Forecasting of Stock Market Indices Using Artificial Neural Network

This paper presents a computational approach for predicting the S&P CNX Nifty 50 Index. A neural network based model has been used in predicting the direction of the movement of the closing value for the next day of trading. The model presented in the paper also confirms that it can be used to predict price trend of the stock market. After studying the various features of the network model, a suitable model for stocks forecast is proposed. The model has used the preprocessed data set of closing value of S&P CNX Nifty 50 Index. The training data set encompasses the trading days from 1st January, 2015 to 30th November, 2016. The test data set encompasses the trading days from 1st January, 2016 to 31st December, 2016. Accuracy of the performance of the neural network is compared with buy and hold return of the index. The model generated returns of 68.4% against buy and hold return of 6.35%. The average accuracy of target forecasting is found to be 87%.