메뉴 건너뛰기




Volumn 11, Issue 12, 2012, Pages 671-680

Forecasting stock market trend using prototype generation classifiers

Author keywords

Forecasting; Learning vector quantization; Neural networks; Particle swarm optimization; Prediction; Prototype generation; Stock market index; Stock price; Support vector machines

Indexed keywords

COMPOSITE INDEX; HIT RATIO; LEARNING VECTOR QUANTIZATION; PROTOTYPE GENERATIONS; SOFT COMPUTING METHODS; STOCK MARKET; STOCK MARKET INDEX; STOCK PRICE; STOCK PRICE FORECASTING; TIME SERIES PREDICTION;

EID: 84871552056     PISSN: 11092777     EISSN: 22242678     Source Type: Journal    
DOI: None     Document Type: Review
Times cited : (14)

References (61)
  • 1
    • 79151471975 scopus 로고    scopus 로고
    • Trend discovery in financial time series data using a case based fuzzy decision tree
    • P. Ch. Chang, Ch. Y. Fan, J. L. Lin, Trend Discovery in Financial Time series Data using a Case based Fuzzy Decision Tree, Expert Systems with Applications, Issue 5, Vol. 38, 2011, pp. 6070-6080.
    • (2011) Expert Systems with Applications , vol.38 , Issue.5 , pp. 6070-6080
    • Chang, P.C.1    Fan, C.Y.2    Lin, J.L.3
  • 2
    • 0242351905 scopus 로고    scopus 로고
    • Financial time series forecasting using support vector machines
    • K. J. Kim, Financial Time Series Forecasting using Support Vector Machines, Neurocomputing, Vol. 55, 2003, pp. 307-319.
    • (2003) Neurocomputing , vol.55 , pp. 307-319
    • Kim, K.J.1
  • 3
    • 0003123930 scopus 로고    scopus 로고
    • Forecasting with artificial neural networks: The state of the art
    • PII S0169207097000447
    • G. Zhang, B. E. Patuwo, M. Y. Hu, Forecasting with Artificial Neural Networks: The State of the Art, International Journal of Forecasting, Vol. 14, 1998, pp. 35-62. (Pubitemid 128340470)
    • (1998) International Journal of Forecasting , vol.14 , Issue.1 , pp. 35-62
    • Zhang, G.1    Eddy Patuwo, B.2    Y. Hu, M.3
  • 6
    • 84986610539 scopus 로고
    • An intelligent forecasting system of stock price using neural networks
    • N. Baba, M. Kozaki, An Intelligent Forecasting System of Stock Price using Neural Networks, International Joint Conference on Neural Networks, Vol. 1, 1992, pp. 371-377.
    • (1992) International Joint Conference on Neural Networks , vol.1 , pp. 371-377
    • Baba, N.1    Kozaki, M.2
  • 8
    • 25844486156 scopus 로고    scopus 로고
    • The use of data mining and neural networks for forecasting stock market returns
    • DOI 10.1016/j.eswa.2005.06.024, PII S0957417405001156
    • D. Enke, S. Thawornwong, The Use of Data Mining and Neural Networks for Forecasting Stock Market Returns, Expert Systems with Applications, Issue 4, Vol. 29, 2005, pp. 927-940. (Pubitemid 41394462)
    • (2005) Expert Systems with Applications , vol.29 , Issue.4 , pp. 927-940
    • Enke, D.1    Thawornwong, S.2
  • 10
    • 73849140052 scopus 로고    scopus 로고
    • The prediction of taiwan 10-year government bond yield
    • K. Chen, H. Lin, T. Huang, The Prediction of Taiwan 10-year Government Bond Yield, WSEAS Transactions on Systems, Issue 9, Vol. 8, 2009, pp. 1051-1060.
