Soft computing and bioinspired computing techniques for stock market prediction-a comprehensive survey


  • Dr S. Kumar Chandar Associate Professor, Department of Management Studies, Christ Deemed to be UniversityHosur Road, Bengaluru, Karnataka, India - 560029





Stock Market Prediction (SMP) is one of the most important and hottest topics in business and finance. The main goal of SMP is to develop an efficient technique to predict stock values and achieves accurate results with minimum number of input data. This


Stock Market Prediction (SMP) is one of the most important and hottest topics in business and finance. The main goal of SMP is to develop an efficient technique to predict stock values and achieves accurate results with minimum number of input data. This research paper reviews currently available SMP techniques based on soft computing and bio inspired computing algorithms. Many issues in-volved in the SMP are identified and different techniques are studied along with their merits and demerits to find the most suitable one. This paper also analyses the performance of various techniques with respect to some metrics including MSE, RMSE, MAD, MAPE, AAE and Hit ratio. The reviewed papers are classified in terms of number of input variables, prediction method and evaluation parame-ters used. A tabular representation of all the SMP techniques is presented to facilitate the future comparison. From the reviewed paper, it is noticed that the integration of soft computing with the bio inspired algorithms has the potential to predict the stock market index with high accuracy and achieves best result than soft computing method alone.




[1] Kurhe A.B., Satonkar S.S., Khanale P.B. and Shinde Ashok (2011),†Soft Computing and its Applicationsâ€, Bioinfo Soft Computing 1(1), pp-05-07.

[2] Antony Arul Raj and Sumathi P, (2016),†A Brief Study on Bio - Organism Behavior Inspired Computing Techniques and It’s Applicationsâ€, International Journal of Innovative Research in Computer and Communication Engineering, 4(10), pp.17436-17444.

[3] Binitha S, Siva Sathya S (2012), "A Survey of Bio inspired Optimization Algorithms", International Journal of Soft Computing and Engineering, 2(2).

[4] Jianjun Ni, Liuying Wu, Xinnan Fan, and Simon X. Yang, (2015), "Bioinspired Intelligent Algorithm and Its Applications for Mobile Robot Control: A Survey", Computational Intelligence and Neuroscience,

[5] Kopperundevi S (2015),†Prediction of future stock prices exploiting machine learning techniquesâ€, Phd thesis.

[6] Mritunjay Sharma (2014),â€Survey on stock market prediction and performance analysisâ€, International journal of Advanced research in computer engineering and technology, 3 (1), pp.131-135.

[7] Chaigusin, S. (2011),â€An investigation into the use of neural networks for the prediction of the stock exchange of Thailandâ€, Doctor of Information Technology, thesis.

[8] Sriram lakshminarayanan(2005)â€An integrated stock market forecasting model using neural networksâ€MSc thesis.

[9] Adebiyi Ayodele A., Ayo Charles K., Adebiyi Marion O., and Otokiti Sunday O,(2012)†Stock Price Prediction using Neural Network with Hybridized Market Indicatorsâ€, Journal of Emerging Trends in Computing and Information Sciences, 3(1),1-9.

[10] Phichhang Ou and Hengshan Wang, (2009),†Prediction of Stock Market Index Movement by Ten Data Mining Techniquesâ€, Modern Applied Science, 3(12), 28-42.

[11] Esmaeil Hadavandi, (2010),†Developing an Evolutionary Neural Network Model for Stock Index Forecastingâ€, Conference Paper in Communications in Computer and Information Science, · Source: DBLP, 407-415.

[12] Wen chen and Yixiang Tian, (2016),â€Short-term prediction of Stock index Based on EMD and SVMsâ€,International journal of multimedia and ubiquitous Enineering,11(8),1-12.

[13] Chandra Shakher Tyagi,Harpreet Singh,Varun Bhardwaj,Kritika Nagpal, (2016),†Applications of Artificial Neural Network in Forecasting of Stock Market Indexâ€, International Journal of Recent Research in Mathematics Computer Science and Information Technology ,3(1),28-38.

