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market-news-analyst This skill should be used when analyzing recent market-moving news events and their impact on equity markets and commodities. Use this skill when the user requests analysis of major financial news from the past 10 days, wants to understand market reactions to monetary policy decisions (FOMC, ECB, BOJ), needs assessment of geopolitical events' impact on commodities, or requires comprehensive review of earnings announcements from mega-cap stocks. The skill automatically collects news using WebSearch/WebFetch tools and produces impact-ranked analysis reports. All analysis thinking and output are conducted in English.
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name market-news-analyst description This skill should be used when analyzing recent market-moving news events and their impact on equity markets and commodities. Use this skill when the user requests analysis of major financial news from the past 10 days, wants to understand market reactions to monetary policy decisions (FOMC, ECB, BOJ), needs assessment of geopolitical events' impact on commodities, or requires comprehensive review of earnings announcements from mega-cap stocks. The skill automatically collects news using WebSearch/WebFetch tools and produces impact-ranked analysis reports. All analysis thinking and output are conducted in English.
Market News Analyst
Overview
This skill enables comprehensive analysis of market-moving news events from the past 10 days, focusing on their impact on US equity markets and commodities. The skill automatically collects news from trusted sources using WebSearch and WebFetch tools, evaluates market impact magnitude, analyzes actual market reactions, and produces structured English reports ranked by market impact significance.
Prerequisites
Tools: WebSearch and WebFetch tools must be available for news collectionAPI Keys: None required (uses built-in web search capabilities)Knowledge: Familiarity with financial markets terminology is helpful but not required
Output
This skill produces conversational guidance during the analysis session. When the full workflow is executed, Claude generates a comprehensive Markdown report (see Step 6 for format) that can be saved to the reports/ directory upon user request. No files are generated automatically; output is presented in the conversation.
When to Use This Skill
Use this skill when:
User requests analysis of recent major market news (past 10 days)
User wants to understand market reactions to specific events (FOMC decisions, earnings, geopolitical)
User needs comprehensive market news summary with impact assessment
User asks about correlations between news events and commodity price movements
User requests analysis of how central bank policy announcements affected markets
"Analyze the major market news from the past 10 days"
"How did the latest FOMC decision impact the market?"
"What were the most important market-moving events this week?"
"Analyze recent geopolitical news and commodity price reactions"
"Review mega-cap tech earnings and their market impact"
Analysis Workflow Follow this structured 6-step workflow when analyzing market news:
Step 1: News Collection via WebSearch/WebFetch Objective: Gather comprehensive news from the past 10 days covering major market-moving events.
Execute parallel WebSearch queries covering different news categories:
Search: "FOMC meeting past 10 days", "Federal Reserve interest rate", "ECB policy decision", "Bank of Japan"
Target: Central bank decisions, forward guidance changes, inflation commentary
Search: "CPI inflation report [current month]", "jobs report NFP", "GDP data", "PPI producer prices"
Target: Major economic data releases and surprises
Search: "Apple earnings [current quarter]", "Microsoft earnings", "NVIDIA earnings", "Amazon earnings", "Tesla earnings", "Meta earnings", "Google earnings"
Target: Results, guidance, market reactions for largest companies
Search: "Middle East conflict oil prices", "Ukraine war", "US China tensions", "trade war tariffs"
Target: Conflicts, sanctions, trade disputes affecting markets
Search: "oil prices news past week", "gold prices", "OPEC meeting", "natural gas prices", "copper prices"
Target: Supply disruptions, demand shifts, price movements
Search: "major M&A announcement", "bank earnings", "tech sector news", "bankruptcy", "credit rating downgrade"
Target: Large corporate events beyond mega-caps
Recommended News Sources (Priority Order):
Official sources: FederalReserve.gov, SEC.gov (EDGAR), Treasury.gov, BLS.gov
Tier 1 financial news: Bloomberg, Reuters, Wall Street Journal, Financial Times
Specialized: CNBC (real-time), MarketWatch (summaries), S&P Global Platts (commodities)
Use WebSearch for broad topic searches
Use WebFetch for specific URLs from official sources or major news outlets
Collect publication dates to ensure news is within 10-day window
Capture: Event date, source, headline, key details, market context (pre-market, trading hours, after-hours)
Focus on Tier 1 market-moving events (see references/market_event_patterns.md)
Prioritize news with clear market impact (price moves, volume spikes)
Exclude: Stock-specific small-cap news, minor product updates, routine filings
Think in English throughout collection process. Document each significant news item with:
Date and time
Event type (monetary policy, earnings, geopolitical, etc.)
