We measure the economic risk of epidemics at a geo-spatially detailed resolution. In addition to data about the …’s resilience (its ability of the recover rapidly from the shock). We find that the economic risk of epidemics is particularly high …

the period 1972:1-2014:12 to forecasts our tail risk indicators with each model in pseudo-real time. Our key finding is …

We examine how the tail risk of currency returns over the past 20 years were impacted by central bank (monetary and … effects last for up to 1 month, and are proportionally higher for joint QE actions. This cross-border source of tail risk is …

We measure the economic risk of COVID-19 at a geo-spatially detailed resolution. In addition to data about the current … prevalence of confirmed cases, we use data from 2014-2018 and a conceptual disaster risk model to compute measures for exposure ….e., its ability of the recover rapidly from the shock). We find that the economic risk of this pandemic is particularly high …

We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high … EV models, especially in the developed markets. -- value at risk ; expected shortfall ; hybrid historical simulation … ; extreme value theory ; bootstrapping …

In accordance with Basel Capital Accords, the Capital Requirements (CR) for market risk exposure of banks is a … nonlinear function of Value-at-Risk (VaR). Importantly, the CR is calculated based on a bank’s actual portfolio, i.e. the …

In this study, we compare the out-of-sample forecasting performance of several modern Value-at- Risk (VaR) estimators … derived from extreme value theory (EVT). Specifically, in a multi-asset study covering 30 years of stock, bond, commodity and …