Model performance between linear vector autoregressive and Markov switching vector autoregressive models on modelling structural change in time series data

Real financial time series data always exhibit structural change, jumps or breaks. Thus, in this paper, the performance of the linear vector autoregressive model (VAR), mean adjusted Markov switching vector autoregressive model (MSM-VAR) and mean adjusted heteroskedasticity Markov switching vector a...

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Main Authors: Wai, P.S., Kun, S.S., Ismail, M.T., Karim, S.A.A.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.30917 /
Published: Institute of Electrical and Electronics Engineers Inc. 2016
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995605754&doi=10.1109%2fISMSC.2015.7594083&partnerID=40&md5=f4f6939c1b18769060fd3ba464fd8216
http://eprints.utp.edu.my/30917/
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spelling utp-eprints.309172022-03-25T07:43:37Z Model performance between linear vector autoregressive and Markov switching vector autoregressive models on modelling structural change in time series data Wai, P.S. Kun, S.S. Ismail, M.T. Karim, S.A.A. Real financial time series data always exhibit structural change, jumps or breaks. Thus, in this paper, the performance of the linear vector autoregressive model (VAR), mean adjusted Markov switching vector autoregressive model (MSM-VAR) and mean adjusted heteroskedasticity Markov switching vector autoregressive model (MSMH-VAR) are applied in order to examine the oil price return and the gold price return effect on stock market returns. The two break point tests indicate the existence of break dates in the data. In addition, a comparison among the three model's performance show that the two Markov switching vector autoregressive models with first autoregressive order able to provide the most significance, reliable and valid results as compared to linear vector autoregressive. © 2015 IEEE. Institute of Electrical and Electronics Engineers Inc. 2016 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995605754&doi=10.1109%2fISMSC.2015.7594083&partnerID=40&md5=f4f6939c1b18769060fd3ba464fd8216 Wai, P.S. and Kun, S.S. and Ismail, M.T. and Karim, S.A.A. (2016) Model performance between linear vector autoregressive and Markov switching vector autoregressive models on modelling structural change in time series data. In: UNSPECIFIED. http://eprints.utp.edu.my/30917/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Real financial time series data always exhibit structural change, jumps or breaks. Thus, in this paper, the performance of the linear vector autoregressive model (VAR), mean adjusted Markov switching vector autoregressive model (MSM-VAR) and mean adjusted heteroskedasticity Markov switching vector autoregressive model (MSMH-VAR) are applied in order to examine the oil price return and the gold price return effect on stock market returns. The two break point tests indicate the existence of break dates in the data. In addition, a comparison among the three model's performance show that the two Markov switching vector autoregressive models with first autoregressive order able to provide the most significance, reliable and valid results as compared to linear vector autoregressive. © 2015 IEEE.
format Conference or Workshop Item
author Wai, P.S.
Kun, S.S.
Ismail, M.T.
Karim, S.A.A.
spellingShingle Wai, P.S.
Kun, S.S.
Ismail, M.T.
Karim, S.A.A.
Model performance between linear vector autoregressive and Markov switching vector autoregressive models on modelling structural change in time series data
author_sort Wai, P.S.
title Model performance between linear vector autoregressive and Markov switching vector autoregressive models on modelling structural change in time series data
title_short Model performance between linear vector autoregressive and Markov switching vector autoregressive models on modelling structural change in time series data
title_full Model performance between linear vector autoregressive and Markov switching vector autoregressive models on modelling structural change in time series data
title_fullStr Model performance between linear vector autoregressive and Markov switching vector autoregressive models on modelling structural change in time series data
title_full_unstemmed Model performance between linear vector autoregressive and Markov switching vector autoregressive models on modelling structural change in time series data
title_sort model performance between linear vector autoregressive and markov switching vector autoregressive models on modelling structural change in time series data
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2016
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995605754&doi=10.1109%2fISMSC.2015.7594083&partnerID=40&md5=f4f6939c1b18769060fd3ba464fd8216
http://eprints.utp.edu.my/30917/
_version_ 1741197489193615360
score 11.62408

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