    • (2009) WSEAS Transactions on Systems , vol.8 , Issue.9 , pp. 1051-1060
    • Chen, K.1    Lin, H.2    Huang, T.3
  • 11
    • 0742268991 scopus 로고    scopus 로고
    • Support vector machine with adaptive parameters in financial time series forecasting
    • L. J. Cao, F. E. H. Tay, Support Vector Machine with Adaptive Parameters in Financial Time Series Forecasting, IEEE Transactions on Neural Networks, Issue 6, Vol. 14, 2003, pp. 1506-1518.
    • (2003) IEEE Transactions on Neural Networks , vol.14 , Issue.6 , pp. 1506-1518
    • Cao, L.J.1    Tay, F.E.H.2
  • 12
    • 0032090662 scopus 로고    scopus 로고
    • Forecasting S&P 500 stock index futures with a hybrid AI system
    • PII S0167923698000281
    • R. Tsaih, Y. Hsu, C. C. Lai, Forecasting S&P 500 Stock Index Futures with a Hybrid AI System, Decision Support Systems, Issue 2, Vol. 23, 1998, pp. 161-174. (Pubitemid 128433703)
    • (1998) Decision Support Systems , vol.23 , Issue.2 , pp. 161-174
    • Tsaih, R.1    Hsu, Y.2    Lai, C.C.3
  • 13
    • 12444272695 scopus 로고    scopus 로고
    • A hybrid genetic-neural architecture for stock indexes forecasting
    • DOI 10.1016/j.ins.2003.03.023, PII S002002550300433X, Computational Intelligence in Economics and Finance
    • G. Armano, M. Marchesi, A. Murru, A Hybrid Genetic-Neural Architecture for Stock Indexes Forecasting, Information Science, Issue 1, Vol. 170, 2005, pp. 3-33. (Pubitemid 40146268)
    • (2005) Information Sciences , vol.170 , Issue.1 , pp. 3-33
    • Armano, G.1    Marchesi, M.2    Murru, A.3
  • 14
    • 0035255160 scopus 로고    scopus 로고
    • An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network
    • R. J. Kuo, C. H. Chen, Y. C. Hwang, An Intelligent Stock Trading Decision Support System through Integration of Genetic Algorithm based Fuzzy Neural Network and Artificial Neural Network, Fuzzy Sets and Systems, Issue 1, Vol. 118, 2001, pp. 21-45.
    • (2001) Fuzzy Sets and Systems , vol.118 , Issue.1 , pp. 21-45
    • Kuo, R.J.1    Chen, C.H.2    Hwang, Y.C.3
  • 15
    • 20344388265 scopus 로고    scopus 로고
    • A hybrid arima and support vector machines model in stock price forecasting
    • P. F. Pai, CH. S. Lin, A hybrid ARIMA and Support Vector Machines Model in Stock Price Forecasting, Omega, Issue 6, Vol. 33, 2005, pp. 497-505.
    • (2005) Omega , vol.33 , Issue.6 , pp. 497-505
    • Pai, P.F.1    Lin, C.H.S.2
  • 17
    • 59749093654 scopus 로고    scopus 로고
    • Evolving least squares support vector machines for stock market trend mining
    • L. Yu, H. Chen, S. Wang, K. K. Lai, Evolving Least Squares Support Vector Machines for Stock Market Trend Mining, IEEE Transactions on Evolutionary Computation, Issue 1, Vol. 13, 2009, pp. 87-102.
    • (2009) IEEE Transactions on Evolutionary Computation , vol.13 , Issue.1 , pp. 87-102
    • Yu, L.1    Chen, H.2    Wang, S.3    Lai, K.K.4
  • 18
    • 56349157405 scopus 로고    scopus 로고
    • Evolving and clustering fuzzy decision tree for financial time series data forecasting
    • R. K. Lai, Ch. Y. Fan, W. H. Huang, P. Ch. Chang, Evolving and Clustering Fuzzy Decision Tree for Financial Time Series Data Forecasting, Expert Systems with Applications, Vol. 36, 2009, pp. 3761-3773.
