This paper is published in Volume-7, Issue-1, 2021
Area
Information Technology
Author
Aditya Kadam, Akshay Hake, Pravin Salunkhe, Piyush Agrawal
Org/Univ
Pune Institute of Computer Technology, Pune, Maharashtra, India
Pub. Date
05 March, 2021
Paper ID
V7I1-1242
Publisher
Keywords
Sentiment Analysis, Deep Learning, Stock Market, Data Mining, Web Scraping

Citationsacebook

IEEE
Aditya Kadam, Akshay Hake, Pravin Salunkhe, Piyush Agrawal. Stock price prediction using sentiment analysis of business domains and company-related news data, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Aditya Kadam, Akshay Hake, Pravin Salunkhe, Piyush Agrawal (2021). Stock price prediction using sentiment analysis of business domains and company-related news data. International Journal of Advance Research, Ideas and Innovations in Technology, 7(1) www.IJARIIT.com.

MLA
Aditya Kadam, Akshay Hake, Pravin Salunkhe, Piyush Agrawal. "Stock price prediction using sentiment analysis of business domains and company-related news data." International Journal of Advance Research, Ideas and Innovations in Technology 7.1 (2021). www.IJARIIT.com.

Abstract

The stock price of a company is volatile in nature but when considering long-term prediction of the stock price, it is dependent on the company's business model and feasibility of the environment for the company to work. This data related to company and domains in which the company works is available on the internet through news media but it is an arduous task for one to keep track of all this data and perform predictions on stock prices. The proposed model in this paper takes sentiment from this available data and provides a prediction of the stock price in the future with the deliberation of the market environment.