Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Pattern Discovery of Fuzzy Time Series for Financial Prediction
IEEE Transactions on Knowledge and Data Engineering
Representing financial time series based on data point importance
Engineering Applications of Artificial Intelligence
Surveying stock market forecasting techniques - Part II: Soft computing methods
Expert Systems with Applications: An International Journal
Financial market trading system with a hierarchical coevolutionary fuzzy predictive model
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
The use of data mining and neural networks for forecasting stock market returns
Expert Systems with Applications: An International Journal
Daily stock prediction using neuro-genetic hybrids
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Concurrency and Computation: Practice & Experience
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Neurofuzzy approaches for predicting financial time series are investigated and shown to perform well in the context of various trading strategies involving stocks and options. The horizon of prediction is typically a few days and trading strategies are examined using historical data. Two methodologies are presented wherein neural predictors are used to anticipate the general behavior of financial indexes (moving up, down, or staying constant) in the context of stocks and options trading. The methodologies are tested with actual financial data and show considerable promise as a decision making and planning tool