A PSO based integrated functional link net and interval type-2 fuzzy logic system for predicting stock market indices
This paper presents an integrated functional link interval type-2 fuzzy neural system (FLIT2FNS) for predicting the stock market indices. The hybrid model uses a TSK (Takagi–Sugano–Kang) type fuzzy rule base that employs type-2 fuzzy sets in the antecedent parts and the outputs from the Functional L...
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| Published in: | Applied soft computing Vol. 12; no. 2; pp. 931 - 941 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
01.02.2012
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| ISSN: | 1568-4946, 1872-9681 |
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| Abstract | This paper presents an integrated functional link interval type-2 fuzzy neural system (FLIT2FNS) for predicting the stock market indices. The hybrid model uses a TSK (Takagi–Sugano–Kang) type fuzzy rule base that employs type-2 fuzzy sets in the antecedent parts and the outputs from the Functional Link Artificial Neural Network (FLANN) in the consequent parts. Two other approaches, namely the integrated FLANN and type-1 fuzzy logic system and Local Linear Wavelet Neural Network (LLWNN) are also presented for a comparative study. Backpropagation and particle swarm optimization (PSO) learning algorithms have been used independently to optimize the parameters of all the forecasting models. To test the model performance, three well known stock market indices like the Standard's & Poor's 500 (S&P 500), Bombay stock exchange (BSE), and Dow Jones industrial average (DJIA) are used. The mean absolute percentage error (MAPE) and root mean square error (RMSE) are used to find out the performance of all the three models. Finally, it is observed that out of three methods, FLIT2FNS performs the best irrespective of the time horizons spanning from 1 day to 1 month. |
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| AbstractList | This paper presents an integrated functional link interval type-2 fuzzy neural system (FLIT2FNS) for predicting the stock market indices. The hybrid model uses a TSK (Takagi–Sugano–Kang) type fuzzy rule base that employs type-2 fuzzy sets in the antecedent parts and the outputs from the Functional Link Artificial Neural Network (FLANN) in the consequent parts. Two other approaches, namely the integrated FLANN and type-1 fuzzy logic system and Local Linear Wavelet Neural Network (LLWNN) are also presented for a comparative study. Backpropagation and particle swarm optimization (PSO) learning algorithms have been used independently to optimize the parameters of all the forecasting models. To test the model performance, three well known stock market indices like the Standard's & Poor's 500 (S&P 500), Bombay stock exchange (BSE), and Dow Jones industrial average (DJIA) are used. The mean absolute percentage error (MAPE) and root mean square error (RMSE) are used to find out the performance of all the three models. Finally, it is observed that out of three methods, FLIT2FNS performs the best irrespective of the time horizons spanning from 1 day to 1 month. |
| Author | Chakravarty, S. Dash, P.K. |
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| Cites_doi | 10.1177/097265270600500305 10.1007/s005210200021 10.3923/itj.2005.289.292 10.1016/j.neucom.2005.02.006 10.1109/TFUZZ.2006.889765 10.1016/j.eswa.2008.07.006 10.1109/91.873577 10.1109/TFUZZ.2008.925907 10.1109/TFUZZ.2006.879986 10.1016/j.eswa.2007.09.034 10.1016/S0020-0255(00)00068-2 10.1016/j.eswa.2008.08.008 |
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| Keywords | Functional Link Artificial Neural Network Interval Type-2FLS Backpropagation learning algorithm Particle swarm optimization Fuzzy logic system |
