market-news-analyst by tradermonty/claude-trading-skills
npx skills add https://github.com/tradermonty/claude-trading-skills --skill market-news-analyst此技能支持对过去10天内影响市场的新闻事件进行全面分析,重点关注其对美国股票市场和商品市场的影响。该技能利用 WebSearch 和 WebFetch 工具自动从可信来源收集新闻,评估市场影响程度,分析实际市场反应,并生成按市场影响重要性排序的结构化英文报告。
此技能在分析会话期间提供对话式指导。当完整的工作流程执行后,Claude 会生成一份全面的 Markdown 报告(格式见步骤6),可根据用户请求保存到 reports/ 目录。不会自动生成文件;输出内容在对话中呈现。
在以下情况使用此技能:
示例用户请求:
分析市场新闻时遵循此结构化6步工作流程:
目标: 收集过去10天内涵盖主要市场驱动事件的全面新闻。
搜索策略:
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触达数万 AI 开发者,精准高效
执行并行 WebSearch 查询,涵盖不同的新闻类别:
货币政策:
通胀/经济数据:
大型公司财报:
地缘政治事件:
商品市场:
公司新闻:
推荐新闻来源(优先级顺序):
搜索执行:
筛选标准:
在整个收集过程中用英语思考。记录每个重要新闻项目,包括:
目标: 获取领域专业知识以指导影响评估。
根据收集到的新闻类型加载相关参考文件:
始终加载:
references/market_event_patterns.md - 所有主要事件类型的全面模式references/trusted_news_sources.md - 来源可信度评估有条件加载(基于收集的新闻):
如果发现货币政策新闻:
如果发现地缘政治事件:
references/geopolitical_commodity_correlations.md如果发现大型公司财报:
references/corporate_news_impact.md如果发现商品新闻:
references/geopolitical_commodity_correlations.md知识整合: 将收集的新闻与历史模式进行比较,以:
目标: 按市场影响重要性对每个新闻事件进行排序。
影响评估框架:
对每个新闻项目,从三个维度进行评估:
1. 资产价格影响(主要因素):
衡量实际或估计的价格变动:
股票市场:
商品市场:
债券市场:
货币市场:
2. 影响广度(乘数):
评估有多少市场/行业受到影响:
3. 前瞻性意义(修正因子):
考虑未来影响:
影响分数计算:
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
计算示例:
FOMC 加息75个基点(鹰派基调):
NVIDIA 盈利超预期:
地缘政治紧张局势升级(中东):
单只股票财报(非大型公司):
排序: 对所有新闻项目评分后,按影响分数从高到低排序。这决定了报告的顺序。
目标: 分析市场对每个事件的实际反应。
对每个重要新闻项目(影响分数 >5)进行详细反应分析:
即时反应(日内):
多资产反应:
股票:
固定收益:
商品:
货币:
衍生品:
模式比较:
将观察到的反应与知识库中的预期模式进行比较:
异常识别:
标记与模式显著偏离的反应:
情绪指标:
目标: 区分直接影响与巧合时机。
多事件分析:
当10天期间发生多个重要事件时,评估其相互作用:
强化事件:
抵消事件:
连续事件:
巧合时机:
地缘政治-商品相关性:
对于地缘政治事件,使用 geopolitical_commodity_correlations.md 专门分析商品市场反应:
能源:
贵金属:
工业金属:
农产品:
传导机制:
追踪新闻影响如何通过市场传导:
直接渠道:
间接渠道:
情绪渠道:
反馈循环:
目标: 创建按市场影响排序的结构化英文 Markdown 报告。
报告结构:
# 市场新闻分析报告 - [日期范围]
## 执行摘要
[3-4句话涵盖:]
- 分析期间(具体日期)
- 识别出的重要事件数量
- 主导市场主题/机制(风险偏好/风险规避、行业轮动)
- 前1-2个最高影响事件
## 市场影响排名
[表格格式,按影响分数降序排序]
| 排名 | 事件 | 日期 | 影响分数 | 受影响的资产类别 | 市场反应 |
|------|-------|------|--------------|------------------------|-----------------|
| 1 | [事件] | [日期] | [分数] | [股票、商品等] | [简要反应] |
| 2 | ... | ... | ... | ... | ... |
---
## 详细事件分析
[按排名顺序为每个事件提供全面分析]
### [排名]. [事件名称] (影响分数: [X])
**事件日期:** [日期, 时间]
**事件类型:** [货币政策 / 财报 / 地缘政治 / 经济数据 / 公司]
**新闻来源:** [来源, 含可信度等级]
#### 事件摘要
[3-4句话描述发生了什么]
- 关键细节(例如:利率决定、盈利超预期/不及预期的幅度、冲突进展)
- 背景(这是预期的还是意外因素)
- 前瞻指引或所述影响
#### 市场反应
**即时(当天):**
- **股票:** S&P 500 [+/-X%], Nasdaq [+/-X%], 行业轮动 [细节]
- **债券:** 10年期收益率 [变化], 信用利差 [变动]
- **商品:** 石油 [+/-X%], 黄金 [+/-X%], 铜 [+/-X%](如果相关)
- **货币:** 美元 [+/-X%], [其他相关货币对]
- **波动性:** VIX [水平/变化]
**后续(后续交易日):**
- [方向:持续、反转或盘整]
- [如果显著,提供额外的价格走势细节]
**模式比较:**
- **预期反应:** [基于知识库的历史模式]
