Fractionally integrated curve time series with cointegration

Won-Ki Seo; Han Lin Shang

doi:10.1214/24-EJS2290

Fractionally integrated curve time series with cointegration

Won-Ki Seo^*, Han Lin Shang

^*Corresponding author for this work

Department of Actuarial Studies and Business Analytics

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

2 Citations (Scopus)

32 Downloads (Pure)

Abstract

We introduce methods and theory for fractionally cointegrated curve time series. We develop a variance-ratio test to determine the dimensions associated with the nonstationary and stationary subspaces. For each subspace, we apply a local Whittle estimator to estimate the long-memory parameter and establish its consistency. A Monte Carlo study of finite- sample performance is included, along with two empirical applications.

Original language	English
Pages (from-to)	3858 - 3902
Number of pages	45
Journal	Electronic Journal of Statistics
Volume	18
Issue number	2
DOIs	https://doi.org/10.1214/24-EJS2290
Publication status	Published - 9 Oct 2024

Bibliographical note

Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

fractional cointegration
long memory time series
functional data
functional principal component analysis
limit theorems

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10.1214/24-EJS2290Licence: CC BY

Publisher version (open access)Final published version, 875 KBLicence: CC BY

Cite this

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title = "Fractionally integrated curve time series with cointegration",

abstract = "We introduce methods and theory for fractionally cointegrated curve time series. We develop a variance-ratio test to determine the dimensions associated with the nonstationary and stationary subspaces. For each subspace, we apply a local Whittle estimator to estimate the long-memory parameter and establish its consistency. A Monte Carlo study of finite- sample performance is included, along with two empirical applications.",

keywords = "fractional cointegration, long memory time series, functional data, functional principal component analysis, limit theorems",

author = "Won-Ki Seo and Shang, {Han Lin}",

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AU - Seo, Won-Ki

AU - Shang, Han Lin

N1 - Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2024/10/9

Y1 - 2024/10/9

N2 - We introduce methods and theory for fractionally cointegrated curve time series. We develop a variance-ratio test to determine the dimensions associated with the nonstationary and stationary subspaces. For each subspace, we apply a local Whittle estimator to estimate the long-memory parameter and establish its consistency. A Monte Carlo study of finite- sample performance is included, along with two empirical applications.

AB - We introduce methods and theory for fractionally cointegrated curve time series. We develop a variance-ratio test to determine the dimensions associated with the nonstationary and stationary subspaces. For each subspace, we apply a local Whittle estimator to estimate the long-memory parameter and establish its consistency. A Monte Carlo study of finite- sample performance is included, along with two empirical applications.

KW - fractional cointegration

KW - long memory time series

KW - functional data

KW - functional principal component analysis

KW - limit theorems

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UR - https://purl.org/au-research/grants/arc/DP230102250

UR - https://purl.org/au-research/grants/arc/FT240100338

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SP - 3858

EP - 3902

JO - Electronic Journal of Statistics

JF - Electronic Journal of Statistics

IS - 2

ER -

Fractionally integrated curve time series with cointegration

Abstract

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Keywords

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