References: [1] Huang, W., Nakamori, Y. & Wang, S.Y. (2005) Forecasting stock market movement direction with support vector machine. Computers and Operations Research, 32, 2513–2522 [DOI: 10.1016/j.cor.2004.03.016]. [2] Lahmiri, S. (2011) A comparison of PNN and SVM for stock market trend prediction using economic and technical information. International Journal of Computers and Applications, 29. [3] Chsherbakov, V. (2010) Efficiency of use of technical analysis: Evidences from Russian stock market. Ekonomika a Management, 4. [4] Dowd, K. (2002). Measuring Market Risk. John Wiley & Sons Ltd: Chichester, UK. [5] Phichhang, O., Wang, H. (2009) Prediction of Stock Market Index Movement by Ten Data Mining Techniques. Modern Applied Science, 3, 28–42. [6] Huang, G.-B., Zhu, Q.-Y. & Siew, C.-K. (2006) Extreme learning machine: Theory and applications. Neurocomputing, 70, 489– 501 [DOI: 10.1016/j.neucom.2005.12.126]. [7] Huang, G., Huang, G.B., Song, S. & You, K. (2015) Trends in extreme learning machines: A review. Neural Networks, 61, 32–48 [DOI: 10.1016/j.neunet.2014.10.001] [PubMed: 25462632]. [8] Markovia, I., Stankovic, J. & M. (2014) Stojanovia. M. Bone. Prediction of the Stock Market Trend Using LS-SVMs Based on Technical Indicators. presented at the 49th international conference. ICEST: Nis, Serbia. [9] Stojanove, M., Cvetkovie, S. & Staneie, G. (2017) Poredenje metoda maginskog ueenja za predikciju Trenda promene finansijskih vremenskih serija. Simpozijum INFOTEH Jahorina, 2017, 398–401. [10] Amihud, Y. (2002) Illiquidity and stock returns: Cross-section and time-series effects. Journal of Financial Markets, 5, 31–56 [DOI: 10.1016/S1386-4181(01)00024-6]. [11] Stankovic, J.Z., Petrovic, E. (2018) Liquidity risk implications for market risk assessment in emerging markets. Journal of Contemporary Economic and Business Issues, 5, 5–23. [12] Yuling, L., Guo, H. & Hu, J. (2013) An SVM-based approach for stock market trend prediction. Neural Networks (IJCNN). IEEE Publications, 1–7. [13] Chang, C.-C. Lin, C.-J. (2011) LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2, 1–27 [DOI: 10.1145/1961189.1961199], p. 27:1-27:27. |