- **实际 vs 预期:** [一致 / 放大 / 减弱 / 反向]
- **偏差解释:** [如果适用,解释反应不同的原因]
#### 影响评估详情
**资产价格影响:** [严重/重大/中等/轻微] - [理由]
**广度:** [系统性/跨资产/全行业/个股特定] - [受影响的市场]
**前瞻性意义:** [制度转变/趋势确认/孤立/相反] - [理由]
**计算分数:** ([价格分数] × [广度乘数]) × [前瞻修正因子] = [总分]
#### 行业特定影响
[如果相关,详细说明哪些行业/产业受影响最大]
- [行业 1]: [影响及原因]
- [行业 2]: [影响及原因]
- [示例:科技 -3%(利率敏感性),能源 +5%(油价溢出效应)]
#### 地缘政治-商品相关性分析
[仅针对地缘政治事件包含此部分]
- [受影响的特定商品]: [价格变动]
- [供应/需求机制]: [解释]
- [历史先例]: [与类似过去事件的比较]
- [预期持续时间]: [暂时性冲击 vs 持续影响]
[为每个排名事件重复详细分析]
---
## 主题综合
### 主导市场叙事
[识别10天期间的首要主题]
- [例如:"尽管经济数据好坏参半,但持续的通胀担忧占主导"]
- [例如:"尽管存在地缘政治阻力,但科技行业强势推动市场走高"]
### 相互关联的事件
[分析事件如何相关或复合]
- [事件 A] + [事件 B] → [综合影响分析]
- [如果适用,连续因果关系]
### 市场机制评估
**风险偏好:** [风险偏好 / 风险规避 / 混合]
**证据:**
- [支持指标:行业表现、避险资金流、信用利差、VIX]
**行业轮动趋势:**
- [成长股 vs 价值股]
- [周期性 vs 防御性]
- [跑赢者和跑输者]
### 异常与意外
[突出意外的市场反应]
1. [事件]: 市场反应 [意外地] 因为 [解释]
2. [对显著异常情况继续]
---
## 商品市场深度分析
[商品走势的专门部分]
### 能源
- **原油 (WTI/布伦特):** [价格水平、期间百分比变化、关键驱动因素]
- **天然气:** [如果变动显著]
- **关键事件:** [影响能源的特定新闻:OPEC、地缘政治、库存数据]
### 贵金属
- **黄金:** [价格水平、百分比变化、避险资金流 vs 实际利率动态]
- **白银:** [如果与黄金显著背离]
- **驱动因素:** [地缘政治风险溢价、通胀对冲、美元强弱]
### 基本金属
- **铜:** [作为经济晴雨表 - 需求信号]
- **铝、镍:** [如果相关供应/需求新闻]
- **中国因素:** [中国经济数据/政策的影响]
### 农产品(如果相关)
- **谷物:** [小麦、玉米、大豆 - 天气、乌克兰冲突影响]
[对每种商品,参考主要分析中的地缘政治事件并绘制相关性]
---
## 前瞻性影响
### 市场仓位洞察
[新闻对当前市场仓位的启示]
- [趋势延续或反转信号]
- [高估或低估迹象]
- [情绪极端(自满或恐慌)]
### 即将到来的催化剂
[近期新闻可能引发的未来事件]
- [近期决策后对下次 FOMC 会议的预期]
- [基于指引的即将到来的财报季]
- [需要监控的地缘政治进展]
### 风险情景
[基于近期新闻,识别关键风险]
1. **[风险名称]:** [描述、概率、潜在影响]
2. **[风险名称]:** [描述、概率、潜在影响]
3. [继续列出3-5个关键风险]
---
## 数据来源与方法论
### 咨询的新闻来源
[按等级列出主要使用的来源]
- **官方来源:** [例如:FederalReserve.gov, SEC.gov]
- **一级财经新闻:** [例如:Bloomberg, Reuters, WSJ]
- **专业媒体:** [例如:S&P Global Platts 用于商品]
### 分析期间
- **开始日期:** [具体日期]
- **结束日期:** [具体日期]
- **总天数:** 10
### 市场数据
- 股票指数: [数据来源]
- 商品价格: [数据来源]
- 经济数据: [政府来源]
### 知识库参考文件
- `market_event_patterns.md` - 历史反应模式
- `geopolitical_commodity_correlations.md` - 地缘政治-商品框架
- `corporate_news_impact.md` - 大型公司影响分析
- `trusted_news_sources.md` - 来源可信度评估
---
*分析日期: [报告生成日期]*
*语言: 英文*
*分析思考: 英文*
文件命名约定: market_news_analysis_[开始日期]_to_[结束日期].md
示例:market_news_analysis_2024-10-25_to_2024-11-03.md
报告质量标准:
进行市场新闻分析时:
过度归因:
近期偏差:
后见之明偏差:
单因素分析:
忽略幅度:
market_event_patterns.md - 涵盖以下内容的全面知识库:
geopolitical_commodity_correlations.md - 涵盖以下内容的详细相关性:
corporate_news_impact.md - 大型公司分析框架:
trusted_news_sources.md - 来源可信度指南:
每周安装次数
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仓库
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首次出现
2026年1月26日
安全审计
安装于
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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.
