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Assessment Of Market Risk In Hog Production Using Value-At-Risk And Extreme Value Theory

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  • Odening, Martin
  • Hinrichs, Jan

Abstract

The objective of this paper is to investigate the performance of different VaR models in the context of risk assessment in hog production. Potential pitfalls of traditional VaR models are pinpointed and proposals to solve them are analyzed. After a brief description these methods are used to calculate the VaR of the hog finishing margin under German market conditions. In particular we apply Extreme Value Theory (EVT) to our data and compare the results with historical simulation (HS) and the variance-covariance method (VCM). Hill's estimator is used to determine the tail index of the extreme distribution of the gross margin in hog finishing and farrow production. A bootstrap method proposed by Danielsson et al. (1999) is adopted to choose the optimal sample fraction for the tail estimator. It turns out that EVT, VCM, and HS lead to different VaR forecasts if the return distributions are fat tailed and the forecast horizon is long.

Suggested Citation

  • Odening, Martin & Hinrichs, Jan, 2002. "Assessment Of Market Risk In Hog Production Using Value-At-Risk And Extreme Value Theory," 2002 Annual meeting, July 28-31, Long Beach, CA 19907, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea02:19907
    DOI: 10.22004/ag.econ.19907
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    References listed on IDEAS

    as
    1. Drost, Feike C & Nijman, Theo E, 1993. "Temporal Aggregation of GARCH Processes," Econometrica, Econometric Society, vol. 61(4), pages 909-927, July.
    2. Francis X. Diebold & Til Schuermann & John D. Stroughair, 1998. "Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management," Center for Financial Institutions Working Papers 98-10, Wharton School Center for Financial Institutions, University of Pennsylvania.
    3. Jon Danielsson & Casper G. de Vries, 1998. "Beyond the Sample: Extreme Quantile and Probability Estimation," FMG Discussion Papers dp298, Financial Markets Group.
    4. Peter F. Christoffersen & Francis X. Diebold, 2000. "How Relevant is Volatility Forecasting for Financial Risk Management?," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 12-22, February.
    5. Jon Danielsson & Casper G. De Vries, 2000. "Value-at-Risk and Extreme Returns," Annals of Economics and Statistics, GENES, issue 60, pages 239-270.
    6. Mark R. Manfredo. & Raymond M. Leuthold, 1999. "Market Risk Measurement and the Cattle Feeding Margin: An Application of Value-at-Risk," Finance 9908002, University Library of Munich, Germany.
    7. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    8. repec:adr:anecst:y:2000:i:60:p:10 is not listed on IDEAS
    9. Manfredo, Mark R. & Leuthold, Raymond M., 1999. "Measuring Market Risk Of The Cattle Feeding Margin: An Application Of Value-At-Risk Analysis," 1999 Annual meeting, August 8-11, Nashville, TN 21628, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Francis X. Diebold & Andrew Hickman & Atsushi Inoue & Til Schuermann, 1997. "Converting 1-Day Volatility to h-Day Volatitlity: Scaling by Root-h is Worse Than You Think," Center for Financial Institutions Working Papers 97-34, Wharton School Center for Financial Institutions, University of Pennsylvania.
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