Stock Price Prediction: LSTM Based Model


Ranjan Kumar Roy
Ezyequity, Kolkata
Koyel Ghosh
Department of Computer Science and Engineering, Central Institute of Technology, Assam
Apurbalal Senapati
Department of Computer Science and Engineering, Central Institute of Technology Kokrajhar, Kokrajhar-783370


Stock price prediction is a critical field used by most business people and common or retail people who tried to increase their money by value with respect to time. People will either gain money or loss their entire life savings in stock market activity. It is a chaos system. Building an accurate model is complex as variation in price depends on multiple factors such as news, social media data, and fundamentals, production of the company, government bonds, historical price and country's economics factor. Prediction model which considers only one factor might not be accurate. Hence incorporating multiple factors news, social media data and historical price might increase the model's accuracy. This paper tried to incorporate the issue when someone implements it as per the model outcome. It cannot give the proper result when someone implements it in real life since capital market data is very sensitive and news-driven. To avoid such a situation, we use the hedging concept when implemented.

July 12, 2021
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