Candlestick Tutor: An Intelligent Tool for Investment Knowledge Learning and Sharing
ICALT '05 Proceedings of the Fifth IEEE International Conference on Advanced Learning Technologies
Pattern Discovery of Fuzzy Time Series for Financial Prediction
IEEE Transactions on Knowledge and Data Engineering
Adaptive simplification of solution for support vector machine
Pattern Recognition
Automatic extraction and identification of chart patterns towards financial forecast
Applied Soft Computing
Hyperplane algorithm - first step of the paired planes classification procedure
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Quadratic kernel-free non-linear support vector machine
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Financial time series prediction using polynomial pipelined neural networks
Expert Systems with Applications: An International Journal
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Dynamic Ridge Polynomial Neural Networks in Exchange Rates Time Series Forecasting
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Research of CT / MRI Tumor Image Registration Based on Least Square Support Vector Machines
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
A hybrid SOFM-SVR with a filter-based feature selection for stock market forecasting
Expert Systems with Applications: An International Journal
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Expert Systems with Applications: An International Journal
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SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
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Pattern Recognition Letters
Financial time series forecasting using independent component analysis and support vector regression
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International Journal of Advanced Intelligence Paradigms
Gas Concentration Forecasting Based on Support Vector Regression in Correlation Space via KPCA
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
A dynamic holding strategy in public transit systems with real-time information
Applied Intelligence
Forecasting Change Directions for Financial Time Series Using Hidden Markov Model
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
A Hybrid Method for Forecasting Stock Market Trend Using Soft-Thresholding De-noise Model and SVM
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Expert Systems with Applications: An International Journal
Automatic stock decision support system based on box theory and SVM algorithm
Expert Systems with Applications: An International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Application of support vector machine technology for weed and nitrogen stress detection in corn
Computers and Electronics in Agriculture
European Option Pricing by Using the Support Vector Regression Approach
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Data Driven Rank Ordering and Its Application to Financial Portfolio Construction
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Intelligent stock trading system based on SVM algorithm and oscillation box prediction
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Application of support vector machines to bandwidth reservation in sectored cellular communications
Engineering Applications of Artificial Intelligence
Time series prediction using support vector machines: a survey
IEEE Computational Intelligence Magazine
Predicting stock trends through technical analysis and nearest neighbor classification
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Real-time foreground-background segmentation using adaptive support vector machine algorithm
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Adaptive chaotic cultural algorithm for hyperparameters selection of support vector regression
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
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ICNC'09 Proceedings of the 5th international conference on Natural computation
GA-SVM based framework for time series forecasting
ICNC'09 Proceedings of the 5th international conference on Natural computation
Expert Systems with Applications: An International Journal
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Expert Systems with Applications: An International Journal
ICDM'10 Proceedings of the 10th industrial conference on Advances in data mining: applications and theoretical aspects
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IEEE Computational Intelligence Magazine
Expert Systems with Applications: An International Journal
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Applied Soft Computing
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Expert Systems with Applications: An International Journal
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Computers and Operations Research
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ACM Transactions on Knowledge Discovery from Data (TKDD)
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Computational Intelligence and Neuroscience
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A novel type of learning machine called support vector machine (SVM) has been receiving increasing interest in areas ranging from its original application in pattern recognition to other applications such as regression estimation due to its remarkable generalization performance. This paper deals with the application of SVM in financial time series forecasting. The feasibility of applying SVM in financial forecasting is first examined by comparing it with the multilayer back-propagation (BP) neural network and the regularized radial basis function (RBF) neural network. The variability in performance of SVM with respect to the free parameters is investigated experimentally. Adaptive parameters are then proposed by incorporating the nonstationarity of financial time series into SVM. Five real futures contracts collated from the Chicago Mercantile Market are used as the data sets. The simulation shows that among the three methods, SVM outperforms the BP neural network in financial forecasting, and there are comparable generalization performance between SVM and the regularized RBF neural network. Furthermore, the free parameters of SVM have a great effect on the generalization performance. SVM with adaptive parameters can both achieve higher generalization performance and use fewer support vectors than the standard SVM in financial forecasting.