Marxia Oli. Sigo, Murugesan Selvam, Balasundram Maniam, Desti Kannaiah, Chinnadurai Kathiravan, Thanikachalam Vadivel
The world has become data driven, which highly accentuated the utilization of information technology. The movements of stock markets are influenced, by both the micro as well as macro economic variables including the legal framework and taxation policies of the respective economies. The crux of the issue lies in exactly forecasting the future stock price movements of individual firms and stock indices, based on historical past prices. The accuracy, in forecasting the market trend, has become difficult due to the prevalence of stochastic behaviour and volatility in the stock prices and index movements. This paper analyses the nonlinear movement pattern of the most volatile, top three stocks in terms of market capitalization, listed in the Bombay Stock Exchange (BSE) in India, namely Reliance Industries Limited (RIL), Tata Consultancy Services (TCS) Limited and HDFC Bank Limited, using the Artificial Neural Network (ANN) for the study period from 2008 to 2017. The findings of the study would help the investors, to make rational, well informed investment decisions, to optimize the stock returns by investing in the most valuable stocks.