论文标题
灵活的两点选择方法，用于基于特征函数的稳定定律的参数估计
Flexible Two-point Selection Approach for Characteristic Function-based Parameter Estimation of Stable Laws
论文作者
论文摘要
稳定的分布是在各个科学领域很好地描述脂肪尾行为和缩放现象的有吸引力的模型之一。基于矩的方法的方法产生了一个简单的过程，以估算稳定的法律参数，要求将矩点用于特征函数，但是点的选择仅被解释很差，尚未详细说明。我们通过引入选择合理点的技术来提出一种新的基于特征函数的方法，这可以带来可用于实际使用的时刻方法。我们的方法的表现优于其他最先进的方法，这些方法表现出稳定定律的所有四个参数的封闭形式表达。最后，通过使用金融资产的几个数据来说明该方法的适用性。数值结果表明，在建模具有稳定分布的经验数据时，我们的方法是有利的。
Stable distribution is one of the attractive models that well describes fat-tail behaviors and scaling phenomena in various scientific fields. The approach based upon the method of moments yields a simple procedure for estimating stable law parameters with the requirement of using momental points for the characteristic function, but the selection of points is only poorly explained and has not been elaborated. We propose a new characteristic function-based approach by introducing a technique of selecting plausible points, which could bring the method of moments available for practical use. Our method outperforms other state-of-art methods that exhibit a closed-form expression of all four parameters of stable laws. Finally, the applicability of the method is illustrated by using several data of financial assets. Numerical results reveal that our approach is advantageous when modeling empirical data with stable distributions.