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| References | Zhang, Wang, Liang, Che (bib0150) 2008 Castro, Castillo, Melin, Rodriguez-Diaz (bib0110) 2007 Ozge, Turksen (bib0120) 2007; 15 Dutta, Jha, Laha, Mohan (bib0025) 2006; 5 Chodhury, Garg (bib0030) 2008 J.C. Roxana, V.M.B.R. Marley, T. Ricardo, Hierarchical type-2 neuro-fuzzy BSP model, in: Eighth International Conference on Hybrid Intelligent Systems, IEEE, (2008), 978-0-7695-3326, DOI 10.1109/113. Liang, Mendel (bib0105) 2000; 8 H. Fu-Yuan, Integration of an improved particle swarm optimization algorithm and fuzzy neural network for Shanghai stock market prediction, in: Workshop on Power Electronics and Intelligent Transportation System, IEEE, (2008), 978-07695-3342, 242–247. Huang (bib0080) 2008 Majhi, Panda, Sahoo (bib0050) 2009; 36 Begian, Melek, Mendel (bib0130) 2008 Majhi, Shalabi, Fathi (bib0045) 2005; 4 Fazel Zarandi, Rezaee, Turksen, Neshat (bib0115) 2009; 36 Sexton, Gupta (bib0160) 2000; 129 Stock Exchange – Stock Exchange Evolution Larson&Holz.htm. Chang, Fan, Chen (bib0060) 2007 Kuo, Horng, Chen, Run, Kao, Chen, Lai, Lin (bib0085) 2009 Eberhart, Kennedy (bib0145) 1995 Mendel, John, Liu (bib0125) 2006; 14 Castillo, Melin, Kacprzyk, Pedrycz (bib0100) 2007 George, Valavanis (bib0090) 2009; 36 Chokri (bib0075) 2006 Jang, Sun, Mizutani (bib0135) 2005 V. Kodogiannis, A. Lolis, Forecasting Financial Time Series Neural Network and Fuzzy System Based Technique, Springer-Verlag, Neural Computing & Applications 11 (2002) 90–102. Juang, Tsao (bib0140) 2008; 16 Yu, Zhang (bib0070) 2005; 35 Yu, Wang, Keung (bib0020) 2005 Cheng, Chen, Teoh (bib0065) 2007 Chen, Dong, Zhao (bib0040) 2005 Abdoh, Jouhare (bib0005) 1996; 13 Ravichandran, Thirunavukarasu, Nallaswamy, Babu (bib0010) 2007; 3 Y. Chen, B. Yang, J. Dong, Time series prediction using a local linear wavelet neural network, Neurocomputing, Elsevier 69 (2006) 449–465 Eberhart (10.1016/j.asoc.2011.09.013_bib0145) 1995 Begian (10.1016/j.asoc.2011.09.013_bib0130) 2008 Liang (10.1016/j.asoc.2011.09.013_bib0105) 2000; 8 Sexton (10.1016/j.asoc.2011.09.013_bib0160) 2000; 129 Mendel (10.1016/j.asoc.2011.09.013_bib0125) 2006; 14 Chokri (10.1016/j.asoc.2011.09.013_bib0075) 2006 Ravichandran (10.1016/j.asoc.2011.09.013_bib0010) 2007; 3 Ozge (10.1016/j.asoc.2011.09.013_bib0120) 2007; 15 George (10.1016/j.asoc.2011.09.013_bib0090) 2009; 36 Juang (10.1016/j.asoc.2011.09.013_bib0140) 2008; 16 Majhi (10.1016/j.asoc.2011.09.013_bib0045) 2005; 4 Jang (10.1016/j.asoc.2011.09.013_bib0135) 2005 Yu (10.1016/j.asoc.2011.09.013_bib0020) 2005 Yu (10.1016/j.asoc.2011.09.013_bib0070) 2005; 35 Kuo (10.1016/j.asoc.2011.09.013_bib0085) 2009 Dutta (10.1016/j.asoc.2011.09.013_bib0025) 2006; 5 10.1016/j.asoc.2011.09.013_bib0015 Castro (10.1016/j.asoc.2011.09.013_bib0110) 2007 10.1016/j.asoc.2011.09.013_bib0035 Castillo (10.1016/j.asoc.2011.09.013_bib0100) 2007 10.1016/j.asoc.2011.09.013_bib0155 10.1016/j.asoc.2011.09.013_bib0055 Chen (10.1016/j.asoc.2011.09.013_bib0040) 2005 Majhi (10.1016/j.asoc.2011.09.013_bib0050) 2009; 36 Fazel Zarandi (10.1016/j.asoc.2011.09.013_bib0115) 2009; 36 Zhang (10.1016/j.asoc.2011.09.013_bib0150) 2008 Chang (10.1016/j.asoc.2011.09.013_bib0060) 2007 Huang (10.1016/j.asoc.2011.09.013_bib0080) 2008 Chodhury (10.1016/j.asoc.2011.09.013_bib0030) 2008 10.1016/j.asoc.2011.09.013_bib0095 Cheng (10.1016/j.asoc.2011.09.013_bib0065) 2007 Abdoh (10.1016/j.asoc.2011.09.013_bib0005) 1996; 13 |
| References_xml | – volume: 13 year: 1996 ident: bib0005 article-title: The investigation of efficiency of stock price index of T.S.E. publication-title: Journal of Financial Research – year: 2006 ident: bib0075 article-title: Neuro-fuzzy network based on extended Kalman filtering for financial time series publication-title: Proceeding of World Academy of Science, Engineering and Technology, vol. 15 – year: 2007 ident: bib0060 article-title: Financial time series data forecasting by wavelet and TSK fuzzy rule based system publication-title: Institute of Electrical and Electronics