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...

Full description

Saved in:

Bibliographic Details
Main Author:	Mohammad Nasir, Muhammad Azim
Format:	Thesis
Language:	English
Published:	2020
Subjects:	QA1 Mathematics (General)
Online Access:	http://eprints.usm.my/52558/1/Pages%20from%20Final%20Thesis%20Muhammad%20Azim%20Mohammad%20Nasir.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-usm-ep.52558
record_format	uketd_dc
spelling	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
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA1 Mathematics (General)
spellingShingle	QA1 Mathematics (General) Mohammad Nasir, Muhammad Azim Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach
description	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
granting_institution	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
_version_	1747822190772879360

Outliers And Structural Breaks Detection In Autoregressive Model By Indicator Saturation Approach

Similar Items