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Extreme measures of agricultural financial risk
Author(s)
Date Issued
2008-10-06
Date Available
2009-12-08T12:46:26Z
Abstract
Risk 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.
Sponsorship
University College Dublin. School of Business
Type of Material
Working Paper
Publisher
University College Dublin. School of Business. Centre for Financial Markets
University College Dublin. School of Business
Series
Centre for Financial Markets working paper series
WP-09-02
UCD Business Schools Working Paper Series
WP09/02
Classification
E17
G19
N52
Subject – LCSH
Agriculture--Finance--United States
Risk--Econometric models
Extreme value theory
Language
English
Status of Item
Not peer reviewed
This item is made available under a Creative Commons License
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