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Market News Analyst

市场新闻分析师

Overview

概述

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.
该技能可对过去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大宗商品的影响。技能会通过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。

When to Use This Skill

何时使用该技能

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"
在以下场景使用该技能：
  • 用户要求分析近期重大市场新闻（过去10天）
  • 用户希望了解特定事件的市场反应（FOMC决策、财报、地缘政治事件）
  • 用户需要包含影响评估的全面市场新闻摘要
  • 用户询问新闻事件与大宗商品价格走势的相关性
  • 用户要求分析央行政策公告对市场的影响
示例用户请求：
  • "分析过去10天的重大市场新闻"
  • "最新FOMC决策对市场有何影响？"
  • "本周最重要的影响市场事件有哪些？"
  • "分析近期地缘政治新闻及大宗商品价格反应"
  • "回顾大盘科技股财报及其对市场的影响"

Analysis Workflow

分析流程

Follow this structured 6-step workflow when analyzing market news:
分析市场新闻时遵循以下结构化的6步流程：

Step 1: News Collection via WebSearch/WebFetch

步骤1：通过WebSearch/WebFetch收集新闻

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):
  1. Official sources: FederalReserve.gov, SEC.gov (EDGAR), Treasury.gov, BLS.gov
  2. Tier 1 financial news: Bloomberg, Reuters, Wall Street Journal, Financial Times
  3. 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)
目标： 收集过去10天内涵盖重大影响市场事件的全面新闻。
搜索策略：
执行并行WebSearch查询，覆盖不同新闻类别：
货币政策：
  • 搜索关键词："FOMC meeting past 10 days", "Federal Reserve interest rate", "ECB policy decision", "Bank of Japan"
  • 目标内容：央行决策、前瞻指引变化、通胀相关评论
通胀/经济数据：
  • 搜索关键词："CPI inflation report [current month]", "jobs report NFP", "GDP data", "PPI producer prices"
  • 目标内容：主要经济数据发布及超预期情况
大盘股财报：
  • 搜索关键词："Apple earnings [current quarter]", "Microsoft earnings", "NVIDIA earnings", "Amazon earnings", "Tesla earnings", "Meta earnings", "Google earnings"
  • 目标内容：头部企业的财报结果、前瞻指引、市场反应
地缘政治事件：
  • 搜索关键词："Middle East conflict oil prices", "Ukraine war", "US China tensions", "trade war tariffs"
  • 目标内容：影响市场的冲突、制裁、贸易争端
大宗商品市场：
  • 搜索关键词："oil prices news past week", "gold prices", "OPEC meeting", "natural gas prices", "copper prices"
  • 目标内容：供应中断、需求变化、价格波动
企业新闻：
  • 搜索关键词："major M&A announcement", "bank earnings", "tech sector news", "bankruptcy", "credit rating downgrade"
  • 目标内容：大盘股以外的重大企业事件
推荐新闻来源（优先级排序）：
  1. 官方来源：FederalReserve.gov, SEC.gov (EDGAR), Treasury.gov, BLS.gov
  2. 一级财经新闻：Bloomberg, Reuters, Wall Street Journal, Financial Times
  3. 专业来源：CNBC（实时）、MarketWatch（摘要）、S&P Global Platts（大宗商品）
搜索执行：
  • 使用WebSearch进行广泛主题搜索
  • 使用WebFetch获取官方来源或主流新闻媒体的特定URL
  • 收集发布日期，确保新闻在10天窗口内
  • 记录：事件日期、来源、标题、关键细节、市场背景（盘前、交易时段、盘后）
筛选标准：
  • 聚焦一级影响市场事件（参考references/market_event_patterns.md）
  • 优先选择有明确市场影响的新闻（价格波动、成交量激增）
  • 排除：小盘股特定新闻、次要产品更新、常规申报
收集全程使用英文思考。为每个重要新闻条目记录：
  • 日期和时间
  • 事件类型（货币政策、财报、地缘政治等）
  • 来源可信度等级
  • 初始市场反应（如可观察到）

