{"title":"应用新闻和媒体情绪分析生成外汇交易信号","authors":"Oluwafemi F Olaiyapo","doi":"arxiv-2403.00785","DOIUrl":null,"url":null,"abstract":"The objective of this research is to examine how sentiment analysis can be\nemployed to generate trading signals for the Foreign Exchange (Forex) market.\nThe author assessed sentiment in social media posts and news articles\npertaining to the United States Dollar (USD) using a combination of methods:\nlexicon-based analysis and the Naive Bayes machine learning algorithm. The\nfindings indicate that sentiment analysis proves valuable in forecasting market\nmovements and devising trading signals. Notably, its effectiveness is\nconsistent across different market conditions. The author concludes that by\nanalyzing sentiment expressed in news and social media, traders can glean\ninsights into prevailing market sentiments towards the USD and other pertinent\ncountries, thereby aiding trading decision-making. This study underscores the\nimportance of weaving sentiment analysis into trading strategies as a pivotal\ntool for predicting market dynamics.","PeriodicalId":501139,"journal":{"name":"arXiv - QuantFin - Statistical Finance","volume":"52 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applying News and Media Sentiment Analysis for Generating Forex Trading Signals\",\"authors\":\"Oluwafemi F Olaiyapo\",\"doi\":\"arxiv-2403.00785\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this research is to examine how sentiment analysis can be\\nemployed to generate trading signals for the Foreign Exchange (Forex) market.\\nThe author assessed sentiment in social media posts and news articles\\npertaining to the United States Dollar (USD) using a combination of methods:\\nlexicon-based analysis and the Naive Bayes machine learning algorithm. The\\nfindings indicate that sentiment analysis proves valuable in forecasting market\\nmovements and devising trading signals. Notably, its effectiveness is\\nconsistent across different market conditions. The author concludes that by\\nanalyzing sentiment expressed in news and social media, traders can glean\\ninsights into prevailing market sentiments towards the USD and other pertinent\\ncountries, thereby aiding trading decision-making. This study underscores the\\nimportance of weaving sentiment analysis into trading strategies as a pivotal\\ntool for predicting market dynamics.\",\"PeriodicalId\":501139,\"journal\":{\"name\":\"arXiv - QuantFin - Statistical Finance\",\"volume\":\"52 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Statistical Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2403.00785\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Statistical Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2403.00785","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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:
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.