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
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
Load References
Read: references/headline_event_patterns.md
Read: references/sector_sensitivity_matrix.md
Read: references/scenario_playbooks.md
Phase 2: Analysis
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
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
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
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
Generate Report
Save as reports/scenario_analysis_<topic>_YYYYMMDD.md with sections:
- Related News (5-10 recent articles with sources)
- Scenario Overview (3 scenarios with probabilities)
- Timeline (0-6m, 6-12m, 12-18m phases for base case)
- Sector Impact Matrix (1°/2°/3° impacts per sector)
- Positive Impact Stocks (3-5 with rationale)
- Negative Impact Stocks (3-5 with rationale)
- Investment Implications (actionable takeaways)
- Risk to Scenarios (what could shift probabilities)
- 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.
1---2name: scenario-analyzer3description: 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.4---5
6# Scenario Analyzer (India Markets)
7
8## Overview
9
10This 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.
11
12## Architecture
13
14```
15Skill (Orchestrator)
16├── Phase 1: Preparation
17│ ├── Headline parsing (keywords, entities, actions, numbers)
18│ ├── Event classification
19│ └── Load references
20├── Phase 2: Analysis
21│ ├── Collect related news (past 2 weeks via WebSearch)
22│ ├── Build 3 scenarios (Base/Bull/Bear, probabilities sum to 100%)
23│ ├── Map 1°/2°/3° sector impacts
24│ └── Identify 3-5 positive + 3-5 negative impact stocks
25└── Phase 3: Report Generation
26 ├── Compile findings
27 ├── Assess scenario probability distribution
28 └── Save report
29```
30
31## Event Classification
32
33Classify the headline into one of these categories:
34
35| Category | Indian Context Examples |
36|----------|----------------------|
37| **Monetary Policy** | RBI rate decision, CRR/SLR change, liquidity measures |
38| **Fiscal Policy** | Union Budget, GST changes, PLI schemes, disinvestment |
39| **Geopolitical** | India-China border, India-Pakistan, Russia-Ukraine, Middle East |
40| **Commodity** | Crude oil shock, gold prices, metal tariffs, food inflation |
41| **Regulatory** | SEBI rules, RBI NPA norms, telecom spectrum, pharma FDA |
42| **Corporate** | Major M&A, earnings surprise, promoter pledging, fraud |
43| **Global Macro** | Fed rate decision, US recession, China slowdown, tariffs |
44| **Weather/Agriculture** | Monsoon forecast, crop damage, food prices |
45| **Elections/Political** | State elections, central govt policy shifts |
46
47## Workflow
48
49### Phase 1: Preparation
50
511. **Parse the Headline**
52 - Extract key entities (companies, sectors, countries, institutions)
53 - Identify the action (increase, decrease, ban, approve, delay)
54 - Note any numbers (rate changes, ₹ amounts, percentages)
55 - Classify the event type
56
572. **Load References**
58 ```
59 Read: references/headline_event_patterns.md
60 Read: references/sector_sensitivity_matrix.md
61 Read: references/scenario_playbooks.md
62 ```
63
64### Phase 2: Analysis
65
663. **Collect Context**
67 - Use WebSearch to find related news from the past 2 weeks
68 - Identify any pre-existing trends or expectations
69 - Note market's initial reaction if available
70
714. **Build 3 Scenarios**
72
73 For each scenario:
74 - **Name**: Descriptive title
75 - **Probability**: Must sum to 100% across all 3
76 - **Timeline**: 3 phases (0-6 months, 6-12 months, 12-18 months)
77 - **Description**: What unfolds in each phase
78 - **Key Assumptions**: What must hold true
79
80 Typical structure:
81 - **Base Case (40-55%)**: Most likely outcome given current trajectory
82 - **Bull Case (20-35%)**: Optimistic scenario with positive catalysts
83 - **Bear Case (15-30%)**: Pessimistic scenario with adverse developments
84
855. **Map Sector Impacts**
86
87 For each scenario, assess impacts using the sector sensitivity matrix:
88
89 | Order | Definition | Example (RBI Rate Cut) |
90 |-------|-----------|----------------------|
91 | 1st | Direct, immediate | Banks: NIM compression, Housing: demand boost |
92 | 2nd | Indirect, 3-6 months | Auto: loan demand, Real estate: prices |
93 | 3rd | Tertiary, 6-18 months | Cement: construction demand, Durables: consumer spending |
94
95 Use NSE sectoral indices:
96 - Nifty Bank, Nifty IT, Nifty Pharma, Nifty Auto, Nifty FMCG
97 - Nifty Metal, Nifty Realty, Nifty Energy, Nifty Infra
98 - Nifty PSU Bank, Nifty Private Bank, Nifty Financial Services
99
1006. **Identify Stock Impacts**
101
102 For each scenario:
103 - 3-5 stocks that benefit most (positive impact)
104 - 3-5 stocks that suffer most (negative impact)
105
106 For each stock, provide:
107 - Ticker (NSE symbol)
108 - Current price (use broker MCP `get_ltp` — Groww or Zerodha Kite — if available)
109 - Impact channel (why this stock is affected)
110 - Magnitude estimate (High/Medium/Low)
111
112### Phase 3: Report Generation
113
1147. **Generate Report**
115
116 Save as `reports/scenario_analysis_<topic>_YYYYMMDD.md` with sections:
117
118 1. **Related News** (5-10 recent articles with sources)
119 2. **Scenario Overview** (3 scenarios with probabilities)
120 3. **Timeline** (0-6m, 6-12m, 12-18m phases for base case)
121 4. **Sector Impact Matrix** (1°/2°/3° impacts per sector)
122 5. **Positive Impact Stocks** (3-5 with rationale)
123 6. **Negative Impact Stocks** (3-5 with rationale)
124 7. **Investment Implications** (actionable takeaways)
125 8. **Risk to Scenarios** (what could shift probabilities)
126 9. **Disclaimer**
127
128## Quality Standards
129
130- All probabilities must sum to 100%
131- Every impact claim must have a causal chain (event → mechanism → impact)
132- Stock picks must include the impact channel, not just "will benefit"
133- Consider second-order effects (e.g., rate cut → weak INR → IT sector benefit)
134- Flag any confirmation bias in scenario construction
135- Include both sectors that benefit AND those that lose
136
137## Example Usage
138
139```
140User: "RBI cuts repo rate by 25 bps to 6%"
141
142Analyst:
1431. Classification: Monetary Policy
1442. Key entities: RBI, repo rate, 25 bps, 6%
1453. Collects recent RBI commentary and market expectations
1464. Scenarios:
147 - Base (50%): One more cut expected → banks pass on, housing demand rises
148 - Bull (30%): Cycle of 75-100 bps cuts → strong credit growth, equity rally
149 - Bear (20%): Global inflation returns → RBI pauses → rate-sensitive sell-off
1505. 1° impacts: Banks, NBFCs, Housing Finance, Auto
1516. 2° impacts: Real Estate, Consumer Durables
1527. 3° impacts: Cement, Infrastructure
1538. Stock picks: HDFCBANK, BAJFINANCE, GODREJPROP (positive); IT exporters if INR weakens
154```
155
156## Resources
157
158### references/headline_event_patterns.md
159Historical Indian market event patterns and reactions.
160
161### references/sector_sensitivity_matrix.md
162Event type × NSE sector impact matrix.
163
164### references/scenario_playbooks.md
165Scenario construction templates with Indian market context.