...
首页> 外文期刊>Abstract and applied analysis >Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation
【24h】

Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation

机译:离散观测时长记忆随机波动率的参数估计

获取原文
           

摘要

Ordinary least squares estimators of variogram parameters in long-memory stochasticvolatility are studied in this paper. We use the discrete observations for practicalpurposes under the assumption that the Hurst parameterH∈(1/2,1)is known. Based on the ordinary least squares method, we obtain both the explicit estimatorsfor drift and diffusion by minimizing the distance function between the variogramand the data periodogram. Furthermore, the resulting estimators are shown to beconsistent and to have the asymptotic normality. Numerical examples are alsopresented to illustrate the performance of our method.
机译:本文研究了长记忆随机波动率中变异函数参数的普通最小二乘估计。在已知赫斯特参数H∈(1 / 2,1)的假设下,我们将离散观测用于实际目的。基于普通最小二乘法,我们通过最小化变异函数图和数据周期图之间的距离函数,获得了漂移和扩散的显式估计量。此外,所得的估计量被证明是一致的并且具有渐近正态性。数值例子也被用来说明我们方法的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号