Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017), 2019
In this paper, Autoregressive Fractionally Integrated Moving Average (ARFIMA) model was modified ... more In this paper, Autoregressive Fractionally Integrated Moving Average (ARFIMA) model was modified and was used for modeling the daily Malaysia Stock Price Index (MSPI). The long and slow decline in autocorrelation function of the data showed the presence of Long Memory (LM) structure. Therefore, the Mandelbrot and Lo rescaled-range tests were used to test the presence of LM. The ARFIMA model then is further extend to the Autoregressive Fractionally Unit Root Integrated Moving Average (ARFURIMA) model. The Geweke and Porter-Hudak (GPH), Local Whittle Estimator (LWE), and Hurst Exponent (HE) were used as the estimation methods to obtain the LM parameters d of both ARFIMA and ARFURIMA models. The best model was identified for each of ARFIMA and ARFURIMA models respectively based on the minimum Akaike Information Criteria (AIC) values. The best fitted model were specified as ARFIMA (2,0.989,0) and ARFURIMA (1,1.069,0). Having compared the residuals analysis of the two models, we conclude that the ARFURIMA model was better in estimating series that exhibit Interminable LM (ILM).
Abstract: It is well known that many countries around the world depend on the US as their major t... more Abstract: It is well known that many countries around the world depend on the US as their major trade partner. As a result, if something does happen to US economy it surely will affect the economy of all these countries. In this study, we investigate the relationship between the US and four Asian emerging stock
Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017), 2019
In this paper, Autoregressive Fractionally Integrated Moving Average (ARFIMA) model was modified ... more In this paper, Autoregressive Fractionally Integrated Moving Average (ARFIMA) model was modified and was used for modeling the daily Malaysia Stock Price Index (MSPI). The long and slow decline in autocorrelation function of the data showed the presence of Long Memory (LM) structure. Therefore, the Mandelbrot and Lo rescaled-range tests were used to test the presence of LM. The ARFIMA model then is further extend to the Autoregressive Fractionally Unit Root Integrated Moving Average (ARFURIMA) model. The Geweke and Porter-Hudak (GPH), Local Whittle Estimator (LWE), and Hurst Exponent (HE) were used as the estimation methods to obtain the LM parameters d of both ARFIMA and ARFURIMA models. The best model was identified for each of ARFIMA and ARFURIMA models respectively based on the minimum Akaike Information Criteria (AIC) values. The best fitted model were specified as ARFIMA (2,0.989,0) and ARFURIMA (1,1.069,0). Having compared the residuals analysis of the two models, we conclude...
It is well known that many countries around the world depend on the US as their major trade partn... more It is well known that many countries around the world depend on the US as their major trade partner. As a result, if something does happen to US economy it surely will affect the economy of all these countries. In this study, we investigate the relationship between the US and four Asian emerging stock markets namely Hong Kong, India, South Korea and Malaysia using monthly data between 1996 and 2008. In order to model the relationships, two approaches are used. They are linear Vector Autoregressive (VAR) model and nonlinear Markov Switching Vector Autoregressive (MS-VAR) model. In general we found that the two models manage to explore the possibility of relationship between all the stock markets. Nevertheless, MS-VAR model provide more insight on when all this relationship occurred. In addition, the result also indicates that the MS-VAR model fitted the data well than the linear VAR model.
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND TECHNOLOGY 2020 (MATHTECH 2020): Sustainable Development of Mathematics & Mathematics in Sustainability Revolution
Communications in Statistics - Simulation and Computation, 2012
In this article, we present the problem of selecting a good stochastic system with high probabili... more In this article, we present the problem of selecting a good stochastic system with high probability and minimum total simulation cost when the number of alternatives is very large. We propose a sequential approach that starts with the Ordinal Optimization procedure to ...
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND TECHNOLOGY 2018 (MATHTECH2018): Innovative Technologies for Mathematics & Mathematics for Technological Innovation
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND TECHNOLOGY 2018 (MATHTECH2018): Innovative Technologies for Mathematics & Mathematics for Technological Innovation
Malaysian Journal of Fundamental and Applied Sciences
The present study investigates the causal relationship between ASEAN seven member countries elect... more The present study investigates the causal relationship between ASEAN seven member countries electricity consumption (EC) and some determinants such as gross domestic product (GDP), exports (EXP) and carbon dioxide emission (CO2) using vector autoregressive (VAR) framework via vector error correction (VEC) model for the period from 1980-2015. The findings show that the effect of the chosen determinants is different among the seven countries. Within the sample period, by utilizing Granger causality test, out of the seven countries, only four revealed either unidirectional or bidirectional causality running from EC to the three determinants, GDP, EXP and CO2. Whereas, thru forecast error variance decomposition (FEVD), forecasting beyond the sample period uncovered a shock to EC will also spread to GDP, EXP and CO2. The present study suggests that ASEAN should take note in designing their electricity policy, since electricity affect and be affected by other factors. In addition, ASEAN a...
Statistical selection approaches are used to select the best stochastic system from a finite set ... more Statistical selection approaches are used to select the best stochastic system from a finite set of alternatives. The best system will be the system with minimum or maximum performance measure. We consider the problem of selecting the best system when the number of alternative systems is huge. Three-stage and Four-stage selection approaches are proposed to solve this problem. The main strategy in these two selection approaches involves a combination method of cardinal and ordinal optimization. Ordinal optimization procedure is used to reduce the number of systems in the search space such that to be appropriate for cardinal optimization procedures. Three-stage selection approach consists three procedures; ordinal optimization, subset selection and indifference-zone. While, four-stage selection approach consists four procedures; ordinal optimization, optimal computing budget allocation, subset selection and indifference-zone. In this paper, we compare the performance between the two s...
Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017), 2019
In this paper, Autoregressive Fractionally Integrated Moving Average (ARFIMA) model was modified ... more In this paper, Autoregressive Fractionally Integrated Moving Average (ARFIMA) model was modified and was used for modeling the daily Malaysia Stock Price Index (MSPI). The long and slow decline in autocorrelation function of the data showed the presence of Long Memory (LM) structure. Therefore, the Mandelbrot and Lo rescaled-range tests were used to test the presence of LM. The ARFIMA model then is further extend to the Autoregressive Fractionally Unit Root Integrated Moving Average (ARFURIMA) model. The Geweke and Porter-Hudak (GPH), Local Whittle Estimator (LWE), and Hurst Exponent (HE) were used as the estimation methods to obtain the LM parameters d of both ARFIMA and ARFURIMA models. The best model was identified for each of ARFIMA and ARFURIMA models respectively based on the minimum Akaike Information Criteria (AIC) values. The best fitted model were specified as ARFIMA (2,0.989,0) and ARFURIMA (1,1.069,0). Having compared the residuals analysis of the two models, we conclude that the ARFURIMA model was better in estimating series that exhibit Interminable LM (ILM).
Abstract: It is well known that many countries around the world depend on the US as their major t... more Abstract: It is well known that many countries around the world depend on the US as their major trade partner. As a result, if something does happen to US economy it surely will affect the economy of all these countries. In this study, we investigate the relationship between the US and four Asian emerging stock
Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017), 2019
In this paper, Autoregressive Fractionally Integrated Moving Average (ARFIMA) model was modified ... more In this paper, Autoregressive Fractionally Integrated Moving Average (ARFIMA) model was modified and was used for modeling the daily Malaysia Stock Price Index (MSPI). The long and slow decline in autocorrelation function of the data showed the presence of Long Memory (LM) structure. Therefore, the Mandelbrot and Lo rescaled-range tests were used to test the presence of LM. The ARFIMA model then is further extend to the Autoregressive Fractionally Unit Root Integrated Moving Average (ARFURIMA) model. The Geweke and Porter-Hudak (GPH), Local Whittle Estimator (LWE), and Hurst Exponent (HE) were used as the estimation methods to obtain the LM parameters d of both ARFIMA and ARFURIMA models. The best model was identified for each of ARFIMA and ARFURIMA models respectively based on the minimum Akaike Information Criteria (AIC) values. The best fitted model were specified as ARFIMA (2,0.989,0) and ARFURIMA (1,1.069,0). Having compared the residuals analysis of the two models, we conclude...
It is well known that many countries around the world depend on the US as their major trade partn... more It is well known that many countries around the world depend on the US as their major trade partner. As a result, if something does happen to US economy it surely will affect the economy of all these countries. In this study, we investigate the relationship between the US and four Asian emerging stock markets namely Hong Kong, India, South Korea and Malaysia using monthly data between 1996 and 2008. In order to model the relationships, two approaches are used. They are linear Vector Autoregressive (VAR) model and nonlinear Markov Switching Vector Autoregressive (MS-VAR) model. In general we found that the two models manage to explore the possibility of relationship between all the stock markets. Nevertheless, MS-VAR model provide more insight on when all this relationship occurred. In addition, the result also indicates that the MS-VAR model fitted the data well than the linear VAR model.
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND TECHNOLOGY 2020 (MATHTECH 2020): Sustainable Development of Mathematics & Mathematics in Sustainability Revolution
Communications in Statistics - Simulation and Computation, 2012
In this article, we present the problem of selecting a good stochastic system with high probabili... more In this article, we present the problem of selecting a good stochastic system with high probability and minimum total simulation cost when the number of alternatives is very large. We propose a sequential approach that starts with the Ordinal Optimization procedure to ...
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND TECHNOLOGY 2018 (MATHTECH2018): Innovative Technologies for Mathematics & Mathematics for Technological Innovation
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND TECHNOLOGY 2018 (MATHTECH2018): Innovative Technologies for Mathematics & Mathematics for Technological Innovation
Malaysian Journal of Fundamental and Applied Sciences
The present study investigates the causal relationship between ASEAN seven member countries elect... more The present study investigates the causal relationship between ASEAN seven member countries electricity consumption (EC) and some determinants such as gross domestic product (GDP), exports (EXP) and carbon dioxide emission (CO2) using vector autoregressive (VAR) framework via vector error correction (VEC) model for the period from 1980-2015. The findings show that the effect of the chosen determinants is different among the seven countries. Within the sample period, by utilizing Granger causality test, out of the seven countries, only four revealed either unidirectional or bidirectional causality running from EC to the three determinants, GDP, EXP and CO2. Whereas, thru forecast error variance decomposition (FEVD), forecasting beyond the sample period uncovered a shock to EC will also spread to GDP, EXP and CO2. The present study suggests that ASEAN should take note in designing their electricity policy, since electricity affect and be affected by other factors. In addition, ASEAN a...
Statistical selection approaches are used to select the best stochastic system from a finite set ... more Statistical selection approaches are used to select the best stochastic system from a finite set of alternatives. The best system will be the system with minimum or maximum performance measure. We consider the problem of selecting the best system when the number of alternative systems is huge. Three-stage and Four-stage selection approaches are proposed to solve this problem. The main strategy in these two selection approaches involves a combination method of cardinal and ordinal optimization. Ordinal optimization procedure is used to reduce the number of systems in the search space such that to be appropriate for cardinal optimization procedures. Three-stage selection approach consists three procedures; ordinal optimization, subset selection and indifference-zone. While, four-stage selection approach consists four procedures; ordinal optimization, optimal computing budget allocation, subset selection and indifference-zone. In this paper, we compare the performance between the two s...
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Papers by ROSMANJAWATI ABDUL RAHMAN