[1]. T. Martikainen, J. Perttunen, P. Yli-Olli, and A. Gunasekaran, 1994. The impact of the return interval on common factors in stock returns: Evidence from a thin security market, Journal of Banking &; Finance, 18(4), 659-672.
[2]. D. Kirkpatrick, and R. Dahlquist, 2006. Technical analysis: The complete resource for financial market technicians, Financial Times Press, 2006, page 3.
[3]. P. C. Chang, and C. Y. Fan, 2008. A hybrid system integrating a wavelet and TSK fuzzy rules for stock price forecasting, IEEE Transactions on Systems, Man, and Cybernetics – Part C: Applications and Reviews, 38(6), 802-815.
[4]. P. C. Chang, T. W. Liao, J. J. Lin, and C. Y. Fan, 2011. A dynamic threshold decision system for stock trading signal detection, Applied Soft Computing, 11(5), 3998-4010.
[5]. S. Asadi, E. Hadavandi, F. Mehmanpazir, and M. M. Nakhostin, 2012. Hybridization of evolutionary Levenberg–Marquardt neural networks and data pre-processing for stock market prediction, Knowledge-Based Systems, 35(11), 245-258.
[6]. W. Shen, X. Guo, C. Wu, and D. Wu, 2011. Forecasting stock indices using radial basis function neural networks optimized by artificial fish swarm algorithm, Knowledge-Based Systems, 24(3), 378-385.
[7]. J. L. Wu, H. S. Chu, L. C. Yu, and P. C. Chang, 2012. Sentiment analysis of stock news using a PMI-based term expansion method, ICIC Express Letters, 6(2), 491-496.
[8]. K. Chan, and J. Franklin, 2011. A text-based decision support system for financial sequence prediction, Decision Support Systems, 52(1), 189-198.
[9]. W. Lo, H. Mamaysky, and J. Wang, 2000. Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation, Journal of Finance, 55(4), 1705-1765.
[10]. L. C. Yu, J. L. Wu, P. C. Chang, and H. S. Chu, 2013. Using a contextual entropy model to expand emotion words and their intensity for the sentiment classification of stock market news, accepted by Knowledge-Based Systems. http://dx.doi.org/10.1016/j.knosys.2013.01.001
[11]. S. S. Groth, and J. Muntermann, 2011. An intraday market risk management approach based on textual analysis, Decision Support Systems, 50(4), 680-691.
[12]. G. P. C. Fung, J. X. Yu, and W. Lam, 2002. News sensitive stock trend prediction, in: Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD-02), Taipei, Taiwan, 481-493.
[13]. L. Zhou, Y. Zhang, C. Xing, Y. Sun, and X. Zhu, 2010. Sentiment classification for stock news, in: Proceedings of the IEEE 5th International Conference on Pervasive Computing and Applications (ICPCA-10), Beijing, China, 99-104.
[14]. E. Hadavandi, H. Shavandi, and A. Ghanbari, 2010. Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting, Knowledge-Based Systems, 23(8), 800-808.
[15]. L. J. Kao, C. C. Chiu, C. J. Lu, and J. L. Yang, 2013. Integration of nonlinear independent component analysis and support vector regression for stock price forecasting, Neurocomputing, 99, 534-542.
[16]. P. C. Chang, D. D. Wang, and C. L. Zhou, 2012. A novel model by evolving partially connected neural network for stock price trend forecasting, Expert Systems with Applications, 39(1), 611-620.
[17]. R. K. Lai, C. Y. Fan, W. H. Huang, and P. C. Chang, 2009. Evolving and clustering fuzzy decision tree for financial time series data forecasting, Expert Systems with Applications, 36(2), 3761-3773.
[18]. F. Tsai, and Y. C. Hsiao, 2010. Combining multiple feature selection methods for stock prediction: Union, intersection, and multi-intersection approaches, Decision Support Systems, 50(1), 258-269.
[19]. J. L. Wu, and P. C. Chang, 2012. A trend-based segmentation method and the support vector regression for financial time series forecasting, Mathematical Problems in Engineering, Article ID 615152, 20 pages.
