Applying News and Media Sentiment Analysis for Generating Forex Trading Signals
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:...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Financial University
2023-01-01
|
| Series: | Review of Business and Economics Studies |
| Subjects: | |
| Online Access: | https://rbes.fa.ru/jour/article/view/304/229 |
| _version_ | 1797229405728145408 |
|---|---|
| author | Oluwafemi F. Olaiyapo |
| author_facet | Oluwafemi F. Olaiyapo |
| author_sort | Oluwafemi F. Olaiyapo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-24T15:12:04Z |
| format | Article |
| id | doaj.art-bc3d2e7960c145668d6d71f0c211b603 |
| institution | Directory Open Access Journal |
| issn | 2308-944X 2311-0279 |
| language | English |
| last_indexed | 2024-04-24T15:12:04Z |
| publishDate | 2023-01-01 |
| publisher | Financial University |
| record_format | Article |
| series | Review of Business and Economics Studies |
| spelling | doaj.art-bc3d2e7960c145668d6d71f0c211b6032024-04-02T10:53:35ZengFinancial UniversityReview of Business and Economics Studies2308-944X2311-02792023-01-011148494https://doi.org/10.26794/2308-944X-2023-11-4-84-94Applying News and Media Sentiment Analysis for Generating Forex Trading SignalsOluwafemi F. Olaiyapo0https://orcid.org/0009-0000-8147-0204Emory UniversityThe 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.https://rbes.fa.ru/jour/article/view/304/229forex marketsentimenttrading signalsforeign exchangecurrenciessocial medianaïve bayesmachine learning |
| spellingShingle | Oluwafemi F. Olaiyapo Applying News and Media Sentiment Analysis for Generating Forex Trading Signals Review of Business and Economics Studies forex market sentiment trading signals foreign exchange currencies social media naïve bayes machine learning |
| title | Applying News and Media Sentiment Analysis for Generating Forex Trading Signals |
| title_full | Applying News and Media Sentiment Analysis for Generating Forex Trading Signals |
| title_fullStr | Applying News and Media Sentiment Analysis for Generating Forex Trading Signals |
| title_full_unstemmed | Applying News and Media Sentiment Analysis for Generating Forex Trading Signals |
| title_short | Applying News and Media Sentiment Analysis for Generating Forex Trading Signals |
| title_sort | applying news and media sentiment analysis for generating forex trading signals |
| topic | forex market sentiment trading signals foreign exchange currencies social media naïve bayes machine learning |
| url | https://rbes.fa.ru/jour/article/view/304/229 |
| work_keys_str_mv | AT oluwafemifolaiyapo applyingnewsandmediasentimentanalysisforgeneratingforextradingsignals |