    • (2009) Expert Systems with Applications , vol.36 , pp. 3761-3773
    • Lai, R.K.1    Fan, C.Y.2    Huang, W.H.3    Chang, P.C.4
  • 19
    • 0000679641 scopus 로고    scopus 로고
    • Forecasting stock indices: A comparison of classification and level estimation models
    • M. T. Leung, H. Daouk, A. S. Chen, Forecasting Stock Indices: A Comparison of Classification and Level Estimation Models, International Journal of Forecasting, Vol. 16, 2000, pp. 173-190.
    • (2000) International Journal of Forecasting , vol.16 , pp. 173-190
    • Leung, M.T.1    Daouk, H.2    Chen, A.S.3
  • 20
    • 13544267510 scopus 로고    scopus 로고
    • Forecasting stock market movement direction with support vector machine
    • DOI 10.1016/j.cor.2004.03.016, PII S0305054804000681, Application of Neural Networks
    • W. Huang, Y. Nakamori, S. Wang, Forecasting Stock Market Movement Direction with Support Vector Machine, Computers and Operations Research, Issue 10, Vol. 32, 2005, pp. 2513-2522. (Pubitemid 40219758)
    • (2005) Computers and Operations Research , vol.32 , Issue.10 , pp. 2513-2522
    • Huang, W.1    Nakamori, Y.2    Wang, S.-Y.3
  • 21
    • 0002477659 scopus 로고
    • The CRISMA trading system: Who says technical analysis can't beat the market?
    • S. W. Pruitt, R. E. White, The CRISMA Trading System: Who Says Technical Analysis Can't Beat the Market?, Journal of Portfolio Management, Issue 3, Vol. 14, 1988, pp. 55-58.
    • (1988) Journal of Portfolio Management , vol.14 , Issue.3 , pp. 55-58
    • Pruitt, S.W.1    White, R.E.2
  • 25
    • 79951518013 scopus 로고    scopus 로고
    • Municipal credit rating modelling by neural networks
    • P. Hajek, Municipal Credit Rating Modelling by Neural Networks, Decision Support Systems, Issue 1, Vol. 51, 2011, pp. 108-118.
    • (2011) Decision Support Systems , vol.51 , Issue.1 , pp. 108-118
    • Hajek, P.1
  • 27
    • 70349472688 scopus 로고    scopus 로고
    • Evaluation of K-nearest neighbor classifier performance for direct marketing
    • M. Govindarajan, R. Chandrasekaran, Evaluation of K-Nearest Neighbor Classifier Performance for Direct Marketing, Expert Systems with Applications, Issue 1, Vol. 37, 2009, pp. 253-258.
    • (2009) Expert Systems with Applications , vol.37 , Issue.1 , pp. 253-258
    • Govindarajan, M.1    Chandrasekaran, R.2
  • 28
    • 46449133299 scopus 로고    scopus 로고
    • Air quality modelling by Kohonen's self-organizing feature maps and LVQ neural networks
    • P. Hajek, V. Olej, Air Quality Modelling by Kohonen's Self-organizing Feature Maps and LVQ Neural Networks, WSEAS Transactions on Environment and Development, Issue 1, Vol. 4, 2008, pp. 45-55. (Pubitemid 351927931)
    • (2008) WSEAS Transactions on Environment and Development , vol.4 , Issue.1 , pp. 45-55
    • Hajek, P.1    Olej, V.2
  • 29
    • 0343081513 scopus 로고    scopus 로고
    • Reduction techniques for instance-based learning algorithms
    • DOI 10.1023/A:1007626913721
    • D. R. Wilson, T. R. Martinez, Reduction Techniques for Instance based Learning Algorithms, Machine Learning, Issue 3, Vol. 38, 2000, pp. 257-286. (Pubitemid 30572450)
    • (2000) Machine Learning , vol.38 , Issue.3 , pp. 257-286
    • Randall Wilson, D.1    Martinez, T.R.2
  • 30
    • 0003410791 scopus 로고    scopus 로고
    • Springer, Verlag, Berlin, Heidelberg, New York
    • T. Kohonen, Self-Organizing Maps, Springer Verlag, Berlin, Heidelberg, New York, 2001.
