Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Understanding the Impact of News on Stock Market Trends Using Natural Language Processing and Machine Learning Algorithms


Affiliations
1 Department of Information Technology, Bharati Vidyapeeth’s College of Engineering, New Delhi, India
     

   Subscribe/Renew Journal


Short-term trading, specifically day-trading involves a high risk concerning monetary resources. Investing money becomes risky without adequate know-ledge and understanding of factors governing the market, some of which include public sentiment, commodity prices, political stability, etc. News is a common way via which people get updates about the latest happenings around the world and hence form opinions about industries, companies, stocks, etc. This affects their trading decisions; substantially impacting their chances of making a profit. Our research focused on building software models that could analyze general news during trading hours and predict the probable stock index closing trend for the end of that day. We used top 25 articles from the Reddit World News Channel and tried to correlate their impact on the DJIA in this study. Using two approaches to the process the text and further deploying machine learning models, we achieved fairly acceptable prediction accuracies.

Keywords

Dow Jones Industrial Average, K-Nearest Neighbors, Logistic Regression, Multi-layer Perceptron, N-gram Model, Reddit World News Channel, Sentiment Analysis.
Subscription Login to verify subscription
User
Notifications
Font Size



  • Understanding the Impact of News on Stock Market Trends Using Natural Language Processing and Machine Learning Algorithms

Abstract Views: 323  |  PDF Views: 0

Authors

Alka Leekha
Department of Information Technology, Bharati Vidyapeeth’s College of Engineering, New Delhi, India
Arnav Wadhwa
Department of Information Technology, Bharati Vidyapeeth’s College of Engineering, New Delhi, India
Nikhil Jain
Department of Information Technology, Bharati Vidyapeeth’s College of Engineering, New Delhi, India
Mehul Wadhwa
Department of Information Technology, Bharati Vidyapeeth’s College of Engineering, New Delhi, India

Abstract


Short-term trading, specifically day-trading involves a high risk concerning monetary resources. Investing money becomes risky without adequate know-ledge and understanding of factors governing the market, some of which include public sentiment, commodity prices, political stability, etc. News is a common way via which people get updates about the latest happenings around the world and hence form opinions about industries, companies, stocks, etc. This affects their trading decisions; substantially impacting their chances of making a profit. Our research focused on building software models that could analyze general news during trading hours and predict the probable stock index closing trend for the end of that day. We used top 25 articles from the Reddit World News Channel and tried to correlate their impact on the DJIA in this study. Using two approaches to the process the text and further deploying machine learning models, we achieved fairly acceptable prediction accuracies.

Keywords


Dow Jones Industrial Average, K-Nearest Neighbors, Logistic Regression, Multi-layer Perceptron, N-gram Model, Reddit World News Channel, Sentiment Analysis.

References