Understanding and measuring model risk is important to financial practitioners. However, there lacks a non …-parametric approach to model risk quantification in a dynamic setting and with path-dependent losses. We propose a complete theory … treatment for measuring both the worst-case risk and the f-divergence budget that originate from the model uncertainty of an …

probability of occurrence. The corresponding risk measure, called Loss VaR (LVaR), determines the minimal capital injection that …We introduce a class of quantile-based risk measures that generalize Value at Risk (VaR) and, likewise Expected … regardless of the size of potential losses. We allow for a range of confidence levels that depend on the loss magnitude. The key …

We show that the value of risk reduction changes rapidly when loss is high, due to interactions between skewness of … probability of loss (p) <<< and K(x¯) <(>), risk seeking (risk averse), imprudent (prudent), and intemperate (temperate) agents … wealth () and kurtosis risk aversion (K(x¯)), increasing ambiguity in model predictions. However, when the initial …