Autoregression Model of Time Series with Matrix Cross-Section Data

Shu Jin Wu; Nan Hua

doi:10.12386/A20190057

Autoregression Model of Time Series with Matrix Cross-Section Data

Shu Jin Wu
, Nan Hua

统计学院

East China Normal University

科研成果: 期刊稿件 › 文章 › 同行评审

3 引用（Scopus）

摘要

The advantage of time series with matrix cross-section data is that multiple attributes of multiple objects can be characterized simultaneously. This paper focuses on autoregression model of time series with matrix cross-section data and presents the methods of parameter estimation, model identification and white noise test. Finally, the daily yield series and daily volume change rate series of two bank stocks are analyzed by this model.

源语言	英语
页（从-至）	1093-1104
页数	12
期刊	Acta Mathematica Sinica, Chinese Series
卷	65
期	6
DOI	https://doi.org/10.12386/A20190057
出版状态	已出版 - 15 11月 2022

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10.12386/A20190057

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title = "Autoregression Model of Time Series with Matrix Cross-Section Data",

abstract = "The advantage of time series with matrix cross-section data is that multiple attributes of multiple objects can be characterized simultaneously. This paper focuses on autoregression model of time series with matrix cross-section data and presents the methods of parameter estimation, model identification and white noise test. Finally, the daily yield series and daily volume change rate series of two bank stocks are analyzed by this model.",

keywords = "likelihood ratio test, parameter estimation, time series with matrix cross-section data, white noise test",

author = "Wu, \{Shu Jin\} and Nan Hua",

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T1 - Autoregression Model of Time Series with Matrix Cross-Section Data

AU - Wu, Shu Jin

AU - Hua, Nan

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N2 - The advantage of time series with matrix cross-section data is that multiple attributes of multiple objects can be characterized simultaneously. This paper focuses on autoregression model of time series with matrix cross-section data and presents the methods of parameter estimation, model identification and white noise test. Finally, the daily yield series and daily volume change rate series of two bank stocks are analyzed by this model.

AB - The advantage of time series with matrix cross-section data is that multiple attributes of multiple objects can be characterized simultaneously. This paper focuses on autoregression model of time series with matrix cross-section data and presents the methods of parameter estimation, model identification and white noise test. Finally, the daily yield series and daily volume change rate series of two bank stocks are analyzed by this model.

KW - likelihood ratio test

KW - parameter estimation

KW - time series with matrix cross-section data

KW - white noise test

UR - https://www.scopus.com/pages/publications/85158898511

U2 - 10.12386/A20190057

DO - 10.12386/A20190057

M3 - 文章

AN - SCOPUS:85158898511

SN - 0583-1431

VL - 65

SP - 1093

EP - 1104

JO - Acta Mathematica Sinica, Chinese Series

JF - Acta Mathematica Sinica, Chinese Series

IS - 6

ER -

Autoregression Model of Time Series with Matrix Cross-Section Data

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