A new combined approach on Hurst exponent estimate and its applications in realized volatility

被引：12

作者：

Luo, Yi ^{[1
]}

Huang, Yirong ^{[2
]}

机构：

[1] Guangdong Polytech Normal Univ, Management Coll, Guangzhou 510665, Guangdong, Peoples R China

[2] Sun Yat Sen Univ, Business Sch, Guangzhou 510275, Guangdong, Peoples R China

来源：

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2018年 / 492卷

关键词：

Hurst exponent; Rescaled range; Fractional Gaussian noise; Monte Carlo simulation; Volatility; TIME-SERIES; RESCALED VARIANCE; MONTE-CARLO; MEMORY; R/S; MODELS; TESTS;

D O I：

10.1016/j.physa.2017.11.063

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

The purpose of this paper is to propose a new estimator of Hurst exponent based on the combined information of the conventional rescaled range methods. We demonstrate the superiority of the proposed estimator by Monte Carlo simulations, and the applications in estimating the Hurst exponent of daily volatility series in Chinese stock market. Moreover, we indicate the impact of the type of estimator and structural break on the estimating results of Hurst exponent. (C) 2017 Elsevier B.V. All rights reserved.

引用

页码：1364 / 1372

页数：9

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