Design, testing, and optimization of trading systems
Design, testing, and optimization of trading systems
Trading on the Edge: Neural, Genetic, and Fuzzy Systems for Chaotic Financial Markets
Trading on the Edge: Neural, Genetic, and Fuzzy Systems for Chaotic Financial Markets
Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real World Performance
Support Vector Machine Regression for Volatile Stock Market Prediction
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Neural networks and the financial markets: predicting, combining and portfolio optimisation
Neural networks and the financial markets: predicting, combining and portfolio optimisation
Computational Intelligence in Economics and Finance: Volume II
Computational Intelligence in Economics and Finance: Volume II
Learning to trade via direct reinforcement
IEEE Transactions on Neural Networks
Accelerated max-margin multiple kernel learning
Applied Intelligence
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A new approach to algorithmic trading system development is presented. This approach, Kernel Price Pattern Trading (KPPT P ), allows the practitioner to link the performance of a learned classifier (that predicts the occurrence of the price pattern P) to the profitability of the system. A positive definite kernel based distance that tries to capture the drivers of the process of price patterns formation and some results about the profitability of the system are also presented.