[14] Osman Hegazy, Omar S. Soliman and Mustafa Abdul Salam, (2015),†Comparative Study between FPA, BA, MCS, ABC, and PSO Algorithms in Training and Optimizing of LS-SVM for Stock Market Predictionâ€, International Journal of Advanced Computer Research, 5(18), 35-45.

[15] Ping-Feng Pai, Chih-Sheng Lin,(2005),†A hybrid ARIMA and support vector machines model in stock price forecastingâ€, The International Journal of Management, 33,497 – 505.

[16] Liu Dao-wen, (2012),†Modelling for Nonlinear Series Prediction based on the Support Vector Machine Theoryâ€, National Conference on Information Technology and Computer Science (CITCS 2012), 922-925.

[17] Jheng-Long Wu , Chen-Chi Su , Liang-Chih Yu and Pei-Chann Chang,(2012),†Stock Price Predication using Combinational Features from Sentimental Analysis of Stock News and Technical Analysis of Trading Informationâ€, DOI: 10.7763/IPEDR. 2012. V55. 8, 39-430.

[18] Xiaowei Lin, Zehong Yang and Yixu Song, (2009),†Short-term stock price prediction based on echo state networksâ€, Expert Systems with Applications, 36, 7313–7317.

[19] Mustain Billah, Sajjad Waheed and Abu Hanifa, (2015),†Predicting Closing Stock Price using Artificial Neural Network and Adaptive Neuro Fuzzy Inference System (ANFIS): The Case of the Dhaka Stock Exchangeâ€, International Journal of Computer Applications, 129 (11), 1-5.

[20] Rajendran Sugumar, Alwar Rengarajan and Chinnappan Jayakumar,(2014),†A technique to stock market prediction using fuzzy clustering and artificial neural networksâ€, Computing and Informatics, 33, 992-1024.

[21] Agrawal, S., Jindal, M., Pillai, G. N.(2010), “Momentum Analysis based Stock Market Prediction using Adaptive Neuro-Fuzzy Inference System (ANFIS)â€, Proceedings of the International Multi Conference of Engineers and Computer Scientists, Hong Kong, 1,March 17 -19, 2010.

[22] Choudhry, R., Garg, K (2008) “A Hybrid Machine Learning System for Stock Market Forecastingâ€, World Academy of Science, Engineering and Technology, Vol. 15,315-318.

[23] Lokesh; Pandey, Anvita; Srivastava, Saakshi; and Darbari, Manuj (2011) "A Hybrid Machine Learning System for Stock Market Forecasting," Journal of International Technology and Information Management, 20 (1), Article 3. Available at:

[24] Myungsook Maha Abdelrasoul,(2007),†Investigation of Some Technical Indexes in Stock Forecasting Using Neural Networksâ€, International Journal of Computer, Electrical, Automation, Control and Information Engineering,1(5),1438-1442.

[25] Sureshkumar. K.K and Elango, N.M (2012),†Performance Analysis of Stock Price Prediction using Artificial Neural Networkâ€, Global Journal of Computer Science and Technology, 12(1).

[26] Tsung-Jung Hsieh, Hsiao-Fen Hsiao and Wei-Chang Yeh (2011),†Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithmâ€, 11 (2), pp.2510-2525.

[27] Amit Ganatr and Kosta.,Y.P,(2012),†Spiking Back Propagation Multilayer Neural Network Design for Predicting Unpredictable Stock Market Prices with Time Series Analysisâ€, International Journal of Computer Theory and Engineering,2(6),963-971.

[28] Amin Hedayati Moghaddam, Moein Hedayati Moghaddam and Morteza Esfandyari,(2016),†Stock market index prediction using artificial neural networkâ€, Journal of Economics, Finance and Administrative Science,21,89–93.