Source reliability tier
Initial market reaction (if observable)
Step 2: Load Knowledge Base References Objective: Access domain expertise to inform impact assessment.
Load relevant reference files based on collected news types:
references/market_event_patterns.md - Comprehensive patterns for all major event typesreferences/trusted_news_sources.md - Source credibility assessment Conditionally Load (Based on News Collected):
If monetary policy news found:
Focus on: market_event_patterns.md → Central Bank Monetary Policy Events section
Key frameworks: Interest rate hike/cut reactions, QE/QT impacts, hawkish/dovish tone
If geopolitical events found:
Load: references/geopolitical_commodity_correlations.md
Focus on: Energy Commodities, Precious Metals, regional frameworks matching event
If mega-cap earnings found:
Load: references/corporate_news_impact.md
Focus on: Specific company sections, sector contagion patterns
Load: references/geopolitical_commodity_correlations.md
Focus on: Specific commodity sections (Oil, Gold, Copper, etc.)
Knowledge Integration:
Compare collected news against historical patterns to:
Predict expected market reactions
Identify anomalies (market reacted differently than historical pattern)
Assess whether reaction was typical magnitude or outsized
Determine if contagion occurred as expected
Step 3: Impact Magnitude Assessment Objective: Rank each news event by market impact significance.
Impact Assessment Framework:
For each news item, evaluate across three dimensions:
1. Asset Price Impact (Primary Factor):
Measure actual or estimated price movements:
Index-level: S&P 500, Nasdaq 100, Dow Jones
Severe: ±2%+ in day
Major: ±1-2%
Moderate: ±0.5-1%
Minor: ±0.2-0.5%
Negligible: <0.2%
Sector-level: Specific sector ETFs
Severe: ±5%+
Major: ±3-5%
Moderate: ±1-3%
Minor: <1%
Stock-specific: Individual mega-caps
Severe: ±10%+ (and index weight causes index move)
Major: ±5-10%
Moderate: ±2-5%
10-Year Treasury Yield:
Severe: ±20bps+ in day
Major: ±10-20bps
Moderate: ±5-10bps
USD Index (DXY):
Severe: ±1.5%+
Major: ±0.75-1.5%
Moderate: ±0.3-0.75%
2. Breadth of Impact (Multiplier):
Assess how many markets/sectors affected:
Systemic (3x multiplier): Multiple asset classes, global markets
Examples: FOMC surprise, banking crisis, major war outbreak
Cross-Asset (2x multiplier): Equities + commodities, or equities + bonds
Examples: Inflation surprise, geopolitical supply shock
Sector-Wide (1.5x multiplier): Entire sector or related sectors
Examples: Tech earnings cluster, energy policy announcement
Stock-Specific (1x multiplier): Single company (unless mega-cap with index impact)
Examples: Individual company earnings, M&A
3. Forward-Looking Significance (Modifier):
Consider future implications:
Regime Change (+50%): Fundamental market structure shift
Examples: Fed pivot from hiking to cutting, major geopolitical realignment
Trend Confirmation (+25%): Reinforces existing trajectory
Examples: Consecutive strong inflation prints, sustained earnings beats
Isolated Event (0%): One-off with limited forward signal
Examples: Single data point within range, company-specific issue
Contrary Signal (-25%): Contradicts prevailing narrative
Examples: Good news ignored by market, bad news rallied
Impact Score Calculation:
Impact Score = (Price Impact Score × Breadth Multiplier) + Forward-Looking Modifier
Price Impact Score:
- Severe: 10 points
- Major: 7 points
- Moderate: 4 points
- Minor: 2 points
- Negligible: 1 point
FOMC 75bps Rate Hike (hawkish tone):
Price Impact: S&P 500 -2.5% (Severe = 10 points)
Breadth: Systemic (equities, bonds, USD, commodities all moved) = 3x
Forward: Trend confirmation (ongoing tightening) = +25%
Score: (10 × 3) × 1.25 = 37.5
Price Impact: NVDA +15%, Nasdaq +1.5% (Severe = 10 points)
Breadth: Sector-wide (semis, tech broadly) = 1.5x
Forward: Trend confirmation (AI demand) = +25%
Score: (10 × 1.5) × 1.25 = 18.75 Geopolitical Flare-up (Middle East):
Price Impact: Oil +8%, S&P -1.2% (Severe = 10 points)
Breadth: Cross-asset (oil, equities, gold) = 2x
Forward: Isolated event (no escalation) = 0%
Score: (10 × 2) × 1.0 = 20 Single Stock Earnings (Non-Mega-Cap):
Price Impact: Stock +12%, no index impact (Major = 7 points)
Breadth: Stock-specific = 1x
Forward: Isolated = 0%
Score: (7 × 1) × 1.0 = 7 Ranking:
After scoring all news items, rank from highest to lowest impact score. This determines report ordering.