Engineers, Fourth International Conference on Fuzzy Systems and Knowledge Discovery – year: 2008 ident: bib0130 article-title: Parametric design of stable type-2 TSK fuzzy system publication-title: IEEE – year: 2007 ident: bib0110 article-title: Hybrid learning algorithm for interval type-2 fuzzy neural networks publication-title: International Conference on Granular Computing, IEEE – volume: 35 start-page: 244 year: 2005 end-page: 249 ident: bib0070 article-title: Evolutionary fuzzy neural networks for hybrid financial prediction publication-title: Institute of Electrical and Electronics Engineers Transaction on Systems Man and Cybernetics – reference: Y. Chen, B. Yang, J. Dong, Time series prediction using a local linear wavelet neural network, Neurocomputing, Elsevier 69 (2006) 449–465 – start-page: 1646 year: 2005 end-page: 1650 ident: bib0040 article-title: Stock index modeling using EDA based local linear wavelet neural network publication-title: IEEE, In Proceedings of International Conference on Neural Networks and Brain, vol. 3 – reference: V. Kodogiannis, A. Lolis, Forecasting Financial Time Series Neural Network and Fuzzy System Based Technique, Springer-Verlag, Neural Computing & Applications 11 (2002) 90–102. – start-page: 3022 year: 2008 end-page: 3027 ident: bib0150 article-title: Chaotic time series forecasting based on fuzzy adaptive PSO for feed forward neural network training publication-title: The 9th International Conference for Young Computer Scientists, IEEE – reference: Stock Exchange – Stock Exchange Evolution Larson&Holz.htm. – volume: 129 start-page: 45 year: 2000 end-page: 59 ident: bib0160 article-title: Comparative evaluation of genetic algorithm and backpropagation for training neural network publication-title: Information Sciences – year: 2007 ident: bib0100 article-title: Type-2 fuzzy logic: theory and application publication-title: International Conference on Granular Computing, IEEE – volume: 36 start-page: 139 year: 2009 end-page: 154 ident: bib0115 article-title: A type-2 fuzzy rule-based expert system model for stock price analysis publication-title: Expert Systems with Applications – volume: 14 year: 2006 ident: bib0125 article-title: Interval type 2 fuzzy logic systems made simple publication-title: IEEE Transaction on Fuzzy Systems – year: 2005 ident: bib0020 article-title: Mining Stock Market Tendency using GA-Based Support Vector Machine – volume: 36 start-page: 6800 year: 2009 end-page: 6808 ident: bib0050 article-title: Development and performance evaluation of FLANN based model for forecasting stock market publication-title: Expert Systems with Applications – volume: 36 start-page: 5932 year: 2009 end-page: 5941 ident: bib0090 article-title: Surveying stock market forecasting techniques – Part 11: soft computing methods publication-title: Expert Systems with Applications – reference: H. Fu-Yuan, Integration of an improved particle swarm optimization algorithm and fuzzy neural network for Shanghai stock market prediction, in: Workshop on Power Electronics and Intelligent Transportation System, IEEE, (2008), 978-07695-3342, 242–247. – year: 2008 ident: bib0080 article-title: Forecasting stock price using a genetic fuzzy neural network publication-title: International Conference on Computer Science and Information Technology – volume: 8 start-page: 535 year: 2000 end-page: 550 ident: bib0105 article-title: Interval type-2 fuzzy logic systems: theory and design publication-title: IEEE Transactions on Fuzzy Systems – volume: 4 start-page: 289 year: 2005 end-page: 292 ident: bib0045 article-title: FLANN based forecasting of S&P 500 index publication-title: Information Technology Journal – year: 1995 ident: bib0145 article-title: A new optimizer using particle swarm theory publication-title: Sixth International Symposium on Micro Machine and Human Science – volume: 5 start-page: 3 year: 2006 ident: bib0025 article-title: