An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction Problem
The financial industry has been becoming more and more dependent on advanced computing technologies in order to maintain competitiveness in a global economy. Hence, the stock price prediction problem using data mining techniques is one of the most important issues in finance. This field has attracte...
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| Format: | Article |
| Language: | English |
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Politeknik Negeri Padang
2017-04-01
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| Series: | JOIV: International Journal on Informatics Visualization |
| Subjects: | |
| Online Access: | http://joiv.org/index.php/joiv/article/view/20 |
| _version_ | 1819231376505831424 |
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| author | Thanh Tung Khuat My Hanh Le |
| author_facet | Thanh Tung Khuat My Hanh Le |
| author_sort | Thanh Tung Khuat |
| collection | DOAJ |
| description | The financial industry has been becoming more and more dependent on advanced computing technologies in order to maintain competitiveness in a global economy. Hence, the stock price prediction problem using data mining techniques is one of the most important issues in finance. This field has attracted great scientific interest and has become a crucial research area to provide a more precise prediction process. Fuzzy logic (FL) and Artificial Neural Network (ANN) present an exciting and promising technique with a wide scope for the applications of prediction. There is a growing interest in both fields of fuzzy logic computing and the financial world in the use of fuzzy logic to predict future changes in prices of stocks, exchange rates, commodities, and other financial time series. Fuzzy logic provides a way to draw definite conclusions from vague, ambiguous or imprecise information. Artificial Neural Network is one of data mining techniques being widely accepted in the business area due to its ability to learn and detect relationships among nonlinear variables. The ANN outperforms statistical regression models and also allows deeper analysis of large data sets, especially those that have the tendency to fluctuate within a short of time period. In this paper, we investigate the ability of Fuzzy logic and multilayer perceptron (MLP), which is a kind of the ANN, to tackle the financial time series stock forecasting problem. The proposed approaches were tested on the historical price data collected from Yahoo Finance with different companies. Furthermore, the comparison between those techniques is performed to examine their effectiveness. |
| first_indexed | 2024-12-23T11:43:59Z |
| format | Article |
| id | doaj.art-51253cbd64354341ba392280cdef133a |
| institution | Directory Open Access Journal |
| issn | 2549-9610 2549-9904 |
| language | English |
| last_indexed | 2024-12-23T11:43:59Z |
| publishDate | 2017-04-01 |
| publisher | Politeknik Negeri Padang |
| record_format | Article |
| series | JOIV: International Journal on Informatics Visualization |
| spelling | doaj.art-51253cbd64354341ba392280cdef133a2022-12-21T17:48:24ZengPoliteknik Negeri PadangJOIV: International Journal on Informatics Visualization2549-96102549-99042017-04-0112404910.30630/joiv.1.2.209An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction ProblemThanh Tung Khuat0My Hanh Le1University of Science and Technology - The University of Danang, VietnamUniversity of Science and Technology - The University of Danang, VietnamThe financial industry has been becoming more and more dependent on advanced computing technologies in order to maintain competitiveness in a global economy. Hence, the stock price prediction problem using data mining techniques is one of the most important issues in finance. This field has attracted great scientific interest and has become a crucial research area to provide a more precise prediction process. Fuzzy logic (FL) and Artificial Neural Network (ANN) present an exciting and promising technique with a wide scope for the applications of prediction. There is a growing interest in both fields of fuzzy logic computing and the financial world in the use of fuzzy logic to predict future changes in prices of stocks, exchange rates, commodities, and other financial time series. Fuzzy logic provides a way to draw definite conclusions from vague, ambiguous or imprecise information. Artificial Neural Network is one of data mining techniques being widely accepted in the business area due to its ability to learn and detect relationships among nonlinear variables. The ANN outperforms statistical regression models and also allows deeper analysis of large data sets, especially those that have the tendency to fluctuate within a short of time period. In this paper, we investigate the ability of Fuzzy logic and multilayer perceptron (MLP), which is a kind of the ANN, to tackle the financial time series stock forecasting problem. The proposed approaches were tested on the historical price data collected from Yahoo Finance with different companies. Furthermore, the comparison between those techniques is performed to examine their effectiveness.http://joiv.org/index.php/joiv/article/view/20Fuzzy LogicFireworks algorithmBack-propagation algorithmstock price forecastingMultilayer Perceptron Neural NetworkWavelet transform. |
| spellingShingle | Thanh Tung Khuat My Hanh Le An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction Problem JOIV: International Journal on Informatics Visualization Fuzzy Logic Fireworks algorithm Back-propagation algorithm stock price forecasting Multilayer Perceptron Neural Network Wavelet transform. |
| title | An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction Problem |
| title_full | An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction Problem |
| title_fullStr | An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction Problem |
| title_full_unstemmed | An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction Problem |
| title_short | An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction Problem |
| title_sort | application of artificial neural networks and fuzzy logic on the stock price prediction problem |
| topic | Fuzzy Logic Fireworks algorithm Back-propagation algorithm stock price forecasting Multilayer Perceptron Neural Network Wavelet transform. |
| url | http://joiv.org/index.php/joiv/article/view/20 |
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