    • (2001) Self-Organizing Maps
    • Kohonen, T.1
  • 31
    • 0026119582 scopus 로고
    • Adaptive nearest neighbor pattern classifier
    • S. Geva, J. Site, Adaptive Nearest Neighbor Pattern Classifier, IEEE Transactions on Neural Networks, Issue 2, Vol. 2, 1991, pp. 318-322.
    • (1991) IEEE Transactions on Neural Networks , vol.2 , Issue.2 , pp. 318-322
    • Geva, S.1    Site, J.2
  • 33
    • 0031062148 scopus 로고    scopus 로고
    • Finding prototypes for nearest neighbour classification by means of gradient descent and deterministic annealing
    • PII S0031320396000726
    • C. Decaestecker, Finding Prototypes for Nearest Neighbour Classification by means of Gradient Descent and Deterministic Annealing, Pattern Recognition, Issue 2, Vol. 30, 1997, pp. 281-288. (Pubitemid 127407618)
    • (1997) Pattern Recognition , vol.30 , Issue.2 , pp. 281-288
    • Decaestecker, C.1
  • 34
    • 3142672346 scopus 로고    scopus 로고
    • Evolutionary design of nearest prototype classifiers
    • F. Fernandez, P. Isaci, Evolutionary Design of Nearest Prototype Classifiers, Journal of Heuristics, Issue 4, Vol. 10, 2004, pp. 431-454.
    • (2004) Journal of Heuristics , vol.10 , Issue.4 , pp. 431-454
    • Fernandez, F.1    Isaci, P.2
  • 35
    • 50549086165 scopus 로고    scopus 로고
    • Prototype reduction using an artificial immune model
    • U. Garain, Prototype Reduction using an Artificial Immune Model, Pattern Analysis and Applications, Issues 3-4, Vol. 11, 2008, pp. 353-363.
    • (2008) Pattern Analysis and Applications , vol.11 , Issue.3-4 , pp. 353-363
    • Garain, U.1
  • 36
    • 58149475488 scopus 로고    scopus 로고
    • Particle swarm optimization for prototype reduction
    • L. Nanni, A. Lumini, Particle Swarm Optimization for Prototype Reduction. Neurocomputing, Issues 4-6, Vol. 72, 2009, 1092-1097.
    • (2009) Neurocomputing , vol.72 , Issue.4-6 , pp. 1092-1097
    • Nanni, L.1    Lumini, A.2
  • 37
    • 38149030933 scopus 로고    scopus 로고
    • An adaptive michigan approach PSO for nearest prototype classification
    • A. Cervantes, I. Galvan, P. Isasi, An Adaptive Michigan Approach PSO for Nearest Prototype Classification, Lecture Notes in Computer Science, Vol. 4528, 2007, pp. 287-296.
    • (2007) Lecture Notes in Computer Science , vol.4528
    • Cervantes, A.1    Galvan, I.2    Isasi, P.3
  • 38
    • 1842787628 scopus 로고    scopus 로고
    • A vector quantization method for nearest neighbor classifier design
    • C. W. Yen, C. N. Young, M. L. Nagurka, A Vector Quantization Method for Nearest Neighbor Classifier Design, Pattern Recognition Letters, Vol. 25, 2004, pp. 725-731.