Artificial neural network models for forecasting stock price index in the bombay stock exchange publication-title: Journal of Emerging Market Finance – year: 2005 ident: bib0135 article-title: Neuro-Fuzzy and Soft Computing – year: 2007 ident: bib0065 article-title: Multiple-period modified fuzzy time series for forecasting TAIEX publication-title: Institute of Electrical and Electronics Engineers, Fourth International Conference on Fuzzy systems and Knowledge Discovery – volume: 3 start-page: 44 year: 2007 end-page: 54 ident: bib0010 article-title: Estimation on return on investment in share market through ANN publication-title: Journal of Theoretical and Applied Information Technology – year: 2008 ident: bib0030 article-title: A hybrid machine learning system for stock market forecasting publication-title: Proceeding of World Academy of Science, Engineering and Technology, vol. 29 – start-page: 1494 year: 2009 end-page: 1502 ident: bib0085 article-title: Forecasting TAIFEX based on fuzzy time series and particle swarm optimization publication-title: Expert System with Applications, Elsevier – volume: 16 start-page: 1411 year: 2008 end-page: 1424 ident: bib0140 article-title: A self-evolving interval type-2 fuzzy neural network with online structure and parameter learning publication-title: IEEE Transaction on Fuzzy Systems – volume: 15 start-page: 90 year: 2007 end-page: 106 ident: bib0120 article-title: Discrete interval type 2 fuzzy system models using uncertainty in learning parameters publication-title: IEEE Transaction on Fuzzy Systems – reference: J.C. Roxana, V.M.B.R. Marley, T. Ricardo, Hierarchical type-2 neuro-fuzzy BSP model, in: Eighth International Conference on Hybrid Intelligent Systems, IEEE, (2008), 978-0-7695-3326, DOI 10.1109/113. – volume: 5 start-page: 3 year: 2006 ident: 10.1016/j.asoc.2011.09.013_bib0025 article-title: Artificial neural network models for forecasting stock price index in the bombay stock exchange publication-title: Journal of Emerging Market Finance doi: 10.1177/097265270600500305 – ident: 10.1016/j.asoc.2011.09.013_bib0015 doi: 10.1007/s005210200021 – ident: 10.1016/j.asoc.2011.09.013_bib0055 – volume: 4 start-page: 289 issue: 3 year: 2005 ident: 10.1016/j.asoc.2011.09.013_bib0045 article-title: FLANN based forecasting of S&P 500 index publication-title: Information Technology Journal doi: 10.3923/itj.2005.289.292 – year: 2006 ident: 10.1016/j.asoc.2011.09.013_bib0075 article-title: Neuro-fuzzy network based on extended Kalman filtering for financial time series – ident: 10.1016/j.asoc.2011.09.013_bib0035 doi: 10.1016/j.neucom.2005.02.006 – year: 2007 ident: 10.1016/j.asoc.2011.09.013_bib0065 article-title: Multiple-period modified fuzzy time series for forecasting TAIEX – volume: 15 start-page: 90 issue: 1 year: 2007 ident: 10.1016/j.asoc.2011.09.013_bib0120 article-title: Discrete interval type 2 fuzzy system models using uncertainty in learning parameters publication-title: IEEE Transaction on Fuzzy Systems doi: 10.1109/TFUZZ.2006.889765 – year: 2005 ident: 10.1016/j.asoc.2011.09.013_bib0135 – volume: 13 issue: 11–12 year: 1996 ident: 10.1016/j.asoc.2011.09.013_bib0005 article-title: The investigation of efficiency of stock price index of T.S.E. publication-title: Journal of Financial Research – volume: 3 start-page: 44 year: 2007 ident: 10.1016/j.asoc.2011.09.013_bib0010 article-title: Estimation on return on investment in share market through ANN publication-title: Journal of Theoretical and Applied Information Technology – year: 2008 ident: 10.1016/j.asoc.2011.09.013_bib0030 article-title: A hybrid machine learning system for stock market forecasting – volume: 35 start-page: 244 issue: 2 year: 2005 ident: 10.1016/j.asoc.2011.09.013_bib0070 article-title: Evolutionary fuzzy neural networks for hybrid financial prediction publication-title: Institute of Electrical and Electronics Engineers Transaction