An improved CAViaR model for oil price risk

Abstract

As a benchmark for measuring market risk, Value-at-Risk (VaR) reduces the risk associated with any kind of asset to just a number (amount in terms of a currency), which can be well understood by regulators, board members, and other interested parties. This paper employs a new kind of VaR approach due to Engle and Manganelli [4] to forecasting oil price risk. In doing so, we provide two original contributions: introducing a new exponentially weighted moving average CAViaR model and developing a least squares regression model for multi-period VaR prediction. © Springer-Verlag Berlin Heidelberg 2007.