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Measuring Price Risk on UK Arable Farms

Authors


  • We are grateful to Philip Cain, Jeremy Franks, David Harvey and three anonymous referees for helpful comments on a previous draft.

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 RiskMetricsTM 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 RiskMetricsTM model underestimates expected losses. UK arable farms face substantial price risk.

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