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Estimating risk-neutral density with parametric models in interest rate markets

机译:使用利率市场中的参数模型估算风险中性密度

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The departure in modelling terms from the log-normal distribution for option pricing has been largely driven by empirical observations on skewness. In recent years, the Weibull and generalized beta distributions have been used to fit the risk-neutral density from option prices. In this article, we also propose the use of the generalized gamma distribution for recovering the risk-neutral density. In terms of complexity, this distribution, having three parameters, falls between the Weibull and generalized beta distributions. New option pricing formulas for European call and put options are derived under the generalized gamma distribution. The empirical evidence based on a set of interest rate derivatives data indicates that this distribution is capable of producing the same type of performance as the Weibull, generalized beta, and Burr3 distributions. In addition, we analyze the effect of July 2005 bombings in London on interest rate markets under the best fitting distribution. Our results indicate that there was very little impact on the volatility of these markets.
机译:期权定价的建模术语与对数正态分布的偏离很大程度上是由对偏度的经验性观察驱动的。近年来,使用威布尔分布和广义贝塔分布来拟合期权价格的风险中性密度。在本文中,我们还建议使用广义伽玛分布来恢复风险中性密度。在复杂性方面,具有三个参数的此分布介于Weibull和广义beta分布之间。欧洲看涨期权和看跌期权的新期权定价公式是在广义伽玛分布下得出的。基于一组利率衍生数据的经验证据表明,这种分布能够产生与Weibull分布,广义beta和Burr3分布相同类型的绩效。此外,我们分析了在最佳拟合分布下2005年7月伦敦爆炸案对利率市场的影响。我们的结果表明,这些市场的波动性影响很小。

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