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.
Use this skill when:
Example user requests:
Follow this structured 6-step workflow when analyzing market news:
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:
Inflation/Economic Data:
Mega-Cap Earnings:
Geopolitical Events:
Commodity Markets:
Corporate News:
Recommended News Sources (Priority Order):
Search Execution:
Filtering Criteria:
Think in English throughout collection process. Document each significant news item with:
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 typesreferences/trusted_news_sources.md - Source credibility assessmentConditionally Load (Based on News Collected):
If monetary policy news found:
If geopolitical events found:
references/geopolitical_commodity_correlations.mdIf mega-cap earnings found:
references/corporate_news_impact.mdIf commodity news found:
references/geopolitical_commodity_correlations.mdKnowledge Integration: Compare collected news against historical patterns to:
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
Sector-level: Specific sector ETFs
Stock-specific: Individual mega-caps
Commodity Markets:
Oil (WTI/Brent):
Gold:
Base Metals (Copper, etc.):
Bond Markets:
Currency Markets:
2. Breadth of Impact (Multiplier):
Assess how many markets/sectors affected:
Systemic (3x multiplier): Multiple asset classes, global markets
Cross-Asset (2x multiplier): Equities + commodities, or equities + bonds
Sector-Wide (1.5x multiplier): Entire sector or related sectors
Stock-Specific (1x multiplier): Single company (unless mega-cap with index impact)
3. Forward-Looking Significance (Modifier):
Consider future implications:
Regime Change (+50%): Fundamental market structure shift
Trend Confirmation (+25%): Reinforces existing trajectory
Isolated Event (0%): One-off with limited forward signal
Contrary Signal (-25%): Contradicts prevailing narrative
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):
NVIDIA Earnings Beat:
Geopolitical Flare-up (Middle East):
Single Stock Earnings (Non-Mega-Cap):
Ranking: After scoring all news items, rank from highest to lowest impact score. This determines report ordering.
Objective: Analyze how markets actually responded to each event.
For each significant news item (Impact Score >5), conduct detailed reaction analysis:
Immediate Reaction (Intraday):
Multi-Asset Response:
Equities:
Fixed Income:
Commodities:
Currencies:
Derivatives:
Pattern Comparison:
Compare observed reaction against expected pattern from knowledge base:
Consistent: Reaction matched historical pattern
Amplified: Reaction exceeded typical pattern
Dampened: Reaction less than historical pattern
Inverse: Reaction opposite of historical pattern
Anomaly Identification:
Flag reactions that deviate significantly from patterns:
Sentiment Indicators:
Objective: Distinguish direct impacts from coincidental timing.
Multi-Event Analysis:
When multiple significant events occurred in the 10-day period, assess interactions:
Reinforcing Events:
Offsetting Events:
Sequential Events:
Coincidental Timing:
Geopolitical-Commodity Correlations:
For geopolitical events, specifically analyze commodity market reactions using geopolitical_commodity_correlations.md:
Energy:
Precious Metals:
Industrial Metals:
Agriculture:
Transmission Mechanisms:
Trace how news impacts flowed through markets:
Direct Channel:
Indirect Channels:
Sentiment Channel:
Feedback Loops:
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:
When conducting market news analysis:
Over-Attribution:
Recency Bias:
Hindsight Bias:
Single-Factor Analysis:
Ignoring Magnitude:
market_event_patterns.md - Comprehensive knowledge base covering:
geopolitical_commodity_correlations.md - Detailed correlations covering:
corporate_news_impact.md - Mega-cap analysis framework:
trusted_news_sources.md - Source credibility guide:
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