“ In this paper, we propose an efficient important sampling method for distortion risk measures in such models that reduces the computational cost through machine learning. We demonstrate the applicability and efficiency of the Monte Carlo method in numerical experiments on various distortion risk measures and models.”
An Integrated App”
“As analysts are primary recipients of these reports, we investigate whether and how analyst forecast properties have changed following...
This study proposes a new method for detecting insider trading. The method combines principal component analysis (PCA) with random forest...
Cyber risk classifications often fail in out-of-sample forecasting despite their in-sample fit. Dynamic, impact-based classifiers...
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