Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach

We propose a copula-based periodic mixed frequency generalized autoregressive (GAS) framework in order to model and forecast the intraday exposure conditional value at risk (ECoVaR) for an asset return corresponding market return. In particular, we analyze GAS models that account long-memory-type of dependencies, periodicities, asymmetric nonlinear dependence structures, fat-tailed distributions, jump processes returns. apply our ECoVaR forecasting performance large data set returns S&P500 index.