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...

Statistical analysis provides a risk assessment of nuclear safety based on historical data. We use classical probabilistic models from risk theory to analyze data on nuclear power accidents from 1952 to 2011. Findings are that the severities of nuclear power accidents should be modeled with an...

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...