It is a well-known fact that most of the asset returns tend to be skewed and heavytailed. Heavy tailed distributions such as the Student’s t distribution and Stable distribution are commonly used in finance to model asset returns that areheavy tailed. Additionally, Stable distribution allows...

This paper studies the asymptotic normality for the kernel deconvolution estimator when the noise distribution is logarithmic chi-square; both identical and independently distributed observations and strong mixing observations are considered. The dependent case of the result is applied to obtain...

This paper employs methodologies that were developed for heavy right-tailed distributions to construct the point and interval estimates of the expected operational losses in the US. These are consistent and unbiased estimates of the mean of the heavy right-tailed loss distribution, whereas those...

This paper proposes some improvements to advanced measurement approach (AMA) to modelling operational losses and applies this approach to US business losses. The AMA involves, among others, modelling a loss severity distribution and estimating its Expected Loss and the 99.9% operational...

Traditional regression models might not be appropriate when the probability of extreme events is higher than that implied by the normal distribution. Extending the method for estimating the parameters of a double Pareto lognormal distribution (DPLN) in Reed and Jorgensen (2004), we develop an EM...

The Azzalini skew-t distributions are popular because of their theoretical foundation and the availability of computational methods in the R package sn. One difficulty with this skew-t family is that the elements of the expected information matrix do not have closed form analytic formulas. Thus,...

This paper provides a detailed framework for modeling portfolios, achieving the highest growth rate under subjective risk constraints such as Value at Risk (VaR) in the presence of stable laws. Although the maximization of the expected logarithm of wealth induces outperforming any other...

Naive asset allocation and other ad-hoc techniques are commonly practiced by fund managers in the industry. Such strategies, however, are deemed mean-variance (MV) sub-optimal according to modern portfolio theory. Nonetheless, taking estimation risk into considerations, such practices are...