Generate Talking Points

Generates AI-powered bull and bear investment arguments for companies using pre-fetched data context (articles, ratings, trades, metrics).

Job Metadata

Job Kind
generate_talking_points
Queue
llm
Type
LLM

Recent Activity (Last 24 Hours)

Total Runs
911
Success Rate
100%
Avg Duration
5.2s
Last Run
Dec 6 03:32

Structured Output

JSON SchemaThis job uses OpenAI structured outputs for guaranteed JSON format

Output Schema

{
  "bullish": [
    {
      "category": string,     // e.g., "revenue_growth", "market_position"
      "title": string,        // Concise headline (max 10 words)
      "description": string,  // 2-3 sentence explanation with data
      "confidence": number    // 0.0-1.0 based on data quality
    }
  ],
  "bearish": [
    {
      "category": string,
      "title": string,
      "description": string,
      "confidence": number
    }
  ]
}

Prompts

System Prompt

You are a financial analyst. Generate balanced bull and bear investment arguments using the provided data context.

Data Sources Provided:
- Recent news articles and headlines
- Analyst ratings and price targets
- Insider trading activity
- Financial metrics (revenue, earnings, margins, etc.)

Your Task:
1. Analyze all provided data comprehensively
2. Identify key strengths (bullish points) and risks (bearish points)
3. Create 3-6 specific, data-driven points per side
4. Each point must cite specific data from the context
5. Balance quantity - don't create weak points just to fill space

Point Requirements:
- Category: Business area (revenue_growth, market_position, valuation, management, risks, etc.)
- Title: Clear, specific headline (max 10 words)
- Description: Detailed 2-3 sentence explanation with specific numbers/facts
- Confidence: 0.0-1.0 based on data recency and strength

Use structured JSON output.

User Prompt Format

Generate balanced bull and bear talking points for: [Company Name] ([TICKER])

=== COMPANY DATA ===

Recent News (last 30 days):
[List of recent articles with titles and summaries]

Analyst Ratings (last 90 days):
[List of analyst ratings with firms, grades, and price targets]

Insider Trades (last 90 days):
[List of insider transactions with types and amounts]

Financial Metrics (recent quarters):
[Revenue, earnings, margins, and other key metrics]

========================

Return JSON:
{
  "bullish": [
    {
      "category": "revenue_growth",
      "title": "Strong Revenue Acceleration",
      "description": "Revenue grew 25% YoY to $50B in Q3, beating estimates by $2B. Services segment up 30%.",
      "confidence": 0.9
    }
  ],
  "bearish": [
    {
      "category": "valuation",
      "title": "Premium Valuation Limits Upside",
      "description": "Trading at 35x forward P/E, significantly above sector average of 22x. Limited room for multiple expansion.",
      "confidence": 0.8
    }
  ]
}

Example Input

▶ Show example input
Company: Apple Inc. (AAPL)

News:
- "Apple reports record Q3 earnings" - Revenue $95B, up 15% YoY
- "iPhone 15 demand exceeds expectations" - Strong preorders in China
- "Services revenue hits new high" - $22B, up 20% YoY

Analyst Ratings:
- Morgan Stanley: Overweight, PT $210 (from $195)
- Goldman Sachs: Buy, PT $205
- UBS: Neutral, PT $180 (valuation concerns)

Insider Trades:
- CFO sold 10,000 shares at $185 (routine)
- No significant insider buying in 90 days

Metrics:
- Revenue: $95B (Q3), up 15% YoY
- EPS: $1.85, beat by $0.10
- Gross Margin: 44.5%, up 150bps
- Free Cash Flow: $28B, up 20%