News-based trading strategies use natural language processing techniques to analyze news articles and events to identify trading signals. Researchers designed an algorithm to track the sentiment of news articles about specific companies and industries, and to generate buy or sell signals based on changes in sentiment. The algorithm was backtested on a large dataset of news articles and company stock prices, and showed potential for generating profitable trading strategies based on interpreting the implications of major news events.