Stock Market Trend Analysis on Indian Financial News Headlines with Natural Language Processing
- Title
- Stock Market Trend Analysis on Indian Financial News Headlines with Natural Language Processing
- Creator
- Saxena A.; Vijay Bhagat V.; Tamang A.
- Description
- Predicting the stock movement in the real-time scenario has been the most challenging and sophisticated in business. This business is affected by several factors from physical to psychological as well as rational to irrational. So far only few aspects have been taken into account while breaking down the conclusion. Implementing sentiment analysis, a subfield of Natural Language Processing (NLP), from the news, social media or financial document, investors decide whether they should invest for the company. The results have shown a significant and a feasible method for predicting the stock market trend with higher accuracy. The current research has mainly focus on finding the sentiment score from the news headlines and finding the hidden trend from it. Further the trading signals are generated based on the prevailing trend and trends are executed by the automated trading system. Using this algorithm, traders can reduce the manual intervention in the buy and sell decisions related to the stock market. 2021 IEEE.
- Source
- 2021 Asian Conference on Innovation in Technology, ASIANCON 2021
- Date
- 2021-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Data Mining; Machine Learning; NLP; Sentiment Analysis; stock prediction; Trend Analysis
- Coverage
- Saxena A., Christ (Deemed to Be University), Bangalore, India; Vijay Bhagat V., Christ (Deemed to Be University), Bangalore, India; Tamang A., Independent Consultant, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-172818583-5
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Saxena A.; Vijay Bhagat V.; Tamang A., “Stock Market Trend Analysis on Indian Financial News Headlines with Natural Language Processing,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/20476.