Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach
The indicator saturation approach is one of the latest methods in the literature that Can detect both the outlier and structural break dates simultaneously in a financial time series data. As the approach applied general-to-specific modelling in identifying the most significant indicators, gets pac...
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my-usm-ep.525582022-05-23T07:04:43Z Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach 2020-11 Mohammad Nasir, Muhammad Azim QA1 Mathematics (General) The indicator saturation approach is one of the latest methods in the literature that Can detect both the outlier and structural break dates simultaneously in a financial time series data. As the approach applied general-to-specific modelling in identifying the most significant indicators, gets package in r and autometrics in oxmetrics can handle the concerns of more variables than observations number, t . As far as we are aware of, all the leading researches use autometrics in their research and most of them carried out simple static data generating process, (dgp) in monte carlo simulations to investigate the performance of indicator saturation. 2020-11 Thesis http://eprints.usm.my/52558/ http://eprints.usm.my/52558/1/Pages%20from%20Final%20Thesis%20Muhammad%20Azim%20Mohammad%20Nasir.pdf application/pdf en public masters Universiti Sains Malaysia Pusat Pengajian Sains Matematik |
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QA1 Mathematics (General) |
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QA1 Mathematics (General) Mohammad Nasir, Muhammad Azim Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach |
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The indicator saturation approach is one of the latest methods in the literature that
Can detect both the outlier and structural break dates simultaneously in a financial time series data. As the approach applied general-to-specific modelling in identifying the most significant indicators, gets package in r and autometrics in oxmetrics can handle the concerns of more variables than observations number, t . As far as we are aware of, all the leading researches use autometrics in their research and most of them carried out simple static data generating process, (dgp) in monte carlo simulations to investigate the performance of indicator saturation. |
format |
Thesis |
qualification_level |
Master's degree |
author |
Mohammad Nasir, Muhammad Azim |
author_facet |
Mohammad Nasir, Muhammad Azim |
author_sort |
Mohammad Nasir, Muhammad Azim |
title |
Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach |
title_short |
Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach |
title_full |
Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach |
title_fullStr |
Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach |
title_full_unstemmed |
Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach |
title_sort |
outliers and structural breaks detection in autoregressive model by indicator saturation approach |
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Universiti Sains Malaysia |
granting_department |
Pusat Pengajian Sains Matematik |
publishDate |
2020 |
url |
http://eprints.usm.my/52558/1/Pages%20from%20Final%20Thesis%20Muhammad%20Azim%20Mohammad%20Nasir.pdf |
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