Step 2: Load Knowledge Base References

步骤2：加载知识库参考资料

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
目标： 获取领域专业知识以辅助影响评估。
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
    - 涵盖所有重大事件类型的全面模式库
  • references/trusted_news_sources.md
    - 来源可信度评估指南
条件加载（基于收集到的新闻）：
如果发现货币政策新闻：
  • 重点关注：market_event_patterns.md → 央行货币政策事件章节
  • 核心框架：加息/降息反应、QE/QT影响、鹰派/鸽派基调
如果发现地缘政治事件：
  • 加载：
    references/geopolitical_commodity_correlations.md
  • 重点关注：能源大宗商品、贵金属、与事件匹配的区域框架
如果发现大盘股财报：
  • 加载：
    references/corporate_news_impact.md
  • 重点关注：特定企业章节、行业传染模式
如果发现大宗商品新闻：
  • 加载：
    references/geopolitical_commodity_correlations.md
  • 重点关注：特定大宗商品章节（石油、黄金、铜等）
知识整合： 将收集到的新闻与历史模式进行对比，以：
  • 预测预期市场反应
  • 识别异常情况（市场反应与历史模式不同）
  • 评估反应是否为典型幅度或过度反应
  • 判断是否如预期发生传染效应

Step 3: Impact Magnitude Assessment

步骤3：影响程度评估

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&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&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&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.
目标： 按市场影响重要性对每个新闻事件进行排名。
影响评估框架：
对每个新闻条目，从三个维度进行评估：
1. 资产价格影响（主要因素）：
衡量实际或预估价格变动：
股票市场：
  • 指数层面：S&P 500、Nasdaq 100、Dow Jones
    • 严重：单日±2%以上
    • 重大：±1-2%
    • 中等：±0.5-1%
    • 轻微：±0.2-0.5%
    • 可忽略：<0.2%
  • 行业层面：特定行业ETF
    • 严重：±5%以上
    • 重大：±3-5%
    • 中等：±1-3%
    • 轻微：<1%
  • 个股层面：单个大盘股
    • 严重：±10%以上（且指数权重导致指数变动）
    • 重大：±5-10%
    • 中等：±2-5%
大宗商品市场：
  • 石油（WTI/Brent）：
    • 严重：±5%以上
    • 重大：±3-5%
    • 中等：±1-3%
  • 黄金：
    • 严重：±3%以上
    • 重大：±1.5-3%
    • 中等：±0.5-1.5%
  • 基本金属（铜等）：
    • 严重：±4%以上
    • 重大：±2-4%
    • 中等：±1-2%
债券市场：
  • 10年期美国国债收益率：
    • 严重：单日±20个基点以上
    • 重大：±10-20个基点
    • 中等：±5-10个基点
外汇市场：
  • 美元指数（DXY）：
    • 严重：±1.5%以上
    • 重大：±0.75-1.5%
    • 中等：±0.3-0.75%
2. 影响广度（乘数）：
评估影响的市场/行业数量：
  • 系统性（3倍乘数）： 多个资产类别、全球市场
    • 示例：FOMC意外决策、银行业危机、重大战争爆发
  • 跨资产（2倍乘数）： 股票+大宗商品，或股票+债券
    • 示例：通胀超预期、地缘政治供应冲击
  • 全行业（1.5倍乘数）： 整个行业或相关行业
    • 示例：科技股财报集中发布、能源政策公告
  • 个股特定（1倍乘数）： 单个企业（除非是影响指数的大盘股）
    • 示例：单个企业财报、并购
3. 前瞻重要性（修正项）：
考虑未来影响：
  • 制度变革（+50%）： 市场结构根本性转变
    • 示例：美联储从加息转向降息、重大地缘政治重组
  • 趋势确认（+25%）： 强化现有趋势
    • 示例：连续强劲通胀数据、持续财报超预期
  • 孤立事件（0%）： 一次性事件，前瞻信号有限
    • 示例：范围内的单个数据点、企业特定问题
  • 反向信号（-25%）： 与主流叙事矛盾
    • 示例：利好消息被市场忽视、利空消息下市场上涨
影响得分计算：
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 75个基点加息（鹰派基调）：
  • 价格影响：S&P 500 下跌2.5%（严重=10分）
  • 广度：系统性（股票、债券、美元、大宗商品均变动）=3倍
  • 前瞻：趋势确认（持续紧缩）=+25%
  • 得分：(10 × 3) × 1.25 = 37.5
NVIDIA财报超预期：
  • 价格影响：NVDA上涨15%，Nasdaq上涨1.5%（严重=10分）
  • 广度：全行业（半导体、整体科技行业）=1.5倍
  • 前瞻：趋势确认（AI需求）=+25%
  • 得分：(10 × 1.5) × 1.25 = 18.75
地缘政治冲突升级（中东）：
  • 价格影响：石油上涨8%，S&P下跌1.2%（严重=10分）
  • 广度：跨资产（石油、股票、黄金）=2倍
  • 前瞻：孤立事件（未升级）=0%
  • 得分：(10 × 2) × 1.0 = 20
个股财报（非大盘股）：
  • 价格影响：个股上涨12%，无指数影响（重大=7分）
  • 广度：个股特定=1倍
  • 前瞻：孤立事件=0%
  • 得分：(7 × 1) × 1.0 = 7
排名： 为所有新闻条目打分后，按影响得分从高到低排名。这将决定报告的顺序。

