Hybridizing Exponential Smoothing and Neural Network for Financial Time Series Predication
In this study, a hybrid synergy model integrating exponential smoothing and neural network is proposed for financial time series prediction. The proposed model attempts to incorporate the linear characteristics of an exponential smoothing model and nonlinear patterns of neural network to create a “synergetic” model via the linear programming technique. For verification, two real-world financial time series are used for testing purpose.
KeywordsRoot Mean Square Error Artificial Neural Network Model Exponential Smoothing Time Series Forecast Financial Time Series
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