Modelling and forecasting volatile data by using ARIMA and GARCH models

Modelling and forecasting of volatile data have become the area of interest in financial time series. Volatility refers to a condition where the conditional variance changes between extremely high and extremely low values. In the current study, modelling and forecasting will be carried out using two sets of real data namely crude oil prices and kijang emas prices. The models investigated are Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model and Generalized Autoregressive Conditionally Heteroscedasticity (GARCH) model. In estimating the parameters for the Box-Jenkins ARIMA model, two estimation methods are used. These are Maximum Likelihood Estimation (MLE) and Ordinary Least Squares Estimation (OLS). The capabilities of these two methods in estimating the ARIMA models are evaluated by using Mean Absolute Percentage Error (MAPE). The modelling performances of ARIMA and GARCH models will be evaluated by using Akaike’s Information Criterion (AIC) while the forecasting performances of both models will be evaluated by using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). The processes of modelling and forecasting will be done by using R and Eviews statistical softwares. As a result of the study, it can be concluded that in terms of parameters estimation of ARIMA models, MLE gives more precise forecast for crude oil prices data while OLS gives more precise forecast for kijang emas prices data. In terms of forecasting performances between ARIMA and GARCH models, it can be concluded that GARCH is a better model for kijang emas prices data while ARIMA is a better model for crude oil prices data

Comparative performance of ARIMA and GARCH Models in modelling and forecasting volatility of Malaysia market properties and shares

Market properties and shares are important in the field of finance in order to measure the economic growth of a country. These market properties are volatile time series as they have huge price swings in a shortage or an oversupply period. In this study, we use two time series models which are Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heterocedasticity (GARCH) models in modelling and forecasting Malaysia property market. The capabilities of ARIMA and GARCH models in modelling and forecasting Malaysia property market will be evaluated by using Akaike's Information Criterion (AIC), Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE). It can be concluded that Box-Jenkins ARIMA model perform better compared than GARCH model in modelling and forecasting Malaysia market properties and shares

Macro-Factor Affecting the Electricity Load Demand in Power System

As Malaysia moves forward as a developed country, it is expected that electricity consumption will be increased when the economy, population and industry are growing. Therefore, this paper presents an analysis on the Macro-Factors such as geographical parameters, meteorological parameters, and economic parameters that affected the electricity load demand. A simple model is presented using correlation coefficient as a tool. On top of it, Johor Bahru and Skudai have been selected as a case study in this research due to the higher electricity demand in Johor. The result indicated that the economic element known as Gross Domestic Product (GDP), population and maximum temperature were the factors that significantly affected the electrical load demand. Furthermore, this finding will be useful for researchers in the same area as a reference for their research works and it is also advantageous for the electrical utility for optimum operational planning in the future

A hybrid model for improving Malaysian gold forecast accuracy

A hybrid model has been considered an effective way to improve forecast accuracy. This paper proposes the hybrid model of the linear autoregressive moving average (ARIMA) and the non-linear generalized autoregressive conditional heteroscedasticity (GARCH) in modeling and forecasting. Malaysian gold price is used to present the development of the hybrid model. The goodness of fit of the model is measured using Akaike information criteria (AIC) while the forecasting performance is assessed using bias, variance proportion, covariance proportion and mean absolute percentage error (MAPE)

Comparative Performance Of ARIMA And DES Models In Forecasting Electricity Load Demand In Malaysia

Malaysia is a developing country which is having a high level of energy demand. Load demand forecasting is essential that is also in line with increasing demand of electricity. The purpose of the current study is to compare the performance of two time series models in forecasting electricity load demand in Malaysia. Two methods are considered, which are Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) and Double Exponential Smoothing (DES). Using Mean Absolute Percentage Error (MAPE) as the forecasting performance measure, the study concludes that ARIMA is more appropriate model

