Best LLMs for Catalyst And Scenario Analysis

Output schema

Every answer on this task is checked against this JSON Schema, whichever model wrote it. An answer that doesn't fit counts as a model failure, and the call is retried on another model.

{
  "$defs": {
    "RecommendationStrength": {
      "description": "Strength levels for trading recommendations",
      "enum": [
        "LOW",
        "MEDIUM",
        "HIGH"
      ],
      "title": "RecommendationStrength",
      "type": "string"
    },
    "RecommendationType": {
      "description": "Trading recommendation types",
      "enum": [
        "BULLISH",
        "BEARISH"
      ],
      "title": "RecommendationType",
      "type": "string"
    },
    "SentimentBreakdown": {
      "description": "Breakdown of sentiment analysis across sources",
      "properties": {
        "negative_sources": {
          "description": "Number of sources with negative sentiment",
          "minimum": 0,
          "title": "Negative Sources",
          "type": "integer"
        },
        "neutral_sources": {
          "description": "Number of sources with neutral sentiment",
          "minimum": 0,
          "title": "Neutral Sources",
          "type": "integer"
        },
        "overall_sentiment_score": {
          "description": "Overall sentiment score from -100 (very bearish) to +100 (very bullish)",
          "maximum": 100,
          "minimum": -100,
          "title": "Overall Sentiment Score",
          "type": "number"
        },
        "positive_sources": {
          "description": "Number of sources with positive sentiment",
          "minimum": 0,
          "title": "Positive Sources",
          "type": "integer"
        }
      },
      "required": [
        "positive_sources",
        "negative_sources",
        "neutral_sources",
        "overall_sentiment_score"
      ],
      "title": "SentimentBreakdown",
      "type": "object"
    }
  },
  "description": "Trading recommendation schema for bullish/bearish analysis\nBased on news sentiment and market intelligence",
  "example": {
    "confidence_score": 78.5,
    "key_catalysts": [
      "Q4 delivery numbers exceeded expectations",
      "Cybertruck production ramp announcement",
      "Energy storage segment growth"
    ],
    "market_context_notes": "Tech sector showing strength, EV subsidy policies supportive",
    "next_review_triggers": [
      "Next week's production update",
      "Competitor earnings releases",
      "Federal Reserve meeting outcome"
    ],
    "recommendation": "BULLISH",
    "recommendation_strength": "HIGH",
    "risk_factors": [
      "Regulatory scrutiny on autonomous driving",
      "Increased EV competition",
      "Supply chain constraints"
    ],
    "sentiment_breakdown": {
      "negative_sources": 20,
      "neutral_sources": 15,
      "overall_sentiment_score": 42.3,
      "positive_sources": 65
    },
    "subject_code": "TSLA",
    "supporting_evidence": [
      "Deliveries up 15% QoQ based on company announcement",
      "Wall Street analyst consensus upgrade to $280 price target",
      "Social sentiment strongly positive following earnings call"
    ],
    "timeline_expectations": "2-5 trading days, high conviction for weekly cycle",
    "total_sources_analyzed": 100
  },
  "properties": {
    "confidence_score": {
      "description": "Confidence level in the recommendation (0-100)",
      "maximum": 100,
      "minimum": 0,
      "title": "Confidence Score",
      "type": "number"
    },
    "expected_pct_change": {
      "anyOf": [
        {
          "maximum": 100,
          "minimum": -100,
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Expected percentage change in price based on analysis",
      "title": "Expected Pct Change"
    },
    "key_catalysts": {
      "anyOf": [
        {
          "items": {
            "type": "string"
          },
          "type": "array"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Primary market-moving events or factors driving the recommendation",
      "example": [
        "Earnings beat expectations",
        "New product launch",
        "Analyst upgrade"
      ],
      "title": "Key Catalysts"
    },
    "market_context_notes": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Additional context about broader market conditions affecting the analysis",
      "title": "Market Context Notes"
    },
    "next_review_triggers": {
      "anyOf": [
        {
          "items": {
            "type": "string"
          },
          "type": "array"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Specific events, dates, or conditions that should prompt recommendation review",
      "example": [
        "Weekly earnings report",
        "Fed announcement",
        "Product launch date"
      ],
      "title": "Next Review Triggers"
    },
    "recommendation": {
      "$ref": "#/$defs/RecommendationType",
      "description": "Trading recommendation: BULLISH (buy calls/long) or BEARISH (puts/short)"
    },
    "recommendation_strength": {
      "$ref": "#/$defs/RecommendationStrength",
      "description": "Strength of the recommendation based on evidence quality and consensus"
    },
    "risk_factors": {
      "anyOf": [
        {
          "items": {
            "type": "string"
          },
          "type": "array"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Key risks that could negatively impact the recommendation",
      "example": [
        "Market volatility",
        "Regulatory concerns",
        "Competitive pressure"
      ],
      "title": "Risk Factors"
    },
    "sentiment_breakdown": {
      "anyOf": [
        {
          "$ref": "#/$defs/SentimentBreakdown"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Detailed breakdown of source sentiment analysis"
    },
    "subject_code": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Stock ticker symbol or entity identifier",
      "example": "AAPL",
      "title": "Subject Code"
    },
    "supporting_evidence": {
      "anyOf": [
        {
          "items": {
            "type": "string"
          },
          "maxItems": 10,
          "type": "array"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Key quotes, facts, or data points from sources supporting the recommendation",
      "title": "Supporting Evidence"
    },
    "timeframe_days": {
      "anyOf": [
        {
          "minimum": 1,
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "expected_pct_change is expected in timeframe_days",
      "title": "Timeframe Days"
    },
    "timeline_expectations": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Expected timeframe for recommendation validity and price movement",
      "example": "1-3 trading days, subject to weekly review",
      "title": "Timeline Expectations"
    },
    "total_sources_analyzed": {
      "anyOf": [
        {
          "minimum": 1,
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Total number of source documents analyzed",
      "title": "Total Sources Analyzed"
    }
  },
  "required": [
    "recommendation",
    "confidence_score",
    "recommendation_strength"
  ],
  "title": "TradingRecommendation",
  "type": "object"
}