to as PD-LGD correlation (here PD refers to probability of default, which is often used synonymously with default rate …This paper seeks to identify computationally efficient importance sampling (IS) algorithms for estimating large …). There is a large literature on modelling stochastic LGD and PD-LGD correlation, but there is a dearth of literature on using …

, including correlation coefficients, error functions, and stepwise regression, are employed to analyze the selected variables … enhance the development of prediction models for stock indices in Jordan and other countries by incorporating relevant …

The aim of this work was to test how returns are distributed across multiple asset classes, markets and sampling …. Finally, we show how sampling and distribution of returns are strictly connected. This is of great importance as, for example …

-form formulae. Additionally, we employ the importance sampling simulations to derive ruin probabilities, which further permit an in …

risks. We discuss the impact of tree topology on the second-order moments and tail statistics of the resulting distribution …

constraints. We assume randomness on the covariance matrix as a way of generalizing. We analyse common barrier derivatives …

measures the increase in kurtosis due to the polynomial expansion, can be estimated so as to make the resulting distribution …, obtained by using Hermite polynomials. This work shows how polynomial expansions of an entire class of spherical laws can be … capable of describing the empirical kurtosis found in the data. An application of the Gram-Charlier-like expansions to a set …

to outliers. To address this issue, we propose a robust alternative that estimates the SUR parameters in a more outlier … the GMCL model and illustrate the importance of taking into account contemporaneous correlations and structural …

computations, we capture this effect using the ratio of standard deviations of pre-term and post-term risks, followed by covariance …