Sentiment Analysis
The use of natural language processing and data analysis to gauge market participants' emotions and opinions about a stock or the market.
Explained Simply
Sentiment analysis in trading goes beyond just reading headlines. It includes NLP analysis of news articles, social media posts, earnings call transcripts, and SEC filings. Quantitative sentiment measures like the put/call ratio, VIX, Fear & Greed Index, and short interest provide additional data points. Extreme sentiment readings are contrarian indicators — extreme fear often marks bottoms and extreme greed marks tops.
How Tradewink Uses Sentiment Analysis
Tradewink uses FinBERT (a finance-specialized NLP model) to analyze news headlines and earnings call transcripts in real-time. Sentiment scores from -1 (bearish) to +1 (bullish) are factored into signal generation. The Finnhub news WebSocket streams headlines 24/7, and sentiment shifts in real-time influence conviction scores. Aggregate social sentiment from multiple sources is included in the daily market pulse.
Related Terms
See Sentiment Analysis in action
Tradewink uses sentiment analysis as part of its AI trading signal pipeline. Start getting signals that use this concept to find real opportunities.