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Related Experiment Videos

Risk-adjusted expected return for selection decisions.

L Pruzzo1, R J C Cantet, C C Fioretti

  • 1Departamento de Producción Animal, Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires, Argentina. lpruzzo@agro.uba.ar

Journal of Animal Science
|December 18, 2003
PubMed
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This study introduces financial risk management tools, value at risk (VaR) and conditional value at risk (CVaR), to animal breeding. These methods provide a risk-adjusted expected return (RAER) for selecting breeding stock, improving decision-making beyond just expected outcomes.

Area of Science:

  • Animal Breeding and Genetics
  • Quantitative Genetics
  • Risk Management in Agriculture

Background:

  • Genetic evaluation provides breeding values but involves uncertainty regarding future economic returns.
  • This uncertainty translates to risk, which is often overlooked when focusing solely on expected returns.
  • Traditional methods do not adequately account for the potential financial losses associated with prediction uncertainty.

Purpose of the Study:

  • To introduce and apply financial risk assessment methodologies, Value at Risk (VaR) and Expected Shortfall (CVaR), to animal breeding decisions.
  • To develop a risk-adjusted expected return (RAER) metric that accounts for the uncertainty in breeding value predictions.
  • To evaluate the impact of risk adjustment on the selection of breeding animals.

Main Methods:

Related Experiment Videos

  • Applied Value at Risk (VaR) and Conditional Value at Risk (CVaR) methodologies, commonly used in finance, to animal breeding.
  • Calculated predicted aggregate genotype (muR), VaR, and CVaR for a dataset of Polled Hereford bull progeny.
  • Derived a Risk-Adjusted Expected Return (RAER) by subtracting CVaR from muR.

Main Results:

  • High correlations (0.89-0.90) were found between predicted aggregate genotype (muR) and risk-adjusted expected return (RAER), indicating a strong overall relationship.
  • Despite high correlations, some bulls showed different rankings when assessed by muR versus RAER, highlighting the impact of risk adjustment.
  • A low and nonsignificant correlation was observed between muR and VaR (0.124), while VaR and RAER showed a significant negative correlation (-0.31), suggesting VaR is a distinct risk measure.

Conclusions:

  • Incorporating risk assessment, specifically through metrics like RAER, is crucial for animal breeding decisions.
  • Adjusting expected returns for the cost of uncertainty can help mitigate potential financial losses from selecting suboptimal animals.
  • The study demonstrates the utility of financial risk management tools in enhancing the accuracy and reliability of genetic selection in livestock.