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....

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...

We engage in a scholarly discussion with artificial intelligence chatbot ChatGPT on concepts in quantitative risk management important for actuarial practice and analyze the interaction. We investigate the extent to which ChatGPT can grasp concepts from the realm of risk, risk measures, time...

In this paper, we propose a novel framework for estimating systemic risk measures and risk allocations based on Markov Chain Monte Carlo (MCMC) methods. We consider a class of allocations whose jth component can be written as some risk measure of the jth conditional marginal loss distribution...

Extreme Value Theory (EVT) has develop ed very rapidly over the past two decades both methodologically and with respect to applications. Whereas (non–life) actuaries have, at least implicitly, used EVT techniques for a long time, mainly through the emergence of quantitative Risk Management, EVT...