Authors: Shobhit Nigam
Investing in stock market requires a lot of expertise and ability to pick the right stock at the right time and to be able to reap high rewards. In the last few years, several financial analysts and portfolio managers have turned their analyzing technical analysis of a stock price using artificial neural network. Artificial neural network is a powerful technique in recognizing various hidden clues for when stock prices will rise or fall. This work is concerned in predicting the closing price of a stock using artificial neural network which can effectively predict the stock prices based on the available data. A single multiplicative neuron model (SMN) has been proposed in this work and trained using standard backpropagation learning algorithm. The validation of the proposed model has been performed on two stocks of different sectors, entertainment and cement sector which are listed in Bombay Stock Exchange (BSE). Different sectors have been considered to evaluate the efficiency of the proposed model and the results obtained using the proposed model has significantly outperformed. The proposed model can also be used as an indicator for an investor while investing in stock market to benefit from volatility and reducing risk which gives opportunity to create wealth.
Keywords: Artificial Neural Network, Financial Market, Single Multiplicative Neuron Model, Stock Price Prediction.