Estimating and evaluating Value-at-Risk forecasts based on realized variance: empirical evidence from ICE Brent Crude oil futures

This paper is the first to use the concept of realized volatility to forecast Value-at-Risk (VaR) for ICE Brent Crude oil futures. We examine sensitivities in the VaR forecasts across intra-daily sampling frequency used to calculate realized volatility. We evaluate the VaR forecasts using Christoffersen's test for conditional coverage on quantiles of particular interest. Additionally, we examine a percentile–percentile plot of the VaR forecasts for all percentiles. The main empirical results show that very good VaR forecasts can be obtained using Gaussian critical values in combination with volatility forecasts based on realized volatility. An examination of the sampling frequency suggests that the most accurate VaR forecasts are obtained with a sampling frequency of between 1 and 10 min. This has important implications for practitioners operating in the financial oil sector.