원문정보
보안공학연구지원센터(IJUNESST)
International Journal of u- and e- Service, Science and Technology
Vol.8 No.7
2015.07
pp.35-48
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Financial investment has become an important issue, there are many trading strategies and parameters based on quantitative models, this paper use neural network algorithm to optimization strategy parameters, various combinations of optimization strategies, as well as the evolution of new strategies to generate better returns. The empirical results show that this method has a stable and substantial return on investment, neural network can be used as an aid for decision making investments in securities.
목차
Abstract
1. Introduction
2. Multi-Factor Model Based on Neural Network
3. Auto Encoders
4. Algorithm Principle
4.1. Probabilistic Neural Network (PNN)
4.2. Radial Basis Function Neural Network (RBFNN)
4.3. Hybrid Neural Network Structure (RBF-PMNN)
4.4. Learning Algorithm Of Radial Basis Function Neural Network Hybrid Probability (RBF- PMNN)
5. Trading Strategies
6. Stock -Picking System
7. Conclusion
References
1. Introduction
2. Multi-Factor Model Based on Neural Network
3. Auto Encoders
4. Algorithm Principle
4.1. Probabilistic Neural Network (PNN)
4.2. Radial Basis Function Neural Network (RBFNN)
4.3. Hybrid Neural Network Structure (RBF-PMNN)
4.4. Learning Algorithm Of Radial Basis Function Neural Network Hybrid Probability (RBF- PMNN)
5. Trading Strategies
6. Stock -Picking System
7. Conclusion
References
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저자정보
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자료제공 : 네이버학술정보