Earnings Call Intelligence for Investment Research
For investment firms analyzing 1000+ earnings calls quarterly. Extract sentiment, key metrics, and management signals. 85% faster research coverage.
Hedge funds, asset managers, and equity research teams who need to efficiently analyze earnings calls across large portfolios
Analysts cannot listen to all relevant earnings calls in real-time. Critical management signals and sentiment shifts are missed, leading to delayed investment decisions
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Why Mixpeek
85% faster research coverage, real-time alerts on sentiment shifts, and comparative analysis across quarters and competitors
Overview
Earnings calls contain crucial signals beyond the numbers. This use case shows how Mixpeek helps investment teams extract alpha from management commentary at scale.
Challenges This Solves
Call Volume
1000+ earnings calls per quarter across covered companies
Impact: Impossible for analysts to attend/listen to all relevant calls
Real-Time Requirements
Markets react within minutes of earnings commentary
Impact: Delayed analysis means missed trading opportunities
Qualitative Signals
Management tone, hedging language, confidence shifts
Impact: Subjective interpretation, inconsistent analysis
Comparative Context
Need to compare vs prior quarters and competitors
Impact: Manual comparison is time-consuming and error-prone
Implementation Steps
Mixpeek transcribes and analyzes earnings call audio, extracting key metrics, sentiment by topic, management tone shifts, and comparisons to previous quarters
Ingest Earnings Calls
Process earnings call audio in real-time
import { Mixpeek } from 'mixpeek';const client = new Mixpeek({ apiKey: process.env.MIXPEEK_API_KEY });// Process earnings call as it happensasync function processEarningsCall(callUrl: string, metadata: {ticker: string;quarter: string;year: number;company_name: string;}) {return client.extract({url: callUrl,extractors: ['speech-to-text', // Full transcription'speaker-diarization', // CEO vs CFO vs analyst'sentiment-analysis', // By speaker and topic'entity-extraction', // Metrics, guidance, products'topic-segmentation' // Segment by discussion topic],settings: {languages: ['en'],speaker_labels: ['ceo', 'cfo', 'analyst', 'operator'],compare_to: `${metadata.ticker}-Q${parseInt(metadata.quarter)-1}-${metadata.year}`},metadata: metadata});}
Extract Key Signals
Identify metrics, guidance, and sentiment
// Extract structured data from callasync function analyzeEarningsCall(callId: string) {const analysis = await client.retrieve({collection_id: 'earnings-calls',document_id: callId,return_fields: ['transcript','sentiment_by_topic','extracted_metrics','guidance_statements','management_tone']});return {// Quantitative extractionsmetrics: {revenue_mentioned: analysis.extracted_metrics.revenue,eps_mentioned: analysis.extracted_metrics.eps,guidance_changes: analysis.guidance_statements},// Qualitative signalssentiment: {overall: analysis.sentiment_by_topic.overall,by_topic: analysis.sentiment_by_topic.breakdown,ceo_confidence: analysis.management_tone.ceo,cfo_confidence: analysis.management_tone.cfo},// Notable languagehedging_detected: analysis.hedging_language,unusual_phrases: analysis.unusual_vs_historical,// Q&A dynamicsanalyst_sentiment: analysis.analyst_questions_sentiment,management_deflections: analysis.deflection_count};}
Compare Across Time
Track changes vs prior quarters
// Compare to historical callsasync function compareToHistory(ticker: string, currentQuarter: string) {const history = await client.retrieve({collection_id: 'earnings-calls',filters: {ticker: ticker,quarter: { $lt: currentQuarter }},sort: { quarter: 'desc' },limit: 4 // Last 4 quarters});const current = await client.retrieve({collection_id: 'earnings-calls',filters: { ticker: ticker, quarter: currentQuarter }});return {sentiment_trend: calculateTrend(history, current, 'sentiment'),tone_shift: detectToneShift(history[0], current),new_topics: findNewTopics(history, current),dropped_topics: findDroppedTopics(history, current),guidance_changes: compareGuidance(history[0], current)};}
Set Up Real-Time Alerts
Get notified on significant signals
// Configure alerts for significant eventsawait client.alerts.create({collection_id: 'earnings-calls',name: 'Sentiment Shift Alert',conditions: [{field: 'sentiment.overall',operator: 'change_from_prior',threshold: 0.2 // 20% sentiment shift},{field: 'guidance_statements',operator: 'contains',values: ['lowered', 'reduced', 'decreased', 'challenging']},{field: 'management_tone.ceo',operator: 'below',threshold: 0.4 // Low confidence detected}],destinations: ['slack', 'email'],priority: 'high'});
Feature Extractors Used
Retriever Stages Used
Expected Outcomes
85% faster analysis across portfolio companies
Research Coverage
Real-time alerts within 30 seconds of key statements
Alert Latency
40% more sentiment signals detected vs manual analysis
Signal Detection
3x more companies covered per analyst
Analyst Productivity
Instant comparison to 20+ quarters of history
Historical Context
Frequently Asked Questions
Related Resources
Related Comparisons
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