Step 4: Market Reaction Analysis Objective: Analyze how markets actually responded to each event.
For each significant news item (Impact Score >5), conduct detailed reaction analysis:
Immediate Reaction (Intraday):
Direction: Positive, negative, mixed
Magnitude: Align with price impact categories
Timing: Pre-market, during trading, after-hours
Volatility: VIX movement, bid-ask spreads
Index performance (S&P 500, Nasdaq, Dow, Russell 2000)
Sector rotation (which sectors outperformed/underperformed)
Individual stock moves (mega-caps, relevant companies)
Growth vs Value, Large vs Small Cap divergences
Treasury yields (2Y, 10Y, 30Y)
Yield curve shape (steepening, flattening, inversion)
Credit spreads (IG, HY)
TIPS breakevens (inflation expectations)
Energy: Oil (WTI, Brent), Natural Gas
Precious Metals: Gold, Silver
Base Metals: Copper, Aluminum (if relevant)
Agricultural: Wheat, Corn, Soybeans (if relevant)
USD Index (DXY)
EUR/USD, USD/JPY, GBP/USD
Emerging market currencies
Safe havens (JPY, CHF)
VIX (volatility index)
Options activity (put/call ratio, unusual volume)
Futures positioning
Compare observed reaction against expected pattern from knowledge base:
Consistent: Reaction matched historical pattern
Example: Fed hike → Tech stocks down, USD up (as expected)
Amplified: Reaction exceeded typical pattern
Example: Inflation print +0.3% above consensus → Selloff 2x typical
Investigate: Positioning, sentiment, cumulative factors
Dampened: Reaction less than historical pattern
Example: Geopolitical event → Oil barely moved
Investigate: Already priced in, other offsetting factors
Inverse: Reaction opposite of historical pattern
Example: Good news ignored, bad news rallied
Investigate: "Good news is bad news" dynamics, Fed pivot hopes
Flag reactions that deviate significantly from patterns:
Market shrugged off typically market-moving news
Overreaction to typically minor news
Contagion failed to spread as expected
Safe havens didn't work (correlations broke)
Risk-On vs Risk-Off: Which regime dominated
Positioning: Evidence of crowded trades unwinding
Momentum: Follow-through in subsequent sessions or reversal
Step 5: Correlation and Causation Assessment Objective: Distinguish direct impacts from coincidental timing.
