STOCK MARKET TREND PREDICTION USING SUPPORT VECTOR MACHINES

The aim of the paper was to outline a trend prediction model for the BELEX15 stock market index of the Belgrade stock exchange based on Support Vector Machines (SVMs). The feature selection was carried out through the analysis of technical and macroeconomics indicators. In addition, the SVM method was compared with a "similar" one, the least squares support vector machines - LS-SVMs to analyze their classification precisions and complexity. The test results indicate that the SVMs outperform benchmarking models and are suitable for short-term stock market trend predictions.

[1]  Milos Bozic,et al.  Stock Market Trend Prediction Based on the LS-SVM Model Update Algorithm , 2014, ICT Innovations.

[2]  S. Ross,et al.  Economic Forces and the Stock Market , 1986 .

[3]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[4]  Jinglu Hu,et al.  An SVM-based approach for stock market trend prediction , 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

[5]  Kimon P. Valavanis,et al.  Surveying stock market forecasting techniques - Part II: Soft computing methods , 2009, Expert Syst. Appl..

[6]  Phichhang Ou,et al.  Prediction of Stock Market Index Movement by Ten Data Mining Techniques , 2009 .

[7]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[8]  Ming-Chi Lee,et al.  Using support vector machine with a hybrid feature selection method to the stock trend prediction , 2009, Expert Syst. Appl..

[9]  Shouyang Wang,et al.  Forecasting stock market movement direction with support vector machine , 2005, Comput. Oper. Res..

[10]  Zhi-Wei Ni,et al.  Stock trend prediction based on fractal feature selection and support vector machine , 2011, Expert Syst. Appl..

[11]  Johan A. K. Suykens,et al.  LS-SVMlab Toolbox User's Guide , 2010 .

[12]  R. Shah,et al.  Least Squares Support Vector Machines , 2022 .

[13]  Manish Kumar,et al.  Forecasting Stock Index Movement: A Comparison of Support Vector Machines and Random Forest , 2006 .

[14]  In-Chan Choi,et al.  Market Index and Stock Price Direction Prediction using Machine Learning Techniques: An empirical study on the KOSPI and HSI , 2013, ArXiv.

[15]  Lahmiri Salim,et al.  A Comparison of PNN and SVM for Stock Market Trend Prediction using Economic and Technical Information , 2011 .

[16]  Ömer Kaan Baykan,et al.  Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange , 2011, Expert Syst. Appl..

[17]  Dejan Erić,et al.  Application of MACD and RVI Indicators as Functions of Investment Strategy Optimization on the Financial Market , 2009 .

[18]  V. Chsherbakov.  Efficiency of Use of Technical Analysis: Evidences from Russian Stock Market , 2010 .