Fintech Empowers Prediction of Stock Market Index Using Artificial Neural Network

In today's business era, it is a very difficult to predict the extract value of the stock market index, accordingly the field has a notable scope for research in forecasting the stock price index and it's movement. Diverse factors such as market trends, behavioral finance, economic indicators, exchange rates, gross domestic product growth, interest rates, unemployment, efficient market, stock option and evaluation and value investors. The paper represents and compares the basic types of input variables and modular overview of the variables and its relations to predict the daily stock market. The model consists of 36 kinds of financial and economic features. A model through Artificial Neural Network is developed to predict the daily stock market index. A multi-layer feed forward network is developed to discuss the issues predicting the stock market index. Fintech favors every investor, by bringing more relevant and richer data to our fingertips. Factors are evaluated using python, results are satisfactory.