Applying News and Media Sentiment Analysis for Generating Forex Trading Signals
https://doi.org/10.26794/2308-944X-2023-11-4-84-94
Abstract
The objective of this research is to examine how sentiment analysis can be employed to generate trading signals for the Foreign Exchange (Forex) market.
The author assessed sentiment in social media posts and news articles pertaining to the United States Dollar (USD) using a combination of methods: lexicon-based analysis and the Naive Bayes machine learning algorithm.
The findings indicate that sentiment analysis proves valuable in forecasting market movements and devising trading signals. Notably, its effectiveness is consistent across different market conditions.
The author concludes that by analyzing sentiment expressed in news and social media, traders can glean insights into prevailing market sentiments towards the USD and other pertinent countries, thereby aiding trading decision-making. This study underscores the importance of weaving sentiment analysis into trading strategies as a pivotal tool for predicting market dynamics.
About the Author
O. F. Olaiyapo
Emory University
United States
United States
Oluwafemi F. Olaiyapo — Graduate Student, Department of Mathematics
Atlanta
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Review
For citations:
Olaiyapo O.F. Applying News and Media Sentiment Analysis for Generating Forex Trading Signals. Review of Business and Economics Studies. 2023;11(4):84-94. https://doi.org/10.26794/2308-944X-2023-11-4-84-94
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