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Maximum Overlapping Discrete Wavelet Methods For Modelling The Saudi Stock Exchange

This study forecasts the stock volatility based on wavelet-based generalized autoregressive conditional heteroscedasticity (GARCH) methods. It builds a forecast model based on GARCH methods, autoregressive integrated moving average (ARIMA) method, and maximum overlap discrete wavelet transform (MODW...

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Main Author: T, Alshammari Tariq Saleh
Format: Thesis
Language:English
Published: 2023
Subjects:
QA1 Mathematics (General)
Online Access:http://eprints.usm.my/60278/1/ALSHAMMARI%20TARIQ%20SALEH%20T%20-%20TESIS24.pdf
http://eprints.usm.my/60278/
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spelling my.usm.eprints.60278 http://eprints.usm.my/60278/ Maximum Overlapping Discrete Wavelet Methods For Modelling The Saudi Stock Exchange T, Alshammari Tariq Saleh QA1 Mathematics (General) This study forecasts the stock volatility based on wavelet-based generalized autoregressive conditional heteroscedasticity (GARCH) methods. It builds a forecast model based on GARCH methods, autoregressive integrated moving average (ARIMA) method, and maximum overlap discrete wavelet transform (MODWT) based on the best-localized function (Bl14) models. The aim is to measure the volatility of stock market forecasting through the non-linear spectral model, GARCH models, which are general GARCH (gGARCH), exponential generalized autoregressive conditional heteroscedasticity (EGARCH) and Glostsen-Jagannathan-Runkle-GARCH (GJR-GARCH) functions, MODWT based on best-localized function (Bl14), and ARIMA model. Also, the study will build a prediction model based on GARCH, ARIMA and MODWT methods based on best-localized function models (Bl14). The developed model was used in the Saudi stock market from August 2011 to December 31, 2019. The study results show that the Saudi Stock Exchange Market witnessed high volatility in several periods. Market returns show a non-normal distribution indicating high volatility among returns. The highest closing price and return volatility was recorded in 2015 and 2016. The GARCH (1,1) model is the best model used to measure volatility. Instabilities are checked and displayed using MODWT based on B114 capabilities. The hybrid method is best for forecasting closing prices and returns in Tadawul Stock Exchange Market (TSEM). The study recommends that the GARCH model based on the normal distribution is the best for measuring volatility, and the hybrid method is the best method that can be used for forecasting. 2023-09 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/60278/1/ALSHAMMARI%20TARIQ%20SALEH%20T%20-%20TESIS24.pdf T, Alshammari Tariq Saleh (2023) Maximum Overlapping Discrete Wavelet Methods For Modelling The Saudi Stock Exchange. PhD thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic QA1 Mathematics (General)
spellingShingle QA1 Mathematics (General)
T, Alshammari Tariq Saleh
Maximum Overlapping Discrete Wavelet Methods For Modelling The Saudi Stock Exchange
description This study forecasts the stock volatility based on wavelet-based generalized autoregressive conditional heteroscedasticity (GARCH) methods. It builds a forecast model based on GARCH methods, autoregressive integrated moving average (ARIMA) method, and maximum overlap discrete wavelet transform (MODWT) based on the best-localized function (Bl14) models. The aim is to measure the volatility of stock market forecasting through the non-linear spectral model, GARCH models, which are general GARCH (gGARCH), exponential generalized autoregressive conditional heteroscedasticity (EGARCH) and Glostsen-Jagannathan-Runkle-GARCH (GJR-GARCH) functions, MODWT based on best-localized function (Bl14), and ARIMA model. Also, the study will build a prediction model based on GARCH, ARIMA and MODWT methods based on best-localized function models (Bl14). The developed model was used in the Saudi stock market from August 2011 to December 31, 2019. The study results show that the Saudi Stock Exchange Market witnessed high volatility in several periods. Market returns show a non-normal distribution indicating high volatility among returns. The highest closing price and return volatility was recorded in 2015 and 2016. The GARCH (1,1) model is the best model used to measure volatility. Instabilities are checked and displayed using MODWT based on B114 capabilities. The hybrid method is best for forecasting closing prices and returns in Tadawul Stock Exchange Market (TSEM). The study recommends that the GARCH model based on the normal distribution is the best for measuring volatility, and the hybrid method is the best method that can be used for forecasting.
format Thesis
author T, Alshammari Tariq Saleh
author_facet T, Alshammari Tariq Saleh
author_sort T, Alshammari Tariq Saleh
title Maximum Overlapping Discrete Wavelet Methods For Modelling The Saudi Stock Exchange
title_short Maximum Overlapping Discrete Wavelet Methods For Modelling The Saudi Stock Exchange
title_full Maximum Overlapping Discrete Wavelet Methods For Modelling The Saudi Stock Exchange
title_fullStr Maximum Overlapping Discrete Wavelet Methods For Modelling The Saudi Stock Exchange
title_full_unstemmed Maximum Overlapping Discrete Wavelet Methods For Modelling The Saudi Stock Exchange
title_sort maximum overlapping discrete wavelet methods for modelling the saudi stock exchange
publishDate 2023
url http://eprints.usm.my/60278/1/ALSHAMMARI%20TARIQ%20SALEH%20T%20-%20TESIS24.pdf
http://eprints.usm.my/60278/
_version_ 1794634924992495616
score 13.211869

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