[20]. L. Dymova, P. Sevastianov, and P. Bartosiewicz, 2010. A new approach to the rule-base evidential reasoning: Stock trading expert system application, Expert Systems with Applications, 37(8), 5564-5576.
[21]. P. C. Chang, and C. H. Liu, 2008. A TSK type fuzzy rule based system for stock price prediction, Expert Systems with Applications, 34(1), 135-144.
[22]. Y. Kara, M. A. Boyacioglu, and #westeur023#. K. Baykan, 2011. Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul stock exchange, Expert Systems with Applications, 38(5), 5311-5319.
[23]. M. Lam, 2004. Neural network techniques for financial performance prediction: integrating fundamental and technical analysis, Decision Support Systems, 37(4), 567-581.
[24]. M. S. Rozeff, and W. R. Kinney, 1976. Capital market seasonality: The case of stock market return, Journal of Financial Economics, 376-402.
[25]. E. Fama, 1970. Efficient capital market: A review of theory and empirical work, Journal of Finance, 25(2), 383-417.
[26]. A. Shleifer, 1986. Do demand curves for stocks slope down?, The Journal Finance, 41(3), 579-590.
[27]. N. H. J. Lorraine, D. J. Collison, and D. M. Power, 2004. An analysis of the stock market impact of environmental performance information, Accounting Forum, 28, 7-26.
[28]. S. J. Kim, 2005. Information leadership in the advanced Asia-Pacific stock market: Return, volatility and volume information spillovers from the US and Japan, Journal of the Japanese and International Economies, 19(3), 338-365.
[29]. X. Zhang, H. Fuehres, and P. A. Gloor, 2011. Predicting stock market indicators through Twitter “I hope it is not as bad as I fear”, Procedia-Social and Behavioral Sciences, 26, 55-62.
[30]. G. S. Atsalakis, and K. P. Valavanis, 2009. Surveying stock market forecasting techniques - part II: Soft computing methods, Expert Systems with Applications, 36(3-2), 5932-5941.
[31]. M. A. H. Dempster, T. W. Payne, Y. Romahi, and G. W. P. Thompson, 2001. Computational learning techniques for intraday FX trading using popular technical indicators, IEEE Transactions on Neural Network, 12(4), 744-754.
[32]. K. Kurumatani, H. Kawamura, and A. Ohuchi, 2005. Market micro-structure analysis by multiagent simulation in X-economy: comparison among technical indices, Information Sciences, 170(1), 65-74.
[33]. M. M. Bradley, and P. J. Lang, 1999. Affective Norms for English Words (ANEW): Instruction Manual and Affective Ratings, Technical Report C-1, Center for Research in Psychophysiology, University of Florida.
[34]. A. Valitutti, C. Strapparava, and O. Stock, 2004. Developing affective lexical resources, PsychNology, 2(1), 61-83.
[35]. A. Esuli, and F. Sebastiani, 2006. SENTIWORDNET: A publicly available lexical resource for opinion mining, in: Proceedings of the 5th Conference on Language Resources and Evaluation (LREC-06), Genoa, Italy, 417-422.
[36]. A. Neviarouskaya, H. Prendinger, and M. Ishizuka, 2011. SentiFul: A lexicon for sentiment analysis, IEEE Transactions on Affective Computing, 2(1), 22-36.
[37]. A. Balahur, J.M. Hermida, and A. Montoyo, 2012. Building and exploiting EmotiNet, a knowledge base for emotion detection based on the appraisal theory model, IEEE Transactions on Affective Computing, 3(1), 88-101.
[38]. W. Ku, and H. H. Chen, 2007. Mining opinions from the web: Beyond relevance retrieval, Journal of the American Society for Information Science and Technology, 58(12), 1838-1850.
[39]. Y. Hu, X. Chen, and D. Yang, 2009. Lyric-based song emotion detection with affective lexicon and fuzzy clustering method, in: Proceedings of the 10th International Society for Music Information Retrieval Conference (ISMIR-09), Kobe, Japan, 123-128.
