Alavi, S. E., Sinaei, H. & Afsharirad, E. (2015). Predict the trend of stock prices using machine learning techniques, International Academic Journal of Economics, 2 (12), 1-11.
Alpaiden, E. (2004). Introduction to machine learning. First Edition. The MIT Press Cambridge Massuchusetts, London, England.
Chen, K.-Y., & Ho, C.-H. (2005). An improved support vector regression modeling for Taiwan Stock Exchange market weighted index forecasting. International Conference on Neural Networks and Brain. Beijing, China.
Dorodi, D., & Abrahimi, S. B. (2017). Presenting a new hybrid method for predicting the Stock Exchange price index. Financial Research Journal, 18 (4), 612-632. (in Persian)
Edwards, R. D., Magee, J. & Bassetti, W. C. (2007). Technical analysis of stock trends: CRC Press.
Enke, D., Thawornwong, S. (2005). The use of data mining and neural networks for forecasting stock market returns. Expert systems with Applications, 29 (4), 927-940.
Fakhari, H. Valipour Khatir, M. & Mousavi, M. (2017). Investigating Performance of Bayesian and Levenberg-Marquardt Neural Network in Comparison Classical Models in Stock Price Forecasting. Financial Research Journal, 19 (2), 229-318. (in Persian)
Ford, N., Batchelor, B., & Wilkins, B. R. (1970). A learning scheme for the Nearest Neighbor Classifier. Information Sciences, 2 (2), 139-157.
Hassan, M. R., Nath, B., & Kirley, M. (2007). A fusion model of HMM, ANN and GA for stock market forecasting. Expert systems with Applications, 33 (1), 171-180.
Hafezi, R., Shahrabi, J., & Hadavandi, E. (2015). A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price. Applied Soft Computing, 29, 196-210.
Kim, E., Kim, W., & Lee, Y. (2003). Combination of multiple classifiers for the customer's purchase behavior prediction. Decision Support Systems, 34 (2), 167-175.
Kuo, R. J., Chen, C., & Hwang, Y. (2001). An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network. Fuzzy sets and systems, 118 (1), 21-45.
Liu, C., Wang, J., Xiao, D., & Liang, Q. (2016). Forecasting S&P 500 Stock Index Using Statistical Learning Models. Open Journal of Statistics, 6 (06), 1067.
Mitchel, T. M. (1997). Machine Learning. First Edition, McGraw Hill Science.
Nabizade, A., Gharehbaghi, H. & Behzadi, A. (2016).Index Tracking Optimization under down Side Beta and Evolutionary Based Algorithms. Financial Research Journal, 19 (2), 319-340. (in Persian)
Patel, J., Shah, S., Thakkar, P., & Kotecha, K. (2015). Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques. Expert systems with Applications, 42 (1), 259-268.
Saad, E. W., Prokhorov, D. V., & Wunsch, D. C. (1998). Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks. IEEE Transactions on neural networks, 9 (6), 1456-1470.
Schöneburg, E. (1990). Stock price prediction using neural networks: A project report. Neurocomputing, 2 (1), 17-27.
Tsai, C.-F., Lin, Y.-C., Yen, D. C., & Chen, Y.-M. (2011). Predicting stock returns by classifier ensembles. Applied Soft Computing, 11 (2), 2452-2459.
Vapnik, V. (2013). The nature of statistical learning theory: Springer science & business media.
Xu, X., Zhou, C., & Wang, Z. (2009). Credit scoring algorithm based on link analysis ranking with support vector machine. Expert systems with Applications, 36 (2), 2625-2632.
Yang, H., Chan, L., & King, I. (2002). Support vector machine regression for volatile stock market prediction. International Conference on Intelligent Data Engineering and Automated Learning. Manchester, UK.