时变扩散模型中收益参数向量的局部复合分位回归估计

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英文篇名：Local composite quantile regression estimation of return parameter vector for time-varying diffusion model 作者：王静 ; 王继霞 英文作者：Wang Jing;Wang Jixia;College of Mathematics and Information Science,Henan Normal University; 关键词：时变扩散模型 ; 时变参数向量 ; 局部线性拟合 ; 复合分位回归 ; 渐近正态性 英文关键词：time-varying diffusion model;;time-varying parameter vector;;local linear fitting;;composite quantile regression estimation;;asymptotic normality 中文刊名：HNSX 英文刊名：Journal of Henan Normal University(Natural Science Edition) 机构：河南师范大学数学与信息科学学院; 出版日期：2019-01-09 14:31 出版单位：河南师范大学学报(自然科学版) 年：2019 期：v.47;No.204 基金：国家自然科学基金(U1504701);; 河南师范大学博士科研启动课题(qd15184) 语种：中文; 页：HNSX201901006 页数：5 CN：01 ISSN：41-1109/N 分类号：46-50

摘要

主要研究多维时变扩散模型中收益参数向量的估计问题.基于离散观测样本,利用局部线性拟合的方法,得到了时变漂移参数向量的局部复合分位回归估计,并证明了估计量的渐近正态性.同时,给出了估计量的渐近偏差和渐近方差.
        Local composite quantile regression estimation of return parameter vector for time-varying diffusion model is studied.Based on discretely observed sample,the local linear composite quantile regression(CQR)estimation of the drift parameter vector is proposed by using the local linear fitting for parameter vector,and the asymptotic normality of local estimation is verified.Moreover,the asymptotic bias and asymptotic variance of the local estimation are provided.

引文

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