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| Larsen, Ryan A.; Leatham, David J.; Vedenov, Dmitry V.. |
| The issue of modeling farm financial decisions in a dynamic framework is addressed in this paper. Discrete stochastic programming is used to model the farm portfolio over the planning period. One of the main issues of discrete stochastic programming is representing the uncertainty of the data. The development of financial scenario generation routines provides a method to model the stochastic nature of the model. In this paper, two approaches are presented for generating scenarios for a farm portfolio problem. The approaches are based on copulas and optimization. The copula method provides an alternative to the multivariate normal assumption. The optimization method generates a number of discrete outcomes which satisfy specified statistical properties by... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Agribusiness; Agricultural Finance; Farm Management. |
| Ano: 2010 |
URL: http://purl.umn.edu/61509 |
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| Larsen, Ryan A.; Vedenov, Dmitry V.; Leatham, David J.. |
| As agriculture becomes more industrialized, the role of risk measures such as value-at-risk (VaR) will become more utilized. In this case it was applied to geographical diversification and also modifying the traditional VaR estimation by incorporating a copula dependence parameter into the VaR estimation. In addition, an alternative risk measure was also calculated, CVaR. The CVaR, unlike VaR, is a coherent risk measure. Thus it does not suffer from many of the shortcomings of the VaR. The land portfolio consisted of Dryland wheat production acres in Texas, Colorado, and Montana. Three series of net returns were calculated for each region. Based on the VaR and the CVaR, the portfolio was optimized based on minimizing the expected loss based on... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Copula; CVaR; Risk-Management; Geographical Diversification; Agribusiness; Farm Management; Risk and Uncertainty. |
| Ano: 2009 |
URL: http://purl.umn.edu/46763 |
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| Larsen, Ryan A.; Mjelde, James W.; Klinefelter, Danny A.; Wolfley, Jared L.. |
| Yield correlations between 380 different counties are calculated for non-irrigated wheat. Using this data, a function is estimated that shows the relationship between correlation and changes in geographic and climate data. In addition movement variables are included added to the specification to capture the impact of moving from one production region to another. A negative relationship was found between changes in latitude, longitude, precipitation, elevation, and temperature. Correlations and longitude and precipitation showed downward sloping concave relationship, whereas correlations and latitude showed downward sloping convex relationships. Changes in latitude and longitude are found to have greatest impact on correlation with elasticities of -1.54... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Yield Correlations; Geographical Diversification; Farm Management; Agribusiness; Crop Production/Industries; Farm Management; Risk and Uncertainty. |
| Ano: 2009 |
URL: http://purl.umn.edu/46819 |
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