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Performance Analysis of MLPFF Neural Network Back Propagation Training Algorithms for Time Series Data
11
Citations
25
References
2014
Year
Unknown Venue
EngineeringMachine LearningTime Series DataRecurrent Neural NetworkData ScienceAlgorithmic TradingTraining AlgorithmNonlinear Time SeriesVarious Training AlgorithmPredictive AnalyticsTrading ModelForecasting AccuracyForecastingSignal ProcessingFinanceIntelligent ForecastingPerformance AnalysisBusinessStock Market PredictionFinancial Forecast
This paper investigates the various training algorithm with Multi-Layer Perceptron Feed Forward Neural Network (MLPFFNN) and identify the best training algorithm for Indian Stock Exchange Market especially for BSE100 and NIFTY MIDCAP50. The forecasting accuracy is analyzed and measured with reference to an Indian stock market index such as Bombay Stock Exchange (BSE) and NIFTY MIDCAP50 in this study and it is found that the best training algorithm is Levenberg-Marquardt. All Training algorithms uses the 1-5-1 MLPFFNN architecture and its various parameter such as epochs, learning rate, etc are studied and the results are tabulated for the data division ratio 60%, 20% and 20% which represents training, validating and testing for all training algorithm.
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