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...
| 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/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: |
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. |
|---|