Step 4: Market Reaction Analysis

步骤4：市场反应分析

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&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
目标： 分析市场对每个事件的实际反应。
对每个重要新闻条目（影响得分>5）进行详细反应分析：
即时反应（日内）：
  • 方向：正面、负面、混合
  • 幅度：符合价格影响类别
  • 时间：盘前、交易时段、盘后
  • 波动率：VIX变动、买卖价差
跨资产反应：
股票：
  • 指数表现（S&P 500、Nasdaq、Dow、Russell 2000）
  • 行业轮动（哪些行业表现优于/逊于大盘）
  • 个股变动（大盘股、相关企业）
  • 成长股vs价值股、大盘股vs小盘股的分化
固定收益：
  • 美国国债收益率（2年期、10年期、30年期）
  • 收益率曲线形态（趋陡、趋平、倒挂）
  • 信用利差（投资级、高收益）
  • TIPS盈亏平衡通胀率（通胀预期）
大宗商品：
  • 能源：石油（WTI、Brent）、天然气
  • 贵金属：黄金、白银
  • 基本金属：铜、铝（如相关）
  • 农产品：小麦、玉米、大豆（如相关）
外汇：
  • 美元指数（DXY）
  • EUR/USD、USD/JPY、GBP/USD
  • 新兴市场货币
  • 避险货币（JPY、CHF）
衍生品：
  • VIX（波动率指数）
  • 期权活动（看跌/看涨比率、异常成交量）
  • 期货持仓
模式对比：
将观察到的反应与知识库中的预期模式进行对比：
  • 一致： 反应符合历史模式
    • 示例：美联储加息→科技股下跌、美元上涨（符合预期）
  • 放大： 反应超出典型模式
    • 示例：通胀数据超预期0.3%→抛售幅度为典型的2倍
    • 调查原因：持仓、情绪、累积因素
  • 减弱： 反应弱于历史模式
    • 示例：地缘政治事件→石油几乎未变动
    • 调查原因：已被提前定价、其他抵消因素
  • 反向： 反应与历史模式相反
    • 示例：利好消息被忽视、利空消息下市场上涨
    • 调查原因：“利好即利空”动态、美联储转向预期
异常识别：
标记与模式显著偏离的反应：
  • 市场对通常影响重大的新闻无动于衷
  • 对通常次要的新闻过度反应
  • 传染效应未如预期扩散
  • 避险资产失效（相关性破裂）
情绪指标：
  • 风险偏好vs风险规避：哪种主导市场
  • 持仓：是否有拥挤交易平仓的迹象
  • 动量：后续时段是持续还是反转

Step 5: Correlation and Causation Assessment

步骤5：相关性与因果关系评估

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
目标： 区分直接影响与巧合时机。
多事件分析：
当10天内发生多个重要事件时，评估相互作用：
强化事件：
  • 相同方向的影响
  • 示例：鹰派FOMC+高通胀数据→均对股票利空，放大跌幅
  • 综合影响通常是非线性的（大于各部分之和）
抵消事件：
  • 相反方向的影响
  • 示例：强劲财报（正面）+地缘政治紧张（负面）→净反应温和
  • 确定哪个因素占主导
连续事件：
  • 一个事件为下一个事件的反应奠定基础
  • 示例：首次加息反应温和，第二次加息反应剧烈（累积紧缩担忧）
  • 路径依赖很重要
巧合时机：
  • 事件无关但同时发生
  • 难以区分单个影响
  • 注明归因的不确定性
地缘政治-大宗商品相关性：
对于地缘政治事件，使用geopolitical_commodity_correlations.md专门分析大宗商品市场反应：
能源：
  • 将冲突/制裁映射到供应中断风险
  • 评估实际与担忧的供应影响
  • 持续时间：临时 spike vs 持续上涨
贵金属：
  • 避险资金流动vs实际利率驱动因素
  • 黄金对风险规避事件的反应
  • 央行购买的影响
工业金属：
  • 经济放缓担忧导致的需求破坏
  • 供应链中断
  • 铜、铝的中国因素
农产品：
  • 黑海谷物出口（俄乌冲突）
  • 天气叠加因素
  • 粮食安全政策响应
传导机制：
追踪新闻如何在市场中传导影响：
直接渠道：
  • 新闻→即时资产价格反应
  • 示例：OPEC减产→石油价格立即上涨
间接渠道：
  • 新闻→经济影响→资产价格
  • 示例：加息→抵押贷款利率上升→房地产放缓→建筑商股票下跌
情绪渠道：
  • 新闻→风险偏好转变→广泛资产重新配置
  • 示例：银行业危机→避险情绪→美国国债上涨、股票抛售
反馈循环：
  • 初始反应产生二次影响
  • 示例：股票抛售→追加保证金通知→强制抛售→进一步抛售