When multiple significant events occurred in the 10-day period, assess interactions:
Same directional impact
Example: Hawkish FOMC + hot CPI → Both bearish for equities, amplified move
Combined impact often non-linear (greater than sum of parts)
Opposite directional impacts
Example: Strong earnings (positive) + geopolitical tensions (negative) → Muted net reaction
Identify which factor dominated
One event set up reaction to next
Example: First rate hike modest reaction, second rate hike severe (cumulative tightening concerns)
Path dependence matters
Events unrelated but occurred simultaneously
Difficult to isolate individual impacts
Note uncertainty in attribution
Geopolitical-Commodity Correlations:
For geopolitical events, specifically analyze commodity market reactions using geopolitical_commodity_correlations.md:
Map conflict/sanction to supply disruption risk
Assess actual vs feared supply impact
Duration: Temporary spike vs sustained elevation
Safe-haven flows vs real rate drivers
Gold response to risk-off events
Central bank buying implications
Demand destruction from economic slowdown fears
Supply chain disruptions
China factor in copper, aluminum
Black Sea grain exports (Russia-Ukraine)
Weather overlays
Food security policy responses
Trace how news impacts flowed through markets:
News → Immediate asset price reaction
Example: OPEC cuts → Oil prices up immediately
News → Economic impact → Asset prices
Example: Rate hike → Mortgage rates up → Housing slows → Homebuilder stocks down
News → Risk appetite shift → Broad asset reallocation
Example: Banking crisis → Flight to quality → Treasuries rally, stocks sell
Initial reaction creates secondary effects
Example: Stock selloff → Margin calls → Forced selling → Deeper selloff
Step 6: Report Generation Objective: Create structured English Markdown report ranked by market impact.
# Market News Analysis Report - [Date Range]
## Executive Summary
[3-4 sentences covering:]
- Period analyzed (specific dates)
- Number of significant events identified
- Dominant market theme/regime (risk-on/risk-off, sector rotation)
- Top 1-2 highest-impact events
## Market Impact Rankings
[Table format, sorted by Impact Score descending]
| Rank | Event | Date | Impact Score | Asset Classes Affected | Market Reaction |
|------|-------|------|--------------|------------------------|-----------------|
| 1 | [Event] | [Date] | [Score] | [Equities, Commodities, etc.] | [Brief reaction] |
| 2 | ... | ... | ... | ... | ... |
---
## Detailed Event Analysis
[For each event in rank order, provide comprehensive analysis]
### [Rank]. [Event Name] (Impact Score: [X])
**Event Date:** [Date, Time]
**Event Type:** [Monetary Policy / Earnings / Geopolitical / Economic Data / Corporate]
**News Source:** [Source, with credibility tier]
#### Event Summary
[3-4 sentences describing what happened]
- Key details (e.g., rate decision, earnings beat/miss magnitude, conflict developments)
- Context (was this expected, surprise factor)
- Forward guidance or implications stated
#### Market Reaction
**Immediate (Day-of):**
- **Equities:** S&P 500 [+/-X%], Nasdaq [+/-X%], Sector rotation [details]
- **Bonds:** 10Y yield [change], credit spreads [movement]
- **Commodities:** Oil [+/-X%], Gold [+/-X%], Copper [+/-X%] (if relevant)
- **Currencies:** USD [+/-X%], [other relevant pairs]
- **Volatility:** VIX [level/change]
**Follow-Through (Subsequent Sessions):**
- [Direction: sustained, reversed, or consolidated]
- [Additional price action details if significant]
**Pattern Comparison:**
- **Expected Reaction:** [Based on historical patterns from knowledge base]
- **Actual vs Expected:** [Consistent / Amplified / Dampened / Inverse]
- **Explanation of Deviation:** [If applicable, why reaction differed]
#### Impact Assessment Detail
**Asset Price Impact:** [Severe/Major/Moderate/Minor] - [Justification]
**Breadth:** [Systemic/Cross-Asset/Sector/Stock-Specific] - [Affected markets]
**Forward Significance:** [Regime Change/Trend Confirmation/Isolated/Contrary] - [Rationale]
**Calculated Score:** ([Price Score] × [Breadth Multiplier]) × [Forward Modifier] = [Total]
#### Sector-Specific Impacts
[If relevant, detail which sectors/industries were most affected]
- [Sector 1]: [Impact and reason]
- [Sector 2]: [Impact and reason]
- [Example: Technology -3% (rate sensitivity), Energy +5% (oil price spillover)]
