Extreme measures of agricultural financial risk

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Title: Extreme measures of agricultural financial risk
Authors: Cotter, John
Dowd, Kevin
Morgan, Wyn
Permanent link: http://hdl.handle.net/10197/3465
Date: Feb-2012
Online since: 2012-02-01T11:51:26Z
Abstract: The agricultural marketing environment is inherently risky. Having accurate measures of risk helps farmers policy makers and financial institutions make better informed decisions about how to deal with this risk. 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 returns data. We compare estimated risk measures in terms of size and precision, and find that they are all considerably higher than Normal estimates. The estimated risk measures are also quite imprecise, and become more so as the risks involved become more extreme.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: Wiley
Journal: Journal of Agricultural Economics
Volume: 63
Issue: 1
Start page: 65
End page: 82
Copyright (published version): 2011 The Agricultural Economics Society
Keywords: Agricultural financial riskSpectral risk measuresExpected shortfallValue at riskExtreme value theory
Subject LCSH: Agriculture--Finance--United States
Risk--Econometric models
Extreme value theory
DOI: 10.1111/j.1477-9552.2011.00322.x
Other versions: http://dx.doi.org/10.1111/j.1477-9552.2011.00322.x
Language: en
Status of Item: Peer reviewed
Appears in Collections:FMC² Research Collection
Business Research Collection

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