吉林大学学报(理学版)2025,Vol.63Issue(1) :41-46.DOI:10.13413/j.cnki.jdxblxb.2024446

由分数Brown运动驱动的EGARCH模型

EG ARCH Model Driven by Fractional Brownian Motion

王玮莹 韩月才
吉林大学学报(理学版)2025,Vol.63Issue(1) :41-46.DOI:10.13413/j.cnki.jdxblxb.2024446

由分数Brown运动驱动的EGARCH模型

EG ARCH Model Driven by Fractional Brownian Motion

王玮莹 1韩月才1
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作者信息

  • 1. 吉林大学数学学院,长春 130012
  • 折叠

摘要

针对传统EGARCH模型难以捕捉长记忆性的问题,通过引入分数Brown运动提出一个fBm-EGARCH模型,给出模型的二阶矩、四阶矩及协方差函数性质,并理论证明其长期记忆性.数值模拟结果表明,该模型不仅能准确捕捉短期波动,还能反映长期记忆性,从而验证了模型的有效性.

Abstract

Aiming at the problem that the traditional EGARCH model was difficult to capture long-term memory,we proposed an fBm-EGARCH model by introducing fractional Brownian motion.We gave the second-order moment,the fourth-order moment and covariance function properties of the model,and theoretically proved its long-term memory.Numerical simulation results show that the model can not only accurately capture short-term fluctuations,but also reflect long-term memory,which verifies the effectiveness of the model.

关键词

EGARCH模型/分数Brown运动/长期记忆性/流动性

Key words

EGARCH model/fractional Brownian motion/long-term memory/liquidity

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出版年

2025
吉林大学学报(理学版)
吉林大学

吉林大学学报(理学版)

北大核心
影响因子:0.46
ISSN:1671-5489
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