#### Geopolitical-Commodity Correlation Analysis
[Include this section only for geopolitical events]
- [Specific commodity affected]: [Price movement]
- [Supply/demand mechanism]: [Explanation]
- [Historical precedent]: [Comparison to similar past events]
- [Expected duration]: [Temporary shock vs sustained impact]
[Repeat detailed analysis for each ranked event]
---
## Thematic Synthesis
### Dominant Market Narrative
[Identify overarching theme across the 10-day period]
- [E.g., "Persistent inflation concerns dominated despite mixed economic data"]
- [E.g., "Tech sector strength drove markets higher despite geopolitical headwinds"]
### Interconnected Events
[Analyze how events related or compounded]
- [Event A] + [Event B] → [Combined impact analysis]
- [Sequential causation if applicable]
### Market Regime Assessment
**Risk Appetite:** [Risk-On / Risk-Off / Mixed]
**Evidence:**
- [Supporting indicators: sector performance, safe haven flows, credit spreads, VIX]
**Sector Rotation Trends:**
- [Growth vs Value]
- [Cyclicals vs Defensives]
- [Outperformers and underperformers]
### Anomalies and Surprises
[Highlight unexpected market reactions]
1. [Event]: Market reacted [unexpectedly] because [explanation]
2. [Continue for significant anomalies]
---
## Commodity Market Deep Dive
[Dedicated section for commodity movements]
### Energy
- **Crude Oil (WTI/Brent):** [Price level, % change over period, key drivers]
- **Natural Gas:** [If significant movement]
- **Key Events:** [Specific news impacting energy: OPEC, geopolitics, inventory data]
### Precious Metals
- **Gold:** [Price level, % change, safe-haven flows vs real rate dynamics]
- **Silver:** [If significant divergence from gold]
- **Drivers:** [Geopolitical risk premium, inflation hedging, USD strength]
### Base Metals
- **Copper:** [As economic barometer - demand signals]
- **Aluminum, Nickel:** [If relevant supply/demand news]
- **China Factor:** [Impact of Chinese economic data/policy]
### Agricultural (If Relevant)
- **Grains:** [Wheat, Corn, Soybeans - weather, Ukraine conflict impacts]
[For each commodity, reference geopolitical events from main analysis and draw correlations]
---
## Forward-Looking Implications
### Market Positioning Insights
[What the news suggests for current market positioning]
- [Trend continuation or reversal signals]
- [Overvaluation or undervaluation indications]
- [Sentiment extremes (complacency or panic)]
### Upcoming Catalysts
[Events on horizon that may be set up by recent news]
- [Next FOMC meeting expectations post-recent decision]
- [Upcoming earnings seasons based on guidance]
- [Geopolitical developments to monitor]
### Risk Scenarios
[Based on recent news, identify key risks]
1. **[Risk Name]:** [Description, probability, potential impact]
2. **[Risk Name]:** [Description, probability, potential impact]
3. [Continue for 3-5 key risks]
---
## Data Sources and Methodology
### News Sources Consulted
[List primary sources used, organized by tier]
- **Official Sources:** [e.g., FederalReserve.gov, SEC.gov]
- **Tier 1 Financial News:** [e.g., Bloomberg, Reuters, WSJ]
- **Specialized:** [e.g., S&P Global Platts for commodities]
### Analysis Period
- **Start Date:** [Specific date]
- **End Date:** [Specific date]
- **Total Days:** 10
### Market Data
- Equity indices: [Data sources]
- Commodity prices: [Data sources]
- Economic data: [Government sources]
### Knowledge Base References
- `market_event_patterns.md` - Historical reaction patterns
- `geopolitical_commodity_correlations.md` - Geopolitical-commodity frameworks
- `corporate_news_impact.md` - Mega-cap impact analysis
- `trusted_news_sources.md` - Source credibility assessment
---
*Analysis Date: [Date report generated]*
*Language: English*
*Analysis Thinking: English*
File Naming Convention:
market_news_analysis_[START_DATE]_to_[END_DATE].md
Example: market_news_analysis_2024-10-25_to_2024-11-03.md
Report Quality Standards:
Objective, fact-based analysis (no speculation beyond probability-weighted scenarios)
Quantify price movements with specific percentages
Cite sources for major claims
Distinguish between correlation and causation
Acknowledge uncertainty when attributing market moves to specific news
Use proper financial terminology
Maintain consistent English throughout
Key Analysis Principles When conducting market news analysis:
