Valor en riesgo en el sector petrolero:: un análisis de la eficiencia en la medición del riesgo de la distribución α-estable versus las distribuciones t-Student generalizada asimétrica y normal

• Ramona Serrano Bautista ^[1] ; José Antonio Núñez Mora
  1. [1] Universidad Panamericana

     Universidad Panamericana

     México

     
• Localización: Contaduría y administración, ISSN 0186-1042, ISSN-e 2448-8410, Vol. 65, Nº. 2, 2020
• Idioma: español
• DOI: 10.22201/fca.24488410e.2021.2487
• Títulos paralelos:
  • Value at risk in the oil sector:: An analysis of the efficiency in the measurement of the risk of the α-stable distribution versus the generalized asymmetric Student-t and normal distributions
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    En el sector petrolero, el VaR se ha implementado con el objetivo de cuantificar lo mejor posible los movimientos extremos de los precios del petróleo, debido a que estos repercuten la actividad económica y afectan significativamente los movimientos en el mercado accionario (Sadorsky, 1999). Con este propósito, en esta investigación cuantificamos el VaR considerando tres tipos de petróleo (Brent, WTI y MME) y analizamos el desempeño de la estimación del VaR a un día mediante el estadístico de Kupiec considerando modelos GARCH con tres distribuciones alternativas en el proceso de innovación: estable, t-Student generalizada asimétrica y normal en un período de alta volatilidad. Los resultados de la evaluación de desempeño del modelo basado en el estadístico de Kupiec señalan que el modelo VaR-estable es un modelo más robusto y preciso para ambos niveles de confianza que los basados en las distribuciónes t-Student generalizada asimétrica y normal. Este resultado es crucial en el sector financiero, debido a que impacta directamente en la previsión de reservas necesarias para afrontar potenciales pérdidas.

  • English

    In the oil sector, value at risk (VaR) can be used to quantify as best as possible the maximum oil price changes, because these have an impact on economic activity and finds evidence of its importance in explaining movements in the stock returns (Sadorsky, 1999). With this purpose, in this paper we quantify the VaR of three types of oil (Brent, WTI and MME) and analyze the performance of the one-day VaR estimation by Kupiec test considering GARCH models with three alternative distributions in the innovation process: stable, Student-t generalized and normal in a period of high volatility. The results of the performance evaluation of the model based on the Kupiec statistic indicate that the VaR-stable model is a more robust and accurate model for both confidence levels than those based on the generalized asymmetric and normalized Student t-distributions. This result is crucial in the financial sector, because it directly impacts the provision of reserves necessary to face potential losses.

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