Publication | Open Access
Performance Evaluation of ANFIS and GA-ANFIS for Predicting Stock Market Indices
22
Citations
10
References
2021
Year
EngineeringStock Market IndicesEvolving Intelligent SystemUnited StatesEconomic ForecastingData ScienceManagementGenetic AlgorithmFuzzy OptimizationStatisticsFuzzy LogicPredictive AnalyticsQuantitative FinanceForecastingFinanceEvolutionary ProgrammingFinancial AnalyticsNeuro-fuzzy SystemEvolutionary AlgorithmFuzzy Expert SystemStock Market PredictionFinancial Forecast
A model of Adaptive Neuro-Fuzzy Inference System (ANFIS) trained with an evolutionary algorithm, namely Genetic Algorithm (GA) is presented in this paper. Further, the model is tested on the NASDAQ stock market indices which is among the most widely followed indices in the United States. Empirical results show that by determining the parameters of ANFIS (premise and consequent parameters) using GA, we can improve performance in terms of Mean Squared Error (MSE), Root Mean Squared Error (RMSE), coefficient of determination (R-Squared) in comparison with using solely ANFIS.
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