Impact Over Noise: Focus on truly market-moving news, filter out minor eventsMulti-Asset Perspective: Analyze across equities, bonds, commodities, currencies to understand full impactPattern Recognition: Compare against historical precedents while noting unique aspectsCausation Discipline: Be rigorous about attributing market moves to specific news vs coincidental timingForward-Looking: Emphasize implications for future market behavior, not just backward-looking descriptionObjectivity: Separate market reaction (what happened) from personal market view (what should happen)Quantification: Use specific numbers (%, bps) rather than vague terms ("significant," "large")Source Credibility: Weight official sources and Tier 1 news over rumors and unverified reportsBreadth Analysis: Individual stock moves only significant if mega-cap or systemic signalEnglish Consistency: All thinking, analysis, and output in English for consistency
Common Pitfalls to Avoid
Not every market move is news-driven (technicals, flows, month-end rebalancing exist)
Acknowledge when attribution is uncertain
Latest news isn't always most important
Rank by actual impact, not chronological order
Distinguish "obvious in retrospect" from "surprising at the time"
Note consensus expectations vs actual outcomes
Markets respond to multiple factors simultaneously
Acknowledge interaction effects
A "hot" CPI that's 0.1% above consensus is different from 0.5% above
Quantify surprise factor
Resources
references/ market_event_patterns.md - Comprehensive knowledge base covering:
Central bank monetary policy events (FOMC, ECB, BOJ, PBOC)
Inflation data releases (CPI, PPI, PCE)
Employment data (NFP, unemployment, wages)
GDP reports
Geopolitical events (conflicts, trade wars, sanctions)
Corporate earnings (mega-cap technology, banks, energy)
Credit events and rating changes
Commodity-specific events (OPEC, weather, supply disruptions)
Recession indicators
Historical case studies (2008 crisis, COVID-19, 2022 inflation)
Pattern recognition framework and sentiment analysis
geopolitical_commodity_correlations.md - Detailed correlations covering:
Energy commodities (crude oil, natural gas, coal) and geopolitical conflicts
Precious metals (gold, silver, platinum, palladium) safe-haven dynamics
Base metals (copper, aluminum, nickel, zinc) and economic/political risks
Agricultural commodities (wheat, corn, soybeans) and weather/policy
Rare earth elements and critical minerals (China dominance, supply security)
Regional geopolitical frameworks (Middle East, Russia-Europe, Asia-Pacific, Latin America)
Correlation summary tables
Time horizon considerations
corporate_news_impact.md - Mega-cap analysis framework:
"Magnificent 7" technology stocks (NVIDIA, Apple, Microsoft, Amazon, Meta, Google, Tesla)
Financial sector mega-caps (JPMorgan, Bank of America, etc.)
Healthcare mega-caps (UnitedHealth, Pfizer, J&J, Merck)
Energy mega-caps (Exxon Mobil, Chevron)
Consumer staples mega-caps (P&G, Coca-Cola, PepsiCo)
Industrial mega-caps (Boeing, Caterpillar)
Earnings impact frameworks, product launches, M&A, regulatory issues
Sector contagion patterns
Impact magnitude framework
trusted_news_sources.md - Source credibility guide:
Tier 1 primary sources (central banks, government agencies, SEC)
Tier 2 major financial news (Bloomberg, Reuters, WSJ, FT, CNBC)
Tier 3 specialized sources (energy, tech, emerging markets, China-specific, crypto)
Tier 4 analysis and research (independent research, central bank publications, think tanks)
Search and aggregation tools
Source quality assessment criteria
Speed vs accuracy trade-offs
Recommended search strategies for 10-day analysis
Source credibility framework
Red flag sources to avoid
Important Notes
All analysis thinking must be conducted in English
All output Markdown files must be in English
Use WebSearch and WebFetch tools to collect news automatically
Focus on trusted news sources as defined in references
Rank events by impact score (price impact × breadth × forward significance)
Target analysis period: Past 10 days from current date
Emphasize US equity markets and commodities as primary analysis subjects
FOMC and other central bank policy decisions receive highest priority analysis
Distinguish between correlation and causation rigorously
Quantify all market reactions with specific percentages
Load appropriate reference files based on news types collected
Generate comprehensive reports ranked by market impact (highest impact first)
