Publication: Estrategias de cobertura de carteras e índices de renta variable: el mercado español
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2017-01-11
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Universidad Complutense de Madrid
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Abstract
En línea con la creciente importancia de la cobertura de riesgos, la eficacia de las diferentes estrategias y las posibilidades de mejorar a través de diferentes modelos estocásticos han sido analizados en un gran número de estudios académicos en diferentes campos, activos financieros, energía, petróleo, etc. La controversia en la literatura sobre estrategias de cobertura se concentra en torno a tres aspectos principals. En primer lugar, una cuestión clave es la elección de la medida de eficacia que va a determinar la función de optimizar. Entre las diferentes medidas propuestas, la reducción de la varianza es el enfoque más simple y común. Muchos autores consideran que otros criterios, como diferentes especificaciones de funciones de utilidad, el riesgo de pérdidas o la variación de la rentabilidad ,se deben tomar en cuenta con el fin de medir la efectividad de cobertura. Estos criterios derivan en diferentes medidas de efectividad de cobertura como el equivalente cierto (CE), Valor en Riesgo (VaR), Valor en Riesgo Condicional (CVaR) o Pérdida Esperada (ES), Momentos parciales inferiores (LPM), semi-varianza, etc. . Un examen de las principales aportaciones de la literatura muestra la falta de uniformidad o resultados concluyentes en favor de una u otra estrategia. En segundo lugar, otro tema importante es la evolución temporal de la relación de cobertura. Hay una controversia en la literatura en cuanto a si la cobertura dinámica, utilizando relaciones que incorporan la nueva información que llega al mercado, es superior a relaciones estáticas, como la cobertura unitaria o la de mínimos cuadrados. En tercer lugar, cuando se trata de estimar los ratios de cobertura, se emplean muchas técnicas diferentes, que van desde los modelos más simples a enfoques dinámicos muy complejos. Sin embargo, no está claro que estos modelos complejos mejoren la eficacia global y en nuestra opinión, no resuelven favorablemente el compromiso entre complejidad y efectividad...
In line with the growing importance of hedging, the effectiveness of different hedging strategies and the possibilities of improving them through different stochastic models have been analysed in a large number of academic studies across different fields, like the analysis of risks in financial assets, and risk analysis in energy, oil and markets for other commodities. The controversy in the literature regarding hedging strategies concentrates around three main aspects that we introduce in the following paragraphs.1 In first place, a key issue related to the hedging effectiveness is the election of the effectiveness measure that will determine the function to optimize and the optimum hedge ratio. Among the different proposed measures, the variance reduction is the simplest and most common approach. Many authors consider that other criteria, like different utility specifications or the downside risk, with its focus on one tail of the return distribution, should be taken into consideration in order to measure hedging effectiveness. Those criteria derive in different hedging effectiveness measures like the Certainty Equivalent (CE), Value at Risk (VaR), Conditional Value at Risk (CVaR) or Expected Shortfall (ES), Lower Partial Moments (LPM), semi-variance, etc.. An examination of the main contributions in the literature shows the lack of uniformity or conclusive results in favour of one or other strategy. In second place, another important issue is the time evolution of the hedge ratio. There is a controversy in the literature as to whether dynamic hedging, using ratios that incorporate the new information that arrives to the market, is superior to static ratios, like the unitary ratio or those that are estimated with the available data and then applied unchanged to out-of-sample simulations...
In line with the growing importance of hedging, the effectiveness of different hedging strategies and the possibilities of improving them through different stochastic models have been analysed in a large number of academic studies across different fields, like the analysis of risks in financial assets, and risk analysis in energy, oil and markets for other commodities. The controversy in the literature regarding hedging strategies concentrates around three main aspects that we introduce in the following paragraphs.1 In first place, a key issue related to the hedging effectiveness is the election of the effectiveness measure that will determine the function to optimize and the optimum hedge ratio. Among the different proposed measures, the variance reduction is the simplest and most common approach. Many authors consider that other criteria, like different utility specifications or the downside risk, with its focus on one tail of the return distribution, should be taken into consideration in order to measure hedging effectiveness. Those criteria derive in different hedging effectiveness measures like the Certainty Equivalent (CE), Value at Risk (VaR), Conditional Value at Risk (CVaR) or Expected Shortfall (ES), Lower Partial Moments (LPM), semi-variance, etc.. An examination of the main contributions in the literature shows the lack of uniformity or conclusive results in favour of one or other strategy. In second place, another important issue is the time evolution of the hedge ratio. There is a controversy in the literature as to whether dynamic hedging, using ratios that incorporate the new information that arrives to the market, is superior to static ratios, like the unitary ratio or those that are estimated with the available data and then applied unchanged to out-of-sample simulations...
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Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Departamento de Fundamentos del Análisis Económico II (Economía Cuantitativa), leída el 30-10-2015