论文标题
经过广义拉普拉斯分布的矩的修改方法
Modified Method of Moments for Generalized Laplace Distribution
论文作者
论文摘要
在本说明中，我们考虑了经典的矩方法的性能，以估计对称方差伽马（广义拉普拉斯）分布的参数估计。我们通过理论分析（多元增量方法）和一项全面的仿真研究来实现这一目标，与最大似然估计进行了比较，发现性能通常不令人满意。此外，我们通过采用绝对时刻来提高效率来修改时刻方法。特别是，我们的仿真研究表明，我们修改的估计器在财务建模中通常会遇到的参数值显着提高了性能，并且在最大似然估计中也具有竞争力。
In this note, we consider the performance of the classic method of moments for parameter estimation of symmetric variance-gamma (generalized Laplace) distributions. We do this through both theoretical analysis (multivariate delta method) and a comprehensive simulation study with comparison to maximum likelihood estimation, finding performance is often unsatisfactory. In addition, we modify the method of moments by taking absolute moments to improve efficiency; in particular, our simulation studies demonstrate that our modified estimators have significantly improved performance for parameter values typically encountered in financial modelling, and is also competitive with maximum likelihood estimation.