[29] Yuehui Chen, Ajith Abraham, Ju Yang, and Bo Yang,(2005),†Hybrid Methods for Stock Index Modelingâ€, Springer-Verlag Berlin Heidelberg, 1067–1070,

[30] Md. Rafiul Hassan and Baikunth Nath, (2005),†Stock Market Forecasting Using Hidden Markov Model: A New Approachâ€, Proceedings of the 2005 fifth International Conference on Intelligent Systems Design and Applications (ISDA’05),

[31] Ajith Abraham , Baikunth Nath and Mahanti,(2001),†Hybrid Intelligent Systems for Stock Market Analysisâ€, , In proceedings of International Conference on Computational Science - ICCS 2001, San Francisco, CA, USA337-345.

[32] Kazi Shah Nawaz Ripon,(2016),†Stock Market Forecast Using Bio-Inspired Computingâ€, 3rd IEEE International Conference on Control, Decision and Information Technologies (CoDIT’16), At Malta.

[33] Maha Abdelrasoul, Gamal Selim and Mohamed Waleed Fakhr,(2011),†Stock Market Trend Prediction Model for the Egyptian Stock Market Using Neural Networks and Fuzzy Logicâ€, Bio-Inspired Computing and Applications - 7th International Conference on Intelligent Computing, ICIC 2011, Zhengzhou,China, August 11-14.

[34] Essam El. Seidy, (2016),†A New Particle Swarm Optimization Based Stock Market Prediction Techniqueâ€, International Journal of Advanced Computer Science and Applications, 7 (4), 322-327.

[35] Savinderjit Kaur and Veenu Mangat, (2012) “Improved Accuracy of PSO and DE using Normalization: an Application to Stock Price Prediction,†International Journal of Advanced Computer Science and Applications,3 (9),197-205

[36] Tarek Aboueldahab and Mahumod Fakhreldin,(2011) “Prediction of Stock Market Indices using Hybrid Genetic Algorithm / Particle Swarm Optimization with Perturbation Term,†In proceeding of the International Conference on Swarm Intelligence, Cergy, France, June 14-15.

[37] Alaa Sheta, Hossam Faris and Mouhammd Alkasassbeh, (2013) “A Genetic Programming Model for S&P 500 Stock Market Prediction,†International Journal of Control and Automation, 6 (5), 303-314.

[38] Puspanjali Mohapatra, Alok Raj and Tapas Kumar Patra,(2012) “Indian Stock Market Prediction Using Differential Evolutionary Neural Network Model,†International Journal of Electronics Communication and Computer Technology, 2(4), 159-166.

[39] Hsuan-Ming Feng and Hsiang-Chai Chou, (2012), “Evolutionary Fuzzy Stock Prediction System Design and Its Application to The Taiwan Stock Index,†International Journal of Innovative Computing, Information and Control, 8(9), 6173-6190.

[40] Acheme David Ijegwa Vincent Olufunke Rebecca Folorunso Olusegun and Olusola Olasunkanmi Isaac, (2014),†A Predictive Stock Market Technical Analysis Using Fuzzy Logicâ€, Computer and Information Science, 7 (3), 1-17.

[41] George S. Atsalakis and Kimon P. Valavanis, (2009),†Forecasting stock market short-term trends using a neuro-fuzzy based methodologyâ€, Expert Systems with Applications, 36, 10696–10707.

[42] Ajith, A., Sajith, N., and Sarathchandran, P. P. (2003),â€Modelling chaotic behaviour of stock indices using Intelligent Paradigmsâ€, Neural, Parallel & Scientific Computations Archive, 11, 143–160.

[43] Armano, G., Marchesi, M., and Murru, A. (2004),†A hybrid genetic-neural architecture for stock indexes forecasting. Information Sciencesâ€, 170(1), 3–33.

