Deep Learning Based Model to Forecast the Direction of Stock Exchange Market Using social media

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Miss. Rutuja Patil, Prof. Nagaraju Bogiri

Abstract

A company’s stock exchange price is not just a measure of the present worth of the value of its shares, but an indicator of its expected future performance as well. The company is an incorporated organisation with the Regulatory Body and shares trading members are registered with SEBI. Given that stock market statistics are extremely time-specific and usually nonlinear in nature, it is very difficult to forecast future stock values. The forecast offers details about the present state of the flow of inventory values. This will also be used to decide whether to purchase or sell the individual shares of the particular stock for consumers. Many scientists were conducted with different data mining techniques to forecast stock market prices. This paper attempts to forecast the stock price of companies in the national stock exchange index LIX15 using Neural Network technology. For designing and training the models, the past data of the chosen stock will be used. To verify the consistency of the model, the effects of the model are used for comparison with actual data.

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