ABSTRACT
Stock price prediction is a highly uncertain and money making approach. There a lot of methods and tools used for this purpose. In this research paper, we present a hybrid deep neural network for prediction of stock prices. This model will predict the day closing price of any stock on the basis of certain parameters. This hybrid model will be the integration of fuzzy inference system with the deep neural network. Fuzzy inference system has the capability to handle the uncertain information but it has the limitation that it cannot learn from the example sets. Deep neural network with more than one hidden layer has the capability to learn from the experience but it cannot handle the uncertain information. If these two models are integrated together then the resulting model can learn from the examples and can handle the uncertain information. In this paper will make some predictions through this model and it will be tested on multiple stocks.
