market-news-analyst

$29

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

Example user requests:

• "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.

Search Strategy:

Execute parallel WebSearch queries covering different news categories:

Monetary Policy:

• 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

Inflation/Economic Data:

• Search: "CPI inflation report [current month]", "jobs report NFP", "GDP data", "PPI producer prices"

• Target: Major economic data releases and surprises

Mega-Cap Earnings:

• 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

Geopolitical Events:

• Search: "Middle East conflict oil prices", "Ukraine war", "US China tensions", "trade war tariffs"

• Target: Conflicts, sanctions, trade disputes affecting markets

Commodity Markets:

• Search: "oil prices news past week", "gold prices", "OPEC meeting", "natural gas prices", "copper prices"

• Target: Supply disruptions, demand shifts, price movements

Corporate News:

• 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)

Search Execution:

• 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)

Filtering Criteria:

• 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:

Always Load:

• references/market_event_patterns.md - Comprehensive patterns for all major event types

• references/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

If commodity news found:

• 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:

Equity Markets:

-

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%

Commodity Markets:

-

Oil (WTI/Brent):

• Severe: ±5%+

• Major: ±3-5%

• Moderate: ±1-3%

-

Gold:

• Severe: ±3%+

• Major: ±1.5-3%

• Moderate: ±0.5-1.5%

-

Base Metals (Copper, etc.):

• Severe: ±4%+

• Major: ±2-4%

• Moderate: ±1-2%

Bond Markets:

• 10-Year Treasury Yield:

• Severe: ±20bps+ in day

• Major: ±10-20bps

• Moderate: ±5-10bps

Currency Markets:

• 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&#x26;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

Example Calculations:

FOMC 75bps Rate Hike (hawkish tone):

• Price Impact: S&#x26;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

NVIDIA Earnings Beat:

• 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&#x26;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

Multi-Asset Response:

Equities:

• Index performance (S&#x26;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

Fixed Income:

• Treasury yields (2Y, 10Y, 30Y)

• Yield curve shape (steepening, flattening, inversion)

• Credit spreads (IG, HY)

• TIPS breakevens (inflation expectations)

Commodities:

• Energy: Oil (WTI, Brent), Natural Gas

• Precious Metals: Gold, Silver

• Base Metals: Copper, Aluminum (if relevant)

• Agricultural: Wheat, Corn, Soybeans (if relevant)

Currencies:

• USD Index (DXY)

• EUR/USD, USD/JPY, GBP/USD

• Emerging market currencies

• Safe havens (JPY, CHF)

Derivatives:

• VIX (volatility index)

• Options activity (put/call ratio, unusual volume)

• Futures positioning

Pattern Comparison:

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

Anomaly Identification:

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)

Sentiment Indicators:

• 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.

Multi-Event Analysis:

When multiple significant events occurred in the 10-day period, assess interactions:

Reinforcing Events:

• Same directional impact

• Example: Hawkish FOMC + hot CPI → Both bearish for equities, amplified move

• Combined impact often non-linear (greater than sum of parts)

Offsetting Events:

• Opposite directional impacts

• Example: Strong earnings (positive) + geopolitical tensions (negative) → Muted net reaction

• Identify which factor dominated

Sequential Events:

• One event set up reaction to next

• Example: First rate hike modest reaction, second rate hike severe (cumulative tightening concerns)

• Path dependence matters

Coincidental Timing:

• 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:

Energy:

• Map conflict/sanction to supply disruption risk

• Assess actual vs feared supply impact

• Duration: Temporary spike vs sustained elevation

Precious Metals:

• Safe-haven flows vs real rate drivers

• Gold response to risk-off events

• Central bank buying implications

Industrial Metals:

• Demand destruction from economic slowdown fears

• Supply chain disruptions

• China factor in copper, aluminum

Agriculture:

• Black Sea grain exports (Russia-Ukraine)

• Weather overlays

• Food security policy responses

Transmission Mechanisms:

Trace how news impacts flowed through markets:

Direct Channel:

• News → Immediate asset price reaction

• Example: OPEC cuts → Oil prices up immediately

Indirect Channels:

• News → Economic impact → Asset prices

• Example: Rate hike → Mortgage rates up → Housing slows → Homebuilder stocks down

Sentiment Channel:

• News → Risk appetite shift → Broad asset reallocation

• Example: Banking crisis → Flight to quality → Treasuries rally, stocks sell

Feedback Loops:

• 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.

Report Structure:

# 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 events

• Multi-Asset Perspective: Analyze across equities, bonds, commodities, currencies to understand full impact

• Pattern Recognition: Compare against historical precedents while noting unique aspects

• Causation Discipline: Be rigorous about attributing market moves to specific news vs coincidental timing

• Forward-Looking: Emphasize implications for future market behavior, not just backward-looking description

• Objectivity: 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 reports

• Breadth Analysis: Individual stock moves only significant if mega-cap or systemic signal

• English Consistency: All thinking, analysis, and output in English for consistency

Common Pitfalls to Avoid

Over-Attribution:

• Not every market move is news-driven (technicals, flows, month-end rebalancing exist)

• Acknowledge when attribution is uncertain

Recency Bias:

• Latest news isn't always most important

• Rank by actual impact, not chronological order

Hindsight Bias:

• Distinguish "obvious in retrospect" from "surprising at the time"

• Note consensus expectations vs actual outcomes

Single-Factor Analysis:

• Markets respond to multiple factors simultaneously

• Acknowledge interaction effects

Ignoring Magnitude:

• 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&#x26;J, Merck)

• Energy mega-caps (Exxon Mobil, Chevron)

• Consumer staples mega-caps (P&#x26;G, Coca-Cola, PepsiCo)

• Industrial mega-caps (Boeing, Caterpillar)

• Earnings impact frameworks, product launches, M&#x26;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)