ARAR Algorithm In Forecasting Electricity Load Demand In Malaysia

Electricity load demand has grown more than four-fold over the last 20 years period. The purpose of the current study is to evaluate the performance of ARAR model in forecasting electricity load demand in Malaysia. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) will be used as a benchmark model since the model has been proven in many forecasting context. Using Root Mean Square Error (RMSE) as the forecasting performance measure, the study concludes that ARAR is more appropriate model

Final Year Student’s Perception before Engaging Engineering Technology Program in UTeM

In line with industrial development which is growing rapidly in Malaysia, the country is in great needs of competent technical workforce able to apply the latest concept of technology, improve equipment and system utilization, optimizing operation and maintenance of equipment. Therefore, an engineering technology program will be introduced in Malaysia education system at higher level. In determining the perception of Engineering Technology program in Universiti Teknikal Malaysia Melaka (UTeM), a market survey has been conducted to gather the perception of the final year students about Engineering Technology. Total numbers of 123 students from Cohort 1 with two different departments, electrical and manufacturing were used as a sample space. The scope of the market survey covered regarding their perspective and understanding of Engineering Technology before enrolling engineering technology program from their perspective courses. The findings show that there is a difference perception in overall especially regarding their understanding of terms Engineering Technology Programs

Estimating down time of glove dipping machines operation using Exponential and Weibull distributions

Reliability of any particular component or system is very important as it involves the whole stage of the product life-cycle. It is necessary for a factory to ensure that down time is managed proactively to ensure efficient product manufacturing process. It is common for many manufacturing plants to conduct preventive and corrective maintenance because long machine repair time will cause loss of productivity and revenue. In order to minimize repair time, both inventory and workforce preparation are crucial. This paper uses statistical methods to determine proper time slots to conduct preventive maintenance of a machine. The proposed method determines Mean Time to Failure (MTTF) via Exponential and Weibull distributions using time to failure data of two sets of similar machines from glove manufacturing production line. Results revealed that Weibull distribution offered better MTTF prediction performance compared to Exponential distribution. By pairwise comparison, these two methods do not present significant difference, and hence, both methods could serve as the benchmark in designing potential preventive maintenance strategy

FTK Students’ Performance in Mathematics: Comparison between SPM and First Year Exam

In the last 20 years, mathematics teaching and learning encounters quite a big problem, especially at the tertiary level. The main concern always surrounds the students’ achievement in the subject matter. Students’ performance in mathematics at first year is reflected by the students’ mathematical background prior to the admittance into the university. The study examined 165 first year students in the Faculty of Engineering Technology (FTK) who took the Mathematics Competency test upon entering the university at the beginning of their first semester. A test consisted of 40 fundamental mathematical questions which students have learned them before. From the result, 84% of these students failed this test. However, looking at their Sijil Pelajaran Malaysia (SPM) mathematics result during Form Five (12th grade) in school, the majority did quite well in that exam. These students also took a first year mathematics course which is Technical Mathematics at the same semester. At the end of the semester, the result of their Technical Mathematics course seemed to be quite good. The performance of these three mathematics results was being compared and studied

FTK Students’ Performance in Mathematics: Comparison between SPM and First Year Exam

In the last 20 years, mathematics teaching and learning encounters quite a big problem, especially at the tertiary level. The main concern always surrounds the students’ achievement in the subject matter. Students’ performance in mathematics at first year is reflected by the students’ mathematical background prior to the admittance into the university. The study examined 165 first year students in the Faculty of Engineering Technology (FTK) who took the Mathematics Competency test upon entering the university at the beginning of their first semester. A test consisted of 40 fundamental mathematical questions which students have learned them before. From the result, 84% of these students failed this test. However, looking at their Sijil Pelajaran Malaysia (SPM) mathematics result during Form Five (12th grade) in school, the majority did quite well in that exam. These students also took a first year mathematics course which is Technical Mathematics at the same semester. At the end of the semester, the result of their Technical Mathematics course seemed to be quite good. The performance of these three mathematics results was being compared and studied