In this article we examine the properties of estimates of realized volatility at various intra-daily sampling frequencies for Brent Crude oil futures traded at the IntercontinentalExchange (ICE). The estimates of realized volatility are subsequently modeled and forecasted to predict day-ahead...

In this paper we propose a simple one-factor quantile regression model based on realized volatility to forecast Value-at-Risk (VaR). The model only uses daily realized volatility as input and thus simplifies estimation substantially compared with most other methodologies currently used to...