As an emerging field of applied research, quantitative risk management (QRM) poses a lot of challenges for probabilistic and statistical modeling. This review provides a discussion on selected past, current, and possible future areas of research at the intersection of statistics and QRM. Topics...

The purpose and novelty of this article is to investigate the extent to which artificial intelligence chatbot ChatGPT can grasp concepts from quantitative risk management. To this end, we enter a scholarly discussion with ChatGPT in the form of questions and answers, and analyze the responses....

The goal of this dissertation is to explore nested Archimedean copulas. In particular, efficient sampling algorithms, especially suited for large dimensions, are presented. As an application, a pricing model for collateralized debt obligations (CDOsʺ) is developed. Copulas are distribution...

After a brief overview of aspects of computational risk management, the implementation of the rearrangement algorithm in R is considered as an example from computational risk management practice. This algorithm is used to compute the largest quantile (worst value-at-risk) of the sum of the...

An asymptotic hypothesis test for value-at-risk subadditivity is introduced and studied. The test is derived based on an equivalent formulation of the value-at-risk subadditivity inequality in terms of the distribution of the underlying risks' sum. Its size is considered mathematically, and its...

This paper presents an intellectual exchange with ChatGPT, an artificial intelligence chatbot, about correlation pitfalls in risk management. The exchange takes place in the form of a conversation that provides ChatGPT with context. The purpose of this conversation is to evaluate ChatGPT's...