Measuring Price Risk on UK Arable Farms

Abstract

Abstract Price risk is estimated for a representative UK arable farm using value‐at‐risk (VaR). To determine the distribution of commodity returns, two multivariate generalised autoregressive conditional heteroscedasticity (GARCH) models, with t ‐distributed and normally distributed errors, and a RiskMetrics TM model are estimated. Returns show excess kurtosis and that the GARCH model with t ‐distributed errors fits best. Estimates of VaR differ between models: both GARCH models perform well but the RiskMetrics TM model underestimates expected losses. UK arable farms face substantial price risk.