Indian Stock Market Prediction Using Differential Evolutionary Neural Network Model
نویسندگان
چکیده
This paper presents a scheme using Differential Evolution based Functional Link Artificial Neural Network (FLANN) to predict the Indian Stock Market Indices. The Model uses Back-Propagation (BP) algorithm and Differential Evolution (DE) algorithm respectively for predicting the Stock Price Indices for one day, one week, two weeks and one month in advance. The Indian stock prices i.e. BSE (Bombay Stock Exchange), NSE, INFY etc. with few technical indicators are considered as input for the experimental data. In all the cases, DE outperforms the BP algorithm. The Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) are calculated for performance evaluation. The MAPE and RMSE in case of DE are found to be very less in comparison to BP method. The simulation study has been done using Java-6 and NetBeans. Keywords-Stock Market Prediction; Functional Link Neural (FLANN); Differential evolution (DE); Back Propagation (BP) Algorithm; Least Mean Square (LMS) method.
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