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Multi-Layer Perceptron (MLP)-Based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) Stock Forecasting Model

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@article{IJASEIT1363,
   author = {I. M. Yassin and M. F. Abdul Khalid and S. H. Herman and I. Pasya and N. Ab Wahab and Z. Awang},
   title = {Multi-Layer Perceptron (MLP)-Based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) Stock Forecasting Model},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {7},
   number = {3},
   year = {2017},
   pages = {1098--1103},
   keywords = {system identification; stock market forecasting; nonlinear auto-regressive with exogenous inputs (NARX), multi-layer perceptron (MLP)},
   abstract = {The prediction of stocks in the stock market is important in investment as it would help the investor to time buy and sell transactions to maximize profits. In this paper, a Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) model was used to predict the prices of the Apple Inc. weekly stock prices over a time horizon of 1995 to 2013. The NARX model belongs is a system identification model that constructs a mathematical model from the dynamic input/output readings of the system, and predicts the future behaviour of the system based on the constructed mathematical model. The One Step Ahead (OSA) and correlation tests were used to test validate the model. Results demonstrate the predictive ability of the model while producing Gaussian residuals (indicating the validity of the model).},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1363},
   doi = {10.18517/ijaseit.7.3.1363}
}

EndNote

%A Yassin, I. M.
%A Abdul Khalid, M. F.
%A Herman, S. H.
%A Pasya, I.
%A Wahab, N. Ab
%A Awang, Z.
%D 2017
%T Multi-Layer Perceptron (MLP)-Based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) Stock Forecasting Model
%B 2017
%9 system identification; stock market forecasting; nonlinear auto-regressive with exogenous inputs (NARX), multi-layer perceptron (MLP)
%! Multi-Layer Perceptron (MLP)-Based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) Stock Forecasting Model
%K system identification; stock market forecasting; nonlinear auto-regressive with exogenous inputs (NARX), multi-layer perceptron (MLP)
%X The prediction of stocks in the stock market is important in investment as it would help the investor to time buy and sell transactions to maximize profits. In this paper, a Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) model was used to predict the prices of the Apple Inc. weekly stock prices over a time horizon of 1995 to 2013. The NARX model belongs is a system identification model that constructs a mathematical model from the dynamic input/output readings of the system, and predicts the future behaviour of the system based on the constructed mathematical model. The One Step Ahead (OSA) and correlation tests were used to test validate the model. Results demonstrate the predictive ability of the model while producing Gaussian residuals (indicating the validity of the model).
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1363
%R doi:10.18517/ijaseit.7.3.1363
%J International Journal on Advanced Science, Engineering and Information Technology
%V 7
%N 3
%@ 2088-5334

IEEE

I. M. Yassin,M. F. Abdul Khalid,S. H. Herman,I. Pasya,N. Ab Wahab and Z. Awang,"Multi-Layer Perceptron (MLP)-Based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) Stock Forecasting Model," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 3, pp. 1098-1103, 2017. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.7.3.1363.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Yassin, I. M.
AU  - Abdul Khalid, M. F.
AU  - Herman, S. H.
AU  - Pasya, I.
AU  - Wahab, N. Ab
AU  - Awang, Z.
PY  - 2017
TI  - Multi-Layer Perceptron (MLP)-Based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) Stock Forecasting Model
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 7 (2017) No. 3
Y2  - 2017
SP  - 1098
EP  - 1103
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - system identification; stock market forecasting; nonlinear auto-regressive with exogenous inputs (NARX), multi-layer perceptron (MLP)
N2  - The prediction of stocks in the stock market is important in investment as it would help the investor to time buy and sell transactions to maximize profits. In this paper, a Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) model was used to predict the prices of the Apple Inc. weekly stock prices over a time horizon of 1995 to 2013. The NARX model belongs is a system identification model that constructs a mathematical model from the dynamic input/output readings of the system, and predicts the future behaviour of the system based on the constructed mathematical model. The One Step Ahead (OSA) and correlation tests were used to test validate the model. Results demonstrate the predictive ability of the model while producing Gaussian residuals (indicating the validity of the model).
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1363
DO  - 10.18517/ijaseit.7.3.1363

RefWorks

RT Journal Article
ID 1363
A1 Yassin, I. M.
A1 Abdul Khalid, M. F.
A1 Herman, S. H.
A1 Pasya, I.
A1 Wahab, N. Ab
A1 Awang, Z.
T1 Multi-Layer Perceptron (MLP)-Based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) Stock Forecasting Model
JF International Journal on Advanced Science, Engineering and Information Technology
VO 7
IS 3
YR 2017
SP 1098
OP 1103
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 system identification; stock market forecasting; nonlinear auto-regressive with exogenous inputs (NARX), multi-layer perceptron (MLP)
AB The prediction of stocks in the stock market is important in investment as it would help the investor to time buy and sell transactions to maximize profits. In this paper, a Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) model was used to predict the prices of the Apple Inc. weekly stock prices over a time horizon of 1995 to 2013. The NARX model belongs is a system identification model that constructs a mathematical model from the dynamic input/output readings of the system, and predicts the future behaviour of the system based on the constructed mathematical model. The One Step Ahead (OSA) and correlation tests were used to test validate the model. Results demonstrate the predictive ability of the model while producing Gaussian residuals (indicating the validity of the model).
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1363
DO  - 10.18517/ijaseit.7.3.1363