    • (2004) Pattern Recognition Letters , vol.25
    • Yen, C.W.1    Young, C.N.2    Nagurka, M.L.3
  • 40
    • 0030196853 scopus 로고    scopus 로고
    • A sample set condensation algorithm for the class sensitive artificial neural network
    • DOI 10.1016/0167-8655(96)00041-4, PII S0167865596000414
    • C. H. Chen, A. Jozwik, A Sample Set Condensation Algorithm for the Class Sensitive Artificial Neural Network, Pattern Recognition Letters, Vol. 17, 1996, pp. 819-823. (Pubitemid 126384186)
    • (1996) Pattern Recognition Letters , vol.17 , Issue.8 , pp. 819-823
    • Chen, C.H.1    Jozwik, A.2
  • 42
    • 0019392071 scopus 로고
    • On the relation of performance to editing in nearest neighbor rules
    • DOI 10.1016/0031-3203(81)90102-3
    • J. Koplowitz, T. A. Brown, On the Relation of Performance to Editing in Nearest Neighbor Rules, Pattern Recognition, Vol. 13, 1981, pp. 251-255. (Pubitemid 11413647)
    • (1981) Pattern Recognition , vol.13 , Issue.3 , pp. 251-255
    • Koplowitz Jack1    Brown Thomas, A.2
  • 44
    • 0036684204 scopus 로고    scopus 로고
    • Discovering useful concept prototypes for classification based on filtering and abstraction
    • W. Lam, C. K. Keung, D. Liu, Discovering Useful Concept Prototypes for Classification based on Filtering and Abstraction, IEEE Transactions on Pattern Analysis and Machine Intelligence, Issue 8, Vol. 14, 2002, pp. 1075-1090.
    • (2002) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.14 , Issue.8 , pp. 1075-1090
    • Lam, W.1    Keung, C.K.2    Liu, D.3
  • 45
    • 33745421067 scopus 로고    scopus 로고
    • Experimental study on prototype optimisation algorithms for prototype-based classification in vector spaces
    • DOI 10.1016/j.patcog.2006.04.005, PII S0031320306001592
    • M. Lozano, J. M. Sotoca, J. S. Sanchez, F. Pla, E. Pekalska, R. P. W. Duin, Experimental Study on Prototype Optimisation Algorithms for Prototypebased Classification in Vector Spaces, Pattern Recognition, Issue 10, Vol. 39, 2006, pp. 1827-1838. (Pubitemid 43947094)
    • (2006) Pattern Recognition , vol.39 , Issue.10 , pp. 1827-1838
    • Lozano, M.1    Sotoca, J.M.2    Sanchez, J.S.3    Pla, F.4    Pekalska, E.5    Duin, R.P.W.6
  • 46
    • 0016127071 scopus 로고
    • Finding prototypes for nearest neighbor classifiers
    • Ch. L. Chang, Finding Prototypes for Nearest Neighbor Classifiers, IEEE Transactions on Computers, Issue 11, Vol. 23, 1974, pp. 1179-1184.
    • (1974) IEEE Transactions on Computers , vol.23 , Issue.11 , pp. 1179-1184
    • Chang, C.L.1
  • 47
    • 19744376790 scopus 로고    scopus 로고
    • A divide-and-conquer approach to the pairwise opposite class-nearest neighbor (POC-NN) algorithm
    • DOI 10.1016/j.patrec.2005.01.003, PII S0167865505000115
    • T. Raicharoen, C. Lursinsap, A Divide-and-Conquer Approach to the Pairwise Opposite Class-Nearest Neighbor (POC-NN) Algorithm, Pattern Recoginiton Letters, Vol. 26, 2005, pp. 1554-1567. (Pubitemid 40744195)
    • (2005) Pattern Recognition Letters , vol.26 , Issue.10 , pp. 1554-1567
    • Raicharoen, T.1    Lursinsap, C.2
  • 48
    • 18144451785 scopus 로고    scopus 로고
    • High training set size reduction by space partitioning and prototype abstraction
    • DOI 10.1016/j.patcog.2003.12.012, PII S0031320304000147
    • J. S. Sanchez, High Training Set Size Reduction by Space Partitioning and Prototype Abstraction, Pattern Recognition, Issue 7, Vol. 37, 2004, pp. 1561-1564. (Pubitemid 38653386)
    • (2004) Pattern Recognition , vol.37 , Issue.7 , pp. 1561-1564
    • Sanchez, J.S.1
  • 49
    • 33846316693 scopus 로고    scopus 로고
    • Self-generating prototypes for pattern classification
    • DOI 10.1016/j.patcog.2006.10.018, PII S0031320306004523
    • H. A. Fayed, S. R. Hashem, A. F. Atiya, Self-Generating Prototypes for Pattern Classification, Pattern Recognition, Issue 5, Vol. 40, 2007, pp. 1498-1509. (Pubitemid 46123389)
    • (2007) Pattern Recognition , vol.40 , Issue.5 , pp. 1498-1509
    • Fayed, H.A.1    Hashem, S.R.2    Atiya, A.F.3
  • 53
    • 80051670014 scopus 로고    scopus 로고
    • Credit rating modelling by kernel-based approaches with supervised and semi-supervised learning
    • P. Hajek, V. Olej, Credit Rating Modelling by Kernel-based Approaches with Supervised and Semi-Supervised Learning, Neural Computing & Applications, Issue 6, Vol. 20, 2011, pp. 761-773.
