--- name: scenario-analyzer description: Analyze news headlines, policy announcements, or geopolitical events to build 18-month probabilistic scenarios for Indian markets. Use when the user provides a headline or asks about the market impact of RBI policy, government announcements, global events, budget, or sector-specific news on NSE/BSE stocks. --- # Scenario Analyzer (India Markets) ## Overview This skill takes a news headline or event and builds probabilistic 18-month scenarios with cascading 1st, 2nd, and 3rd order sector impacts and specific stock recommendations for the Indian market. ## Architecture ``` Skill (Orchestrator) ├── Phase 1: Preparation │ ├── Headline parsing (keywords, entities, actions, numbers) │ ├── Event classification │ └── Load references ├── Phase 2: Analysis │ ├── Collect related news (past 2 weeks via WebSearch) │ ├── Build 3 scenarios (Base/Bull/Bear, probabilities sum to 100%) │ ├── Map 1°/2°/3° sector impacts │ └── Identify 3-5 positive + 3-5 negative impact stocks └── Phase 3: Report Generation ├── Compile findings ├── Assess scenario probability distribution └── Save report ``` ## Event Classification Classify the headline into one of these categories: | Category | Indian Context Examples | |----------|----------------------| | **Monetary Policy** | RBI rate decision, CRR/SLR change, liquidity measures | | **Fiscal Policy** | Union Budget, GST changes, PLI schemes, disinvestment | | **Geopolitical** | India-China border, India-Pakistan, Russia-Ukraine, Middle East | | **Commodity** | Crude oil shock, gold prices, metal tariffs, food inflation | | **Regulatory** | SEBI rules, RBI NPA norms, telecom spectrum, pharma FDA | | **Corporate** | Major M&A, earnings surprise, promoter pledging, fraud | | **Global Macro** | Fed rate decision, US recession, China slowdown, tariffs | | **Weather/Agriculture** | Monsoon forecast, crop damage, food prices | | **Elections/Political** | State elections, central govt policy shifts | ## Workflow ### Phase 1: Preparation 1. **Parse the Headline** - Extract key entities (companies, sectors, countries, institutions) - Identify the action (increase, decrease, ban, approve, delay) - Note any numbers (rate changes, ₹ amounts, percentages) - Classify the event type 2. **Load References** ``` Read: references/headline_event_patterns.md Read: references/sector_sensitivity_matrix.md Read: references/scenario_playbooks.md ``` ### Phase 2: Analysis 3. **Collect Context** - Use WebSearch to find related news from the past 2 weeks - Identify any pre-existing trends or expectations - Note market's initial reaction if available 4. **Build 3 Scenarios** For each scenario: - **Name**: Descriptive title - **Probability**: Must sum to 100% across all 3 - **Timeline**: 3 phases (0-6 months, 6-12 months, 12-18 months) - **Description**: What unfolds in each phase - **Key Assumptions**: What must hold true Typical structure: - **Base Case (40-55%)**: Most likely outcome given current trajectory - **Bull Case (20-35%)**: Optimistic scenario with positive catalysts - **Bear Case (15-30%)**: Pessimistic scenario with adverse developments 5. **Map Sector Impacts** For each scenario, assess impacts using the sector sensitivity matrix: | Order | Definition | Example (RBI Rate Cut) | |-------|-----------|----------------------| | 1st | Direct, immediate | Banks: NIM compression, Housing: demand boost | | 2nd | Indirect, 3-6 months | Auto: loan demand, Real estate: prices | | 3rd | Tertiary, 6-18 months | Cement: construction demand, Durables: consumer spending | Use NSE sectoral indices: - Nifty Bank, Nifty IT, Nifty Pharma, Nifty Auto, Nifty FMCG - Nifty Metal, Nifty Realty, Nifty Energy, Nifty Infra - Nifty PSU Bank, Nifty Private Bank, Nifty Financial Services 6. **Identify Stock Impacts** For each scenario: - 3-5 stocks that benefit most (positive impact) - 3-5 stocks that suffer most (negative impact) For each stock, provide: - Ticker (NSE symbol) - Current price (use broker MCP `get_ltp` — Groww or Zerodha Kite — if available) - Impact channel (why this stock is affected) - Magnitude estimate (High/Medium/Low) ### Phase 3: Report Generation 7. **Generate Report** Save as `reports/scenario_analysis__YYYYMMDD.md` with sections: 1. **Related News** (5-10 recent articles with sources) 2. **Scenario Overview** (3 scenarios with probabilities) 3. **Timeline** (0-6m, 6-12m, 12-18m phases for base case) 4. **Sector Impact Matrix** (1°/2°/3° impacts per sector) 5. **Positive Impact Stocks** (3-5 with rationale) 6. **Negative Impact Stocks** (3-5 with rationale) 7. **Investment Implications** (actionable takeaways) 8. **Risk to Scenarios** (what could shift probabilities) 9. **Disclaimer** ## Quality Standards - All probabilities must sum to 100% - Every impact claim must have a causal chain (event → mechanism → impact) - Stock picks must include the impact channel, not just "will benefit" - Consider second-order effects (e.g., rate cut → weak INR → IT sector benefit) - Flag any confirmation bias in scenario construction - Include both sectors that benefit AND those that lose ## Example Usage ``` User: "RBI cuts repo rate by 25 bps to 6%" Analyst: 1. Classification: Monetary Policy 2. Key entities: RBI, repo rate, 25 bps, 6% 3. Collects recent RBI commentary and market expectations 4. Scenarios: - Base (50%): One more cut expected → banks pass on, housing demand rises - Bull (30%): Cycle of 75-100 bps cuts → strong credit growth, equity rally - Bear (20%): Global inflation returns → RBI pauses → rate-sensitive sell-off 5. 1° impacts: Banks, NBFCs, Housing Finance, Auto 6. 2° impacts: Real Estate, Consumer Durables 7. 3° impacts: Cement, Infrastructure 8. Stock picks: HDFCBANK, BAJFINANCE, GODREJPROP (positive); IT exporters if INR weakens ``` ## Resources ### references/headline_event_patterns.md Historical Indian market event patterns and reactions. ### references/sector_sensitivity_matrix.md Event type × NSE sector impact matrix. ### references/scenario_playbooks.md Scenario construction templates with Indian market context.