[40]. C. Quan, and F. Ren, 2010. Sentence emotion analysis and recognition based on emotion words using Ren-CECps, International Journal of Advanced Intelligence, 2(1), 105-117.
[41]. G. Xu, X. Meng, and H. Wang, 2010. Build Chinese emotion lexicons using a graph-based algorithm and multiple resources, in: Proceedings of the 23rd International Conference on Computational Linguistics (Coling-10), Beijing, China, 1209-1217.
[42]. Y. W. Liu, S. B. Xiao, T. Wang, and S. C. Shi, 2011. Building Chinese sentiment lexicon based on HowNet, Advanced Materials Research, 187, 405-410.
[43]. N. Li, and D. D. Wu, 2009. Using text mining and sentiment analysis for online forums hotspot detection and forecast, Decision Support Systems, 48(2), 354-368.
[44]. C. Kaiser, S. Schlick, and F. Bodendorf, 2011. Warning system for online market research – Identifying critical situations in online opinion formation, Knowledge-Based Systems, 24(6), 824-836.
[45]. C. H. Wu, L. C. Yu, and F. L. Jang, 2005. Using semantic dependencies to mine depressive symptoms from consultation records, IEEE Intelligent Systems, 20(6), 50-58.
[46]. L. C. Yu, C. L. Chan, C. C. Lin, and I. C Lin, 2011. Mining association language patterns using a distributional semantic model for negative life event classification, Journal of Biomedical Informatics, 44(4), 509-518.
[47]. A. Abbasi, H. Chen, S. Thoms, and T. Fu, 2008. Affect analysis of web forums and blogs using correlation ensembles, IEEE Transactions on Knowledge and Data Engineering, 20(9), 1168-1180.
[48]. G. Grefenstette, Y. Qu, D. A. Evans, and J. G. Shanahan, 2006. Validating the coverage of lexical resources for affect analysis and automatically classifying new words along semantic axes, Computing Attitude and Affect in Text: Theory and Applications, 20, 93-107.
[49]. M. Baroni, and S. Vegnaduzzo, 2004. Identifying subjective adjectives through Web-based mutual information, in: Proceedings of the 7th Konferenz zur Verarbeitung Nat#westeur061#rlicher Sprache (German Conference on Natural Language Processing – KONVENS’04), Vienna, Austria, 613-619.
[50]. P. D. Turney, and M. L. Littman, 2003. Measuring praise and criticism: Inference of semantic orientation from association, ACM Transactions on Information Systems, 21(4), 315-346.
[51]. A. Lachaud, F. Vialard, and D. Vieilleville, 2005. Analysis and comparative evaluation of discrete tangent estimators, In: Andres, E., Damiand, G., Lienhardt, P. (eds) DGCI 2005, LNCS, Springer (3429), 240-251.
[52]. Y. Zhu, D. Wu, and S. Li, 2007. A piecewise linear representation method of time series based on feature pints, in: Proceeding of the 11th International Conference Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks (KES 2007/ WIRN 2007), Part II, Vietri sul Mare, Italy, 1066-1072.
[53]. Z. Zhang, J. Jiang, X. Liu, W. C. Lau, H. Wang, S. Wang, X. Song, and D. Xu, 2007. Pattern recognition in stock data based on a new segmentation algorithm, in Zhang, Z. and Siekmann, J. (eds) KSEM 2007, LNCS, Springer (4798), 520–525.
[54]. N. Gershenfeld, 1999. The nature of mathematical modeling. Cambridge University Press, Cambridge, England, 205-08.
[55]. F. X. Diebold, and R. S. Mariano, 2002. Comparing predictive accuracy, Journal of Business and Economic Statistics, 20(1), 134-144.
[56]. R. Gencay, 1999. Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules, Journal of International Economic, 47(1), 91-107.
[57]. Y. S. Lee, and L. I. Tong, 2011. Forecasting time series using a methodology based on autoregressive integrated moving average and genetic programming, Knowledge-Based Systems, 24(1), 66-72.
[58]. D. Bao, and Z. Yang, 2008. Intelligent stock trading system by turning point confirming and probabilistic reasoning, Expert Systems with Applications, 34(1), 620-627.
