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Market risk and the cattle feeding margin: An application of Value‐at‐Risk
Author(s) -
Manfredo Mark R.,
Leuthold Raymond M.
Publication year - 2001
Publication title -
agribusiness
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.57
H-Index - 43
eISSN - 1520-6297
pISSN - 0742-4477
DOI - 10.1002/agr.1020
Subject(s) - margin (machine learning) , value at risk , portfolio , econometrics , economics , estimation , confidence interval , nonparametric statistics , commodity , value (mathematics) , market risk , statistics , financial economics , risk management , mathematics , computer science , finance , management , machine learning
Value‐at‐Risk, known as VaR, gives a prediction with a certain level of confidence of potential portfolio losses that may be encountered over a specified time period due to adverse price movements in the portfolio's assets. For example, a VaR of 1 million dollars at the 95% level of confidence implies that overall portfolio losses should not exceed 1 million dollars more than 5% of the time over a given holding period. This research examines the effectiveness of VaR measures, developed using alternative estimation techniques, in predicting large losses in the cattle‐feeding margin. Results show that several estimation techniques, both parametric and nonparametric, provide well‐calibrated estimates of VaR such that violations (losses exceeding the VaR estimate) are commensurate with the desired level of confidence. In particular, estimates developed using the RiskMetrics TM method appear robust for instruments that have linear payoff structures such as cash commodity prices. © 2001 John Wiley & Sons, Inc.