on Systems Man and Cybernetics – volume: 36 start-page: 5932 year: 2009 ident: 10.1016/j.asoc.2011.09.013_bib0090 article-title: Surveying stock market forecasting techniques – Part 11: soft computing methods publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2008.07.006 – start-page: 1646 year: 2005 ident: 10.1016/j.asoc.2011.09.013_bib0040 article-title: Stock index modeling using EDA based local linear wavelet neural network – year: 1995 ident: 10.1016/j.asoc.2011.09.013_bib0145 article-title: A new optimizer using particle swarm theory – year: 2005 ident: 10.1016/j.asoc.2011.09.013_bib0020 – year: 2008 ident: 10.1016/j.asoc.2011.09.013_bib0130 article-title: Parametric design of stable type-2 TSK fuzzy system publication-title: IEEE – start-page: 1494 year: 2009 ident: 10.1016/j.asoc.2011.09.013_bib0085 article-title: Forecasting TAIFEX based on fuzzy time series and particle swarm optimization publication-title: Expert System with Applications, Elsevier – volume: 8 start-page: 535 issue: 5 year: 2000 ident: 10.1016/j.asoc.2011.09.013_bib0105 article-title: Interval type-2 fuzzy logic systems: theory and design publication-title: IEEE Transactions on Fuzzy Systems doi: 10.1109/91.873577 – ident: 10.1016/j.asoc.2011.09.013_bib0155 – year: 2008 ident: 10.1016/j.asoc.2011.09.013_bib0080 article-title: Forecasting stock price using a genetic fuzzy neural network – year: 2007 ident: 10.1016/j.asoc.2011.09.013_bib0100 article-title: Type-2 fuzzy logic: theory and application – volume: 16 start-page: 1411 issue: 6 year: 2008 ident: 10.1016/j.asoc.2011.09.013_bib0140 article-title: A self-evolving interval type-2 fuzzy neural network with online structure and parameter learning publication-title: IEEE Transaction on Fuzzy Systems doi: 10.1109/TFUZZ.2008.925907 – year: 2007 ident: 10.1016/j.asoc.2011.09.013_bib0060 article-title: Financial time series data forecasting by wavelet and TSK fuzzy rule based system – volume: 14 issue: 6 year: 2006 ident: 10.1016/j.asoc.2011.09.013_bib0125 article-title: Interval type 2 fuzzy logic systems made simple publication-title: IEEE Transaction on Fuzzy Systems doi: 10.1109/TFUZZ.2006.879986 – volume: 36 start-page: 139 year: 2009 ident: 10.1016/j.asoc.2011.09.013_bib0115 article-title: A type-2 fuzzy rule-based expert system model for stock price analysis publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2007.09.034 – ident: 10.1016/j.asoc.2011.09.013_bib0095 – year: 2007 ident: 10.1016/j.asoc.2011.09.013_bib0110 article-title: Hybrid learning algorithm for interval type-2 fuzzy neural networks – volume: 129 start-page: 45 year: 2000 ident: 10.1016/j.asoc.2011.09.013_bib0160 article-title: Comparative evaluation of genetic algorithm and backpropagation for training neural network publication-title: Information Sciences doi: 10.1016/S0020-0255(00)00068-2 – volume: 36 start-page: 6800 year: 2009 ident: 10.1016/j.asoc.2011.09.013_bib0050 article-title: Development and performance evaluation of FLANN based model for forecasting stock market publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2008.08.008 – start-page: 3022 year: 2008 ident: 10.1016/j.asoc.2011.09.013_bib0150 article-title: Chaotic time series forecasting based on fuzzy adaptive PSO for feed forward neural network training |
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| Snippet | This paper presents an integrated functional link interval type-2 fuzzy neural system (FLIT2FNS) for predicting the stock market indices. The hybrid model uses... |
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| SubjectTerms | Backpropagation learning algorithm Functional Link Artificial Neural Network Fuzzy logic system Interval Type-2FLS Particle swarm optimization |
| Title | A PSO based integrated functional link net and interval type-2 fuzzy logic system for predicting stock market indices |
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