Evolving Fuzzy Modeling for Stock Market Forecasting
Stock market forecasting plays an important role in risk management, asset pricing and portfolio analysis. Stock prices involve non-linear dynamics and uncertainties due to their high volatility and noisy environments. Forecasting modeling with adaptive and high performance accuracy is a major requirement in this case. This paper addresses a new approach for stock market forecast within the framework of evolving fuzzy rule-based modeling, a form of adaptive fuzzy modeling. US and Brazilian stock market data are used to evaluate modeling characteristics and forecasting performance. The results show the high potential of evolving fuzzy models to describe stock market behavior accurately. The evolving modeling approach reveals the essential capability to detect structural changes arising from complex dynamics and instabilities like financial crisis.
KeywordsEvolving Fuzzy Systems Stock Price Forecasting Rule-Based Models Adaptive Systems
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