Earnings Call Statistics Database
A comprehensive reference database of earnings call statistics: coverage volume, AI sentiment analysis accuracy, processing efficiency, market impact, and technology adoption. Updated for 2026.
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- • 2.5M+ earnings transcripts are now AI-searchable across 15,000+ companies
- • AI beats human analysts on EPS prediction accuracy: 68% vs 61%
- • 62% of asset managers now use NLP for earnings call analysis
- • 60% of stock volatility occurs on just 10-15 earnings days per year
- • AI processes earnings calls 5-8x faster than human analysts
Earnings Call Coverage & Volume
AI Sentiment Analysis Accuracy
Processing & Analysis Efficiency
Financial Impact & Market Reaction
Technology & Tooling
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Frequently Asked Questions
How many earnings call transcripts are available for AI analysis?
Over 2.5 million transcripts are available across 15,000+ public companies globally. US coverage is highest at 94% with AI-searchable transcripts.
How accurate is AI sentiment analysis of earnings calls?
AI sentiment analysis predicts post-earnings stock direction with 58% accuracy based on management tone alone. For binary bullish/bearish classification, accuracy reaches 81%. AI beats human EPS predictions by 7 percentage points (68% vs 61%).
How much faster is AI earnings analysis than human analysis?
AI completes a full earnings call analysis in approximately 45 minutes, compared to 4-6 hours for human-only analysis - a 5-8x speed advantage. AI can also process 12x more transcripts per day.
What percentage of total stock volatility occurs on earnings days?
60% of annual stock volatility occurs on earnings days, which represent only 10-15 trading days per year. This makes earnings analysis important for investors.