Comparative performance of ARIMA and ARCH GARCH models on time series of traffic accidents in Gaza Strip
Other Title(s)
الأداء المقارن لنماذج آريما و نماذج آرش قارش على السلاسل الزمنية للحوادث المرورية في قطاع غزة
Dissertant
al-Ajiz, Raja Muhammad Mustafa
Thesis advisor
Comitee Members
Salihah, Raid Bashir Ibrahim
al-Hanjuri, Mumin Muhammad Ramadan
University
Islamic University
Faculty
Faculty of Science
Department
Department of Mathematics
University Country
Palestine (Gaza Strip)
Degree
Master
Degree Date
2016
English Abstract
The accuracy of forecasts using time series models has recently received a great atten- tion.
The Box-Jenkins, SARIMA models have been the most widely used models for forecasting.
These models give good forecasts for future observations but they are not so accurate for many ones.
Recent studies suggest that GARCH models which take into ac- count volatility in the time series can be a promising alternative to the traditional method SARIMA in forecasting especially in the case of non-linear data and for forecasting many future forecast values.
The aim of this study is to evaluate the performance of SARIMA as linear models and GARCH as non-linear models to forecast monthly Trac Accident number in Gaza-Strip.
This study used the Box-Jenkins methodology and GARCH approach in analysing the Trac Accident data.
We consider multiple time series models for tting our data for the period from 1st January 1995 to 31st December 2014, The data are divided into two parts.
One is for model's estimation and another is for tasting purposes.
We selected the best SARIMA models and the best GARCH model based on model selection crite- ria AIC, AICc and BIC, then we made a comparison between SARIMA(3; 1; 2)(1; 0; 1)12 and ARMA(1; 1)?GARCH(1; 1) models in order to determine which better to use in similar situation.
The analysis of this study are carried out with the assist of R soft- ware.
The accuracy of GARCH and SARIMA models for forecasting monthly Trac Accidents in Gaza Strip was compared using di erent statistical forecast evaluation cri- teria MAE, MSE, RMSE and MAPE eciency between SARIMA(3; 1; 2)(1; 0; 1)12 and ARMA(1; 1)?GARCH(1; 1) model, we found that nonlinear models outperform linear models and ARMA(1; 1)?GARCH(1; 1) outperforms SARIMA(3; 1; 2)(1; 0; 1)12 model.
Main Subjects
Sociology and Anthropology and Social Work
No. of Pages
95
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Fundamental concepts and definitions.
Chapter Three : Seasonal ARIMA models.
Chapter Four : Conditional heteroscedasticity : ARCH / GARCH models.
Chapter Five : Case study.
Chapter Six : Conclusions and recommendations.
References.
American Psychological Association (APA)
al-Ajiz, Raja Muhammad Mustafa. (2016). Comparative performance of ARIMA and ARCH GARCH models on time series of traffic accidents in Gaza Strip. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-688579
Modern Language Association (MLA)
al-Ajiz, Raja Muhammad Mustafa. Comparative performance of ARIMA and ARCH GARCH models on time series of traffic accidents in Gaza Strip. (Master's theses Theses and Dissertations Master). Islamic University. (2016).
https://search.emarefa.net/detail/BIM-688579
American Medical Association (AMA)
al-Ajiz, Raja Muhammad Mustafa. (2016). Comparative performance of ARIMA and ARCH GARCH models on time series of traffic accidents in Gaza Strip. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-688579
Language
English
Data Type
Arab Theses
Record ID
BIM-688579