    • (2011) Neural Computing & Applications , vol.20 , Issue.6 , pp. 761-773
    • Hajek, P.1    Olej, V.2
  • 55
    • 84871543909 scopus 로고    scopus 로고
    • Up/down analysis of stock index by using bayesian network
    • Y. Zuo, E. Kita, Up/Down Analysis of Stock Index by Using Bayesian Network, Engineering Management Research, Issue 2, Vol. 1, 2012, pp. 46-52.
    • (2012) Engineering Management Research , vol.1 , Issue.2 , pp. 46-52
    • Zuo, Y.1    Kita, E.2
  • 56
    • 78649525701 scopus 로고    scopus 로고
    • Municipal revenue prediction by ensembles of neural networks and support vector machines
    • P. Hajek, V. Olej, Municipal Revenue Prediction by Ensembles of Neural Networks and Support Vector Machines, WSEAS Transactions on Computers, Issue 11, Vol. 9, 2010, pp. 1255-1264.
    • (2010) WSEAS Transactions on Computers , vol.9 , Issue.11 , pp. 1255-1264
    • Hajek, P.1    Olej, V.2
  • 57
    • 80055020943 scopus 로고    scopus 로고
    • Soft computing algorithms in price of taiwan real estates
    • H. Lin, K. Chen, Soft Computing Algorithms in Price of Taiwan Real Estates, WSEAS Transactions on Systems, Issue 10, Vol. 10, 2011, pp. 342-351.
    • (2011) WSEAS Transactions on Systems , vol.10 , Issue.10 , pp. 342-351
    • Lin, H.1    Chen, K.2
  • 59
    • 24644436777 scopus 로고    scopus 로고
    • Prediction of high increases in stock prices using neural networks
    • COMPSTAT 2004
    • K. Michalak, P. Lipinski, Prediction of High Increases in Stock Prices using Neural Networks, Neural Network World, Vol. 15, 2005, pp. 359-366. (Pubitemid 41274843)
    • (2005) Neural Network World , vol.15 , Issue.4 , pp. 359-366
    • Michalak, K.1    Lipinski, P.2
  • 60
    • 84864117770 scopus 로고    scopus 로고
    • Learning predictive models for financial time series by using agent based simulations
    • F. Neri, Learning Predictive Models for Financial Time Series by Using Agent Based Simulations, Lecture Notes in Computer Science, Vol. 7190, 2012, pp. 202-221.
    • (2012) Lecture Notes in Computer Science , vol.7190 , pp. 202-221
    • Neri, F.1
  • 61
    • 84867569780 scopus 로고    scopus 로고
    • Agent based modeling under partial and full knowledge learning settings to simulate financial markets
    • F. Neri, Agent based Modeling under Partial and Full Knowledge Learning Settings to Simulate Financial Markets, AI Communications, Issue 4, Vol. 25, 2012, pp. 295-304.
    • (2012) AI Communications , vol.25 , Issue.4 , pp. 295-304
    • Neri, F.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.