2 papers
q-fin.RM2025
An Integrated Approach to Importance Sampling and Machine Learning for Efficient Monte Carlo Estimation of Distortion Risk Measures in Black Box Models
Sören Bettels, Stefan Weber
Distortion risk measures play a critical role in quantifying risks associated with uncertain outcomes. Accurately estimating these risk measures in the context of computationally e…
q-fin.RM2024
Multinomial Backtesting of Distortion Risk Measures
Sören Bettels, Sojung Kim, Stefan Weber
We extend the scope of risk measures for which backtesting models are available by proposing a multinomial backtesting method for general distortion risk measures. The method relie…