Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Data mining in finance: advances in relational and hybrid methods
Data mining in finance: advances in relational and hybrid methods
Landmarks: A New Model for Similarity-Based Pattern Querying in Time Series Databases
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Discriminative training of Markov logic networks
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
A generalized model for financial time series representation and prediction
Applied Intelligence
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
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
Predicting stock trends through technical analysis and nearest neighbor classification
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Expert Systems with Applications: An International Journal
Improving trading systems using the RSI financial indicator and neural networks
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
A review on time series data mining
Engineering Applications of Artificial Intelligence
A learning-based contrarian trading strategy via a dual-classifier model
ACM Transactions on Intelligent Systems and Technology (TIST)
Intelligent stock trading system based on improved technical analysis and Echo State Network
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A dynamic threshold decision system for stock trading signal detection
Applied Soft Computing
Learning the funding momentum of research projects
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
Feature selection for classification of oscillating time series
Expert Systems: The Journal of Knowledge Engineering
OBST-based segmentation approach to financial time series
Engineering Applications of Artificial Intelligence
| Hi-index | 12.07 |
Financial engineering such as trading decision is an emerging research area and also has great commercial potentials. A successful stock buying/selling generally occurs near price trend turning point. Traditional technical analysis relies on some statistics (i.e. technical indicators) to predict turning point of the trend. However, these indicators can not guarantee the accuracy of prediction in chaotic domain. In this paper, we propose an intelligent financial trading system through a new approach: learn trading strategy by probabilistic model from high-level representation of time series-turning points and technical indicators. The main contributions of this paper are two-fold. First, we utilize high-level representation (turning point and technical indicators). High-level representation has several advantages such as insensitive to noise and intuitive to human being. However, it is rarely used in past research. Technical indicator is the knowledge from professional investors, which can generally characterize the market. Second, by combining high-level representation with probabilistic model, the randomness and uncertainty of chaotic system is further reduced. In this way, we achieve great results (comprehensive experiments on S&P500 components) in a chaotic domain in which the prediction is thought impossible in the past.