Earnings Call Analyzer (NLP Sentiment)

The Earnings Call Analyzer in Company Research uses natural language processing to extract sentiment and key themes from a company's earnings call transcripts.

How to use it

On any company's research page, select the Earnings Analysis model. The card shows the most recent quarter's transcript scored across four dimensions:

• Tone — how positive or negative management's language was overall.
• Confidence — how strongly management hedged versus committed.
• Q&A evasiveness — how often executives sidestepped analyst questions.
• Topic shifts — what topics got more or less airtime versus prior quarters.

What you see

• A directional tilt (Bullish, Neutral, Bearish, Mixed) with a confidence level (Low, Moderate, High).
• The 4-quarter trend on each metric.
• The top topics from the transcript.
• A list of positive and negative signals that justified the tilt.

Important caveats

Earnings-call NLP produces a signal, not a prediction. Academic research on similar techniques shows roughly 55–60% directional accuracy over 5–10 day windows for mid-caps — meaningful but modest edge. Use it alongside fundamental analysis, not as a replacement.

Sources

Transcripts are sourced from Financial Modeling Prep. Sentiment scoring uses the Loughran-McDonald financial dictionary, the academic standard for finance text analysis.