[44] Atiya, A., Noha Talaat and Samir Shaheen, (1997),†An efficient stock market forecasting model using neural networksâ€,In Proceedings of the IEEE International Conference on Neural Networks.

[45] Ayob, M., Nasrudin, M. F., Omar, K., and Surip, M. (2001),â€The effects of returns function on individual stock price (KLSE) prediction model using neural networksâ€, In Proceedings of the International Conference on Artificial Intelligence, IC-AI 2001 (pp. 409–415).

[46] Baba, N., and Kozaki, M. (1992),â€An intelligent forecasting system of stock price using neural networksâ€, Proceedings of the IEEE International Joint Conference on Neural Networks, 371–377.

[47] Kumar Chandar S, Sumathi M and Sivanandam SN (2016),†Prediction of Stock Market Price using Hybrid of Wavelet Transform and Artificial Neural Networkâ€, Indian Journal of Science and Technology,9(8),PP.1-5.

[48] Baek, J., and Cho, S. (2001),â€Time to jump. Long rising pattern detection in KOSPI 200 future using an auto-associative neural networkâ€,ICONIP, Shanghai,china,160-165.

[49] Chen, A. S., Leung, M. T., and Daouk, H. (2001),†Application of neural networks to an emerging financial market: Forecasting and trading the Taiwan Stock Indexâ€,Computers and Operations Research, 30, 901–923.

[50] Chen, Y., Dong, X., and Zhao, Y. (2005),†Stock index modelling using EDA based local linear wavelet neural network. Proceedings of International Conference on Neural Networks and Brain, 1646–1650.

[51] Chen, Y., Abraham, A., Yang, J., and Yang, B. (2005),†Hybrid methods for stock index modelling. Proceedings of Fuzzy Systems and Knowledge Discoveryâ€, Second International Conference, 1067–1070.

[52] Dong, M., and Zhou, X. (2002),â€Exploring the fuzzy nature of technical patterns of U.S. stock marketâ€, Proceedings of Fuzzy System and Knowledge Discovery, 1,324–328.

[53] Zhang, Y.-Q., Akkaladevi, S., Vachtsevanos, G., and Lin, T. Y. (2002),†Granular neural web agents for stock prediction. Soft Computing 6 406–431.

[54] Zhang, D., Jiang, Q., and Li, X. (2004),†Application of neural networks in financial data miningâ€, Proceedings of International Conference on Computational Intelligence, 392–395.

[55] Xueshen Sui, Qinghua Hu, Daren Yu, Zongxia Xie and Zhongying Qi, (2007),â€A Hybrid Method for Forecasting Stock Market Trend Using Soft-Thresholding De-noise Model and SVMâ€, Springer-Verlag Berlin Heidelberg, 387-394.

[56] Swarnava Mitra and Atanu Das, (2009),†Security Index Forecasting Using Multi Step Ahead Wavelet Neural Network and Wavelet Garch A Comparative Studyâ€, Institute of Management Studies,4(2),17-21.

[57] Mahdi Pakdaman Naeini, Hamidreza Taremian and Homa Baradaran Hashemi, (2010),†Stock Market Value Prediction Using Neural Networksâ€, International Conference on Computer Information Systems and Industrial Management Applications, 132-136.

[58] Victor Devadoss,A and Antony Alphonnse Ligori,T,(2013),†Stock Prediction Using Artificial Neural Networksâ€, International Journal of Data Mining Techniques and Applications,2, 283-291.

[59] Yusuf Perwej and Asif Perwej, (2012),†Prediction of the Bombay Stock Exchange (BSE) Market Returns Using Artificial Neural Network and Genetic Algorithmâ€, Journal of Intelligent Learning Systems and Applications, 2012, 108-119.

[60] Mingyue Qiu and Yu Song, (2016),†Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Modelâ€, PLoS ONE 11(5): e0155133. Doi: 10.1371/journal. pone.0155133.

