distribution, but, compared with the well

multi-allele model is simulated and it is concluded that the two-allele model gives a good approximation of its behaviour. It is argued that the total number of loci capable of influencing most quantitative traits is large, and that the distribution of mutant effects is highly leptokurtic

short-term horizon and 99 % confidence level, by properly applying a scaling on the short-term Profit-and-Loss (P&L) distribution. Besides the standard square-root-of-time scaling, based on normality assumptions, we consider two leptokurtic probability density function classes for fitting empirical

An approach based on Extreme Value Theory as a measure to quantify market risk of equity securities and portfolios