This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) Expected Shortfall (ES) uncertainty intervals in high frequency data. A Bayesian bootstrapping backtest density forecasts, which are based on a weighted threshold quantile continuously ranked probability score, developed. Developed backtesting procedures revealed that an estimated...