Step 6: Report Generation

步骤6：报告生成

Objective: Create structured English Markdown report ranked by market impact.
Report Structure:
markdown
undefined
目标： 创建按市场影响排序的结构化英文Markdown报告。
报告结构：
markdown
undefined

Market News Analysis Report - [Date Range]

Market News Analysis Report - [Date Range]

Executive Summary

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
[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

Market Impact Rankings

[Table format, sorted by Impact Score descending]
RankEventDateImpact ScoreAsset Classes AffectedMarket Reaction
1[Event][Date][Score][Equities, Commodities, etc.][Brief reaction]
2...............
[Table format, sorted by Impact Score descending]
RankEventDateImpact ScoreAsset Classes AffectedMarket Reaction
1[Event][Date][Score][Equities, Commodities, etc.][Brief reaction]
2...............

Detailed Event Analysis

Detailed Event Analysis

[For each event in rank order, provide comprehensive analysis]
[For each event in rank order, provide comprehensive analysis]

[Rank]. [Event Name] (Impact Score: [X])

[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 Date: [Date, Time] Event Type: [Monetary Policy / Earnings / Geopolitical / Economic Data / Corporate] News Source: [Source, with credibility tier]

Event Summary

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
[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

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]
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

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]
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

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)]
[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

Geopolitical-Commodity Correlation Analysis

[Include this section only for geopolitical events]
  • [Specific commodity affected]: [Price movement]
  • [Historical precedent]: [Comparison to similar past events]
  • [Expected duration]: [Temporary shock vs sustained impact]
[Repeat detailed analysis for each ranked event]
[Include this section only for geopolitical events]
  • [Specific commodity affected]: [Price movement]
  • [Historical precedent]: [Comparison to similar past events]
  • [Expected duration]: [Temporary shock vs sustained impact]
[Repeat detailed analysis for each ranked event]

Thematic Synthesis

Thematic Synthesis

Dominant Market Narrative

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"]
[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

Interconnected Events

[Analyze how events related or compounded]
  • [Event A] + [Event B] → [Combined impact analysis]
  • [Sequential causation if applicable]
[Analyze how events related or compounded]
  • [Event A] + [Event B] → [Combined impact analysis]
  • [Sequential causation if applicable]

Market Regime Assessment

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]
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

Anomalies and Surprises

[Highlight unexpected market reactions]
  1. [Event]: Market reacted [unexpectedly] because [explanation]
  2. [Continue for significant anomalies]
[Highlight unexpected market reactions]
  1. [Event]: Market reacted [unexpectedly] because [explanation]
  2. [Continue for significant anomalies]

Commodity Market Deep Dive

Commodity Market Deep Dive

[Dedicated section for commodity movements]
[Dedicated section for commodity movements]

Energy

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]
  • 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

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]
  • 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

Base Metals

  • Copper: [As economic barometer - demand signals]
  • Aluminum, Nickel: [If relevant supply/demand news]
  • China Factor: [Impact of Chinese economic data/policy]
  • Copper: [As economic barometer - demand signals]
  • Aluminum, Nickel: [If relevant supply/demand news]
  • China Factor: [Impact of Chinese economic data/policy]

Agricultural (If Relevant)

Agricultural (If Relevant)

  • Grains: [Wheat, Corn, Soybeans - weather, Ukraine conflict impacts]
[For each commodity, reference geopolitical events from main analysis and draw correlations]
  • Grains: [Wheat, Corn, Soybeans - weather, Ukraine conflict impacts]
[For each commodity, reference geopolitical events from main analysis and draw correlations]

Forward-Looking Implications

Forward-Looking Implications

Market Positioning Insights

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)]
[What the news suggests for current market positioning]
  • [Trend continuation or reversal signals]
  • [Overvaluation or undervaluation indications]
  • [Sentiment extremes (complacency or panic)]