[61] Makridou, G., Atsalakis, G.S., Zopounidis, C. and Andriosopoulos, K. (2013) ‘Gold price forecasting with a neuro-fuzzy-based inference system’, Int. J. Financial Engineering and Risk Management, 1(1), pp. 35–54.

[62] Guo Z, Wang H, Yang J and Miller DJ, (2015),†A Stock Market Forecasting Model Combining TwoDirectional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Networkâ€, PLoS ONE 10(4): e0122385.

[63] Shipra Banik, A. F. M. Khodadad Khan, and Mohammad Anwer, (2014),†Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisionsâ€, Computational Intelligence and Neuroscience, Article ID 318524,

[64] Yonghui Dai, Dongmei Han,and Weihui Dai,(2014),†Modeling and Computing of Stock Index Forecasting Based on Neural Network and Markov Chainâ€, The Scientific World Journal , Article ID 124523,

[65] Guo Z, Wang H, Liu Q andYang J, (2014),â€A Feature Fusion Based Forecasting Model for Financial Time Seriesâ€, PLoS ONE 9(6): e101113. Doi: 10.1371/journal. pone.0101113.

[66] Jie Wang,Jun Wang, Wen Fang, and Hongli Niu,(2016),†Financial Time Series Prediction Using Elman Recurrent Random Neural Networksâ€, Computational Intelligence and Neuroscience Article ID 4742515,

[67] Hongli Niu and Jun Wang, (2014),†Financial time series prediction by a random data-time effective RBF neural networkâ€, Soft Computing, 18,497–508.

[68] Rout, A.K. et al.,(2015),†Forecasting financial time series using a low complexity recurrent neural network and evolutionary learning approachâ€, Journal of King Saud University – Computer and Information Scienc

[69] Ina Khandelwal, Ratnadip Adhikari and Ghanshyam Verma,(2016),†Time Series Forecasting using Hybrid ARIMA and ANN Models based on DWT Decompositionâ€, Procedia Computer Science 48, 173 – 179.

[70] Ritanjali Majhi , G. Panda, Babita Majhi and G. Sahoo,(2009),†Efficient prediction of stock market indices using adaptive bacterial foraging optimization (ABFO) and BFO based techniquesâ€, Expert Systems with Applications 36,10097–10104.

[71] Peter Zhang (2003),†Time series forecasting using a hybrid ARIMA and neural network modelâ€, Neurocomputing, 50,159 – 175

[72] Jatinder Kumar, Amandeep Kaur and Pammy Manchanda (2015),†Forecasting the Time Series Data Using ARIMA with Waveletâ€, Journal of Computer and Mathematical Sciences,6(8),430-438.

[73] Jatinder kumara and Mandeep kaur(2016),†Comparison of different wavelet-based statistical methods in banking sectorâ€,International Journal of Mathematical Archive-7(6),18-26.

[74] Rahib h. abiyev and , vasif hidayat abiyev(2012),†Differential evaluation learning of fuzzy wavelet neural networks for stock Price Predictionâ€, Journal of Information and Computing Science Vol. 7, No. 2, 121-130

[75] Uduak A. Umoh and Alfred A. Udosen (2014),â€Sugeno-Type Fuzzy Inference Model for Stock Price Predictionâ€, International Journal of Computer Applications, 103(3), 1-12.

[76] Chang, P.-C., & Liu, C.-H. (2006),†A TSK type fuzzy rule based system for stock price prediction, Expert Systems with Applications,

[77] Salim Lahmiri (2012),â€Wavelet transform, neural networks and the prediction of S&P price index: a comparative study of back propagation numerical algorithmsâ€, Business Intelligence Journal, 592,235-244.

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How to Cite

S. Kumar Chandar, D. (2018). Soft computing and bioinspired computing techniques for stock market prediction-a comprehensive survey. International Journal of Engineering & Technology, 7(3), 1836–1845.
Received 2018-06-27
Accepted 2018-07-19
Published 2018-08-22