[59]. T. Farooq, A. Guergachi, and S. Krishnan, 2010. Knowledge-based Green's Kernel for support vector regression, Mathematical Problems in Engineering, 2010 (378652), 16 pages.
[60]. S. O. Lozza, E. Angelelli, and A. Bianchi, 2011. Financial applications of bivariate Markov processes, Mathematical Problems in Engineering, 2011 (347604), 15 pages.
[61]. A. Swishchuk, and R. Manca, 2010. Modeling and pricing of variance and volatility swaps for local semi-markov volatilities in financial engineering, Mathematical Problems in Engineering, 2010 (537571), 17 pages.
[62]. M. S. Abd-Elouahab, N. E. Hamri, and J. Wang, 2010. Chaos control of a fractional-order financial system, Mathematical Problems in Engineering, 2010 (270646), 18 pages.
[63]. A. J. Smola, and B. Sch#westeur055#lkopf, 2004. A tutorial on support vector regression, Journal of Statistics and Computing, 14(3), 199-222.
[64]. N. Vapnik, 1998. Statistical Learning Theory, JohnWiley &; Sons, New York, NY, USA.
[65]. Z. Liu, 2010. Chaotic time series analysis, Mathematical Problems in Engineering, 2010 (720190), 31 pages.
[66]. B. Chen, M. W. Chang, and C. J. Lin, 2004. A study on EUNITE competition 2001, IEEE Transactions on Power Systems, 19(4), 1821-1830.
[67]. F. Girosi, M. Jones, and T. Poggio, 1995. Regularization theory and neural networks architectures, Neural Computation, 7, 219-269.
[68]. P. F. Pai, and C. S. Lin, 2005. A hybrid ARIMA and support vector machines model in stock price forecasting, Omega, 33(6), 497-505.
[69]. H. Liu and J. Wang, 2011. Integrating independent component analysis and principal component analysis with neural network to predict Chinese stock market, Mathematical Problems in Engineering, 2011 (382659), 15 pages.
[70]. Y. W. Wang, P. C. Chang, C. Y. Fan, and C. H. Huang, 2010. Database classification by integrating a case-based reasoning and support vector machine for induction, Journal of Circuits, Systems, and Computers, 19(1), 31-44.
[71]. L. Zhang, W. D. Zhou, and P. C. Chang, 2011. Generalized nonlinear discriminant analysis and its small sample size problems, Neurocomputing, 74(4), 568-574.
[72]. N. Sapankevych, and R. Sankar, 2009. Time series prediction using support vector machines: a survey, IEEE Computational Intelligence Magazine, 4(2), 24-38.
[73]. J. L. Wu, L. C. Yu, and P. C. Chang, 2011. Emotion classification by removal of the overlap from incremental association language features, Journal of the Chinese Institute of Engineers, 34(7), 947-955.
[74]. L. C. Yu, C. H. Wu, J. F. Yeh, and F. L. Jang, 2008. HAL-based evolutionary inference for pattern induction from psychiatry web resources, IEEE Transactions on Evolutionary Computation, 12(2), 160-170.
[75]. T. Xu, Q. Peng, and Y. Cheng, 2012. Identifying the semantic orientation of terms using S-HAL for sentiment analysis, Knowledge-Based Systems, 35, 279-289.
[76]. G. Salton, and C. Buckley, 1988. Term-weighting approaches in automatic text retrieval, Information Processing Management, 24(5), 513-523.
[77]. P. I. Chen, and S. J. Lin, 2011. Word AdHoc network: Using Google core distance to extract the most relevant information, Knowledge-Based Systems, 24(3), 393-405.
[78]. Q. Cao, W. Duan, and Q. Gan, 2011. Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approach, Decision Support Systems, 50 (2), 511-521.
[79]. S. Kullback, 1959. Information Theory and Statistics, John-Wiley &; Sons, New York, NY, USA.
[80]. B. Achelis, 2000. Technical Analysis from A to Z (4th eds.), McGraw-Hill, New York, NY, USA.