Extreme Measures of Agricultural Financial Risk
AbstractRisk is an inherent feature of agricultural production and marketing and accurate measurement of it helps inform more efficient use of resources. This paper examines three tail quantile-based risk measures applied to the estimation of extreme agricultural financial risk for corn and soybean production in the US: Value at Risk (VaR), Expected Shortfall (ES) and Spectral Risk Measures (SRMs). We use Extreme Value Theory (EVT) to model the tail returns and present results for these three different risk measures using agricultural futures market data. We compare the estimated risk measures in terms of their size and precision, and find that they are all considerably higher than normal estimates; they are also quite uncertain, and become more uncertain as the risks involved become more extreme.
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Bibliographic InfoArticle provided by Wiley Blackwell in its journal Journal of Agricultural Economics.
Volume (Year): 63 (2012)
Issue (Month): 1 (02)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0021-857X
Other versions of this item:
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
- G19 - Financial Economics - - General Financial Markets - - - Other
- N52 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - U.S.; Canada: 1913-
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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