Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model

Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model

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...

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Published in:International Journal on Advanced Science, Engineering and Information Technology
Main Author: Yassin I.M.; Abdul Khalid M.F.; Herman S.H.; Pasya I.; Ab Wahab N.; Awang Z.
Format: Article
Language:English
Published: Insight Society 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021071041&doi=10.18517%2fijaseit.7.3.1363&partnerID=40&md5=6115a8ec3c9bcf394aa4c8d5882772be
id 2-s2.0-85021071041
spelling 2-s2.0-85021071041
Yassin I.M.; Abdul Khalid M.F.; Herman S.H.; Pasya I.; Ab Wahab N.; Awang Z.
Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model
2017
International Journal on Advanced Science, Engineering and Information Technology
7
3
10.18517/ijaseit.7.3.1363
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021071041&doi=10.18517%2fijaseit.7.3.1363&partnerID=40&md5=6115a8ec3c9bcf394aa4c8d5882772be
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 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 validate the model. Results demonstrate the predictive ability of the model while producing Gaussian residuals (indicating the validity of the model).
Insight Society
20885334
English
Article
All Open Access; Hybrid Gold Open Access
author Yassin I.M.; Abdul Khalid M.F.; Herman S.H.; Pasya I.; Ab Wahab N.; Awang Z.
spellingShingle Yassin I.M.; Abdul Khalid M.F.; Herman S.H.; Pasya I.; Ab Wahab N.; Awang Z.
Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model
author_facet Yassin I.M.; Abdul Khalid M.F.; Herman S.H.; Pasya I.; Ab Wahab N.; Awang Z.
author_sort Yassin I.M.; Abdul Khalid M.F.; Herman S.H.; Pasya I.; Ab Wahab N.; Awang Z.
title Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model
title_short Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model
title_full Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model
title_fullStr Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model
title_full_unstemmed Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model
title_sort Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) stock forecasting model
publishDate 2017
container_title International Journal on Advanced Science, Engineering and Information Technology
container_volume 7
container_issue 3
doi_str_mv 10.18517/ijaseit.7.3.1363
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021071041&doi=10.18517%2fijaseit.7.3.1363&partnerID=40&md5=6115a8ec3c9bcf394aa4c8d5882772be
description 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 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 validate the model. Results demonstrate the predictive ability of the model while producing Gaussian residuals (indicating the validity of the model).
publisher Insight Society
issn 20885334
language English
format Article
accesstype All Open Access; Hybrid Gold Open Access
record_format scopus
collection Scopus
_version_ 1809677909230616576

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