Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach

The presence of structural changes, specifically outliers and structural breaks, adversely affects the estimation of economic and financial indicators in terms of the model accuracy and forecasting performance. Focusing on the detection of outliers and structural breaks, which has recently gained gr...

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Main Author:	Rose, Farid Zamani Che
Format:	Thesis
Language:	English
Published:	2023
Subjects:	QA1 Mathematics (General)
Online Access:	http://eprints.usm.my/61267/1/24%20Pages%20from%20FARID%20ZAMANI%20BIN%20CHE%20ROSE.pdf
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spelling	my-usm-ep.612672024-10-11T01:02:31Z Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach 2023-03 Rose, Farid Zamani Che QA1 Mathematics (General) The presence of structural changes, specifically outliers and structural breaks, adversely affects the estimation of economic and financial indicators in terms of the model accuracy and forecasting performance. Focusing on the detection of outliers and structural breaks, which has recently gained growing research interest, this study aimed to examine the performance of indicator saturation, as an extension of the general-to-specific (GETS) modelling, in detecting these structural changes in structural time series model framework. The proposed technique is capable to detect the location, duration, magnitude and number of structural changes in time series data. To date, prior studies only considered using Autometrics embodied in OxMetrics to apply this approach in static data generating process (DGP). Addressing this gap, this study used the gets package in R to examine the performance of indicator saturation in dynamic model viz state space model. Through Monte Carlo simulations, the performance of indicator saturation was evaluated in terms of potency and gauge. Based on the simulation results, the sequential selection algorithm outperformed the non-sequential selection approach in the automatic GETS model selection procedure. The results also suggested α = 1/T as the optimum level of significance level. 2023-03 Thesis http://eprints.usm.my/61267/ http://eprints.usm.my/61267/1/24%20Pages%20from%20FARID%20ZAMANI%20BIN%20CHE%20ROSE.pdf application/pdf en public phd doctoral Perpustakaan Hamzah Sendut Pusat Pengajian Sains Matematik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA1 Mathematics (General)
spellingShingle	QA1 Mathematics (General) Rose, Farid Zamani Che Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach
description	The presence of structural changes, specifically outliers and structural breaks, adversely affects the estimation of economic and financial indicators in terms of the model accuracy and forecasting performance. Focusing on the detection of outliers and structural breaks, which has recently gained growing research interest, this study aimed to examine the performance of indicator saturation, as an extension of the general-to-specific (GETS) modelling, in detecting these structural changes in structural time series model framework. The proposed technique is capable to detect the location, duration, magnitude and number of structural changes in time series data. To date, prior studies only considered using Autometrics embodied in OxMetrics to apply this approach in static data generating process (DGP). Addressing this gap, this study used the gets package in R to examine the performance of indicator saturation in dynamic model viz state space model. Through Monte Carlo simulations, the performance of indicator saturation was evaluated in terms of potency and gauge. Based on the simulation results, the sequential selection algorithm outperformed the non-sequential selection approach in the automatic GETS model selection procedure. The results also suggested α = 1/T as the optimum level of significance level.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Rose, Farid Zamani Che
author_facet	Rose, Farid Zamani Che
author_sort	Rose, Farid Zamani Che
title	Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach
title_short	Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach
title_full	Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach
title_fullStr	Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach
title_full_unstemmed	Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach
title_sort	detection of outliers and structural breaks in structural time series model using indicator saturation approach
granting_institution	Perpustakaan Hamzah Sendut
granting_department	Pusat Pengajian Sains Matematik
publishDate	2023
url	http://eprints.usm.my/61267/1/24%20Pages%20from%20FARID%20ZAMANI%20BIN%20CHE%20ROSE.pdf
_version_	1818647382144843776

Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach

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