Prediction of Stock Prices based on Historical Data using Linear Regression Model through LSTM Algorithm

In general, the stock market can be considered as a major component of the free market and one of the crucial pillars of the economy of any country. In a globalized world where the stock markets have brought in a revolution, the upgradation of stock prices in the financial sector has witnessed a profound change. The current trade and prediction rate has focused on the challenges and understanding of the financial sector with an emphasis on the growth of the industry. The upliftment of technological demand concerning the financial sector is to underline the importance of the present as well as future prediction(s) in stock prices. Concerning this paper, the LSTM algorithm has been implemented to predict stock prices and enable non-risk investments. To increase the performance and obtain an appropriate result, the efficient model of Linear Regression has also been utilized. The future enhancement of this work is extensively based on sentimental analysis associated with reference to the public opinions being indicated in the form of tweets.