A new stochastic process with long-range dependence

Sung Ik Kim; Young Shin Kim

doi:10.2991/jsta.d.200923.001

A new stochastic process with long-range dependence

Sung Ik Kim
, Young Shin Kim

Dean's Office, College of Business

Louisiana State University in Shreveport

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, we introduce a fractional Generalized Hyperbolic process, a new stochastic process with long-range dependence obtained by subordinating fractional Brownian motion to a fractional Generalized Inverse Gaussian process. The basic properties and covariance structure between the elements of the processes are discussed, and we present numerical methods to generate the sample paths for the processes.

Original language	English
Pages (from-to)	432-438
Number of pages	7
Journal	Journal of Statistical Theory and Applications
Volume	19
Issue number	3
DOIs	https://doi.org/10.2991/jsta.d.200923.001
State	Published - Sep 2020

Keywords

Brownian motion
Brownian motion
Fractional
Generalized hyperbolic process
Long-range dependence
Lévy process
Time-changed

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10.2991/jsta.d.200923.001

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title = "A new stochastic process with long-range dependence",

abstract = "In this paper, we introduce a fractional Generalized Hyperbolic process, a new stochastic process with long-range dependence obtained by subordinating fractional Brownian motion to a fractional Generalized Inverse Gaussian process. The basic properties and covariance structure between the elements of the processes are discussed, and we present numerical methods to generate the sample paths for the processes.",

keywords = "Brownian motion, Brownian motion, Fractional, Generalized hyperbolic process, Long-range dependence, L{\'e}vy process, Time-changed",

author = "Kim, \{Sung Ik\} and Kim, \{Young Shin\}",

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PY - 2020/9

Y1 - 2020/9

N2 - In this paper, we introduce a fractional Generalized Hyperbolic process, a new stochastic process with long-range dependence obtained by subordinating fractional Brownian motion to a fractional Generalized Inverse Gaussian process. The basic properties and covariance structure between the elements of the processes are discussed, and we present numerical methods to generate the sample paths for the processes.

AB - In this paper, we introduce a fractional Generalized Hyperbolic process, a new stochastic process with long-range dependence obtained by subordinating fractional Brownian motion to a fractional Generalized Inverse Gaussian process. The basic properties and covariance structure between the elements of the processes are discussed, and we present numerical methods to generate the sample paths for the processes.

KW - Brownian motion

KW - Fractional

KW - Generalized hyperbolic process

KW - Long-range dependence

KW - Lévy process

KW - Time-changed

UR - https://www.scopus.com/pages/publications/85095868871

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DO - 10.2991/jsta.d.200923.001

M3 - Article

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VL - 19

SP - 432

EP - 438

JO - Journal of Statistical Theory and Applications

JF - Journal of Statistical Theory and Applications

IS - 3

ER -

A new stochastic process with long-range dependence

Abstract

Keywords

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