, practitioners and researchers. However, little attention has been paid to the predictability of their risk measures. In this paper …, we compare the predictability of the one-step-ahead volatility and Value-at-Risk of Bitcoin using several volatility … models. We also include procedures that take into account the presence of outliers and estimate the volatility and Value-at-Risk …

Credit risk is a critical issue that affects banks and companies on a global scale. Possessing the ability to … accurately predict the level of credit risk has the potential to help the lender and borrower. This is achieved by alleviating … trees, random forests, and stochastic gradient boosting to add to the current literature on credit-risk modelling. The …

Recent literature has focuses on realized volatility models to predict financial risk. This paper studies the benefit … of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized …

We analyse four stochastic claims reserving methods in terms of their capability to estimate reserve risk and how … claim triangles support our results. The appropriateness of the Solvency II risk margin on a one-year horizon and of the … IFRS 17 risk adjustment in the long run largely vary by the chosen risk model. Despite the fact that IFRS 17 does not …