Upcoming Catalysts

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]
[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

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]
[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

Data Sources and Methodology

News Sources Consulted

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]
[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

Analysis Period

  • Start Date: [Specific date]
  • End Date: [Specific date]
  • Total Days: 10
  • Start Date: [Specific date]
  • End Date: [Specific date]
  • Total Days: 10

Market Data

Market Data

  • Equity indices: [Data sources]
  • Commodity prices: [Data sources]
  • Economic data: [Government sources]
  • Equity indices: [Data sources]
  • Commodity prices: [Data sources]
  • Economic data: [Government sources]

Knowledge Base References

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
  • 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

**文件命名规范：**
`market_news_analysis_[START_DATE]_to_[END_DATE].md`

示例：`market_news_analysis_2024-10-25_to_2024-11-03.md`

**报告质量标准：**
- 客观、基于事实的分析（除概率加权场景外无猜测）
- 用具体百分比量化价格变动
- 为主要主张引用来源
- 区分相关性与因果关系
- 归因市场变动时承认不确定性
- 使用正确的金融术语
- 全程保持英文一致

Key Analysis Principles

核心分析原则

When conducting market news analysis:
  1. Impact Over Noise: Focus on truly market-moving news, filter out minor events
  2. Multi-Asset Perspective: Analyze across equities, bonds, commodities, currencies to understand full impact
  3. Pattern Recognition: Compare against historical precedents while noting unique aspects
  4. Causation Discipline: Be rigorous about attributing market moves to specific news vs coincidental timing
  5. Forward-Looking: Emphasize implications for future market behavior, not just backward-looking description
  6. Objectivity: Separate market reaction (what happened) from personal market view (what should happen)
  7. Quantification: Use specific numbers (%, bps) rather than vague terms ("significant," "large")
  8. Source Credibility: Weight official sources and Tier 1 news over rumors and unverified reports
  9. Breadth Analysis: Individual stock moves only significant if mega-cap or systemic signal
  10. English Consistency: All thinking, analysis, and output in English for consistency
进行市场新闻分析时：
  1. 影响优先于噪音： 聚焦真正影响市场的新闻，过滤次要事件
  2. 跨资产视角： 分析股票、债券、大宗商品、外汇以了解全面影响
  3. 模式识别： 与历史先例对比，同时注意独特之处
  4. 因果关系严谨性： 严格区分市场变动是由特定新闻驱动还是巧合时机
  5. 前瞻性： 强调对未来市场行为的影响，而非仅回顾性描述
  6. 客观性： 区分市场反应（已发生的事）与个人市场观点（应该发生的事）
  7. 量化： 使用具体数字（%、基点）而非模糊术语（“重大”、“大幅”）
  8. 来源可信度： 优先官方来源和一级新闻，而非谣言和未验证报告
  9. 广度分析： 个股变动仅在为大盘股或系统性信号时才重要
  10. 英文一致性： 所有思考、分析和输出均使用英文以保持一致

Common Pitfalls to Avoid

需避免的常见陷阱

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
过度归因：
  • 并非所有市场变动都由新闻驱动（技术面、资金流、月末再平衡也存在）
  • 当归因不确定时需明确说明
近期偏差：
  • 最新新闻不一定最重要
  • 按实际影响排名，而非时间顺序
事后诸葛亮偏差：
  • 区分“事后明显”与“当时意外”
  • 注明共识预期与实际结果的差异
单因素分析：
  • 市场同时对多个因素做出反应
  • 承认交互效应
忽略幅度：
  • 超预期0.1%的“高”CPI与超预期0.5%的情况不同
  • 量化超预期程度

Resources

资源

references/

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
market_event_patterns.md - 全面知识库，涵盖：
  • 央行货币政策事件（FOMC、ECB、BOJ、PBOC）
  • 通胀数据发布（CPI、PPI、PCE）
  • 就业数据（NFP、失业率、薪资）
  • GDP报告
  • 地缘政治事件（冲突、贸易战、制裁）
  • 企业财报（大盘科技股、银行、能源）
  • 信用事件和评级调整
  • 大宗商品特定事件（OPEC、天气、供应中断）
  • 衰退指标
  • 历史案例研究（2008年危机、COVID-19、2022年通胀）
  • 模式识别框架和情绪分析
geopolitical_commodity_correlations.md - 详细相关性，涵盖：
  • 能源大宗商品（原油、天然气、煤炭）与地缘政治冲突
  • 贵金属（黄金、白银、铂金、钯金）避险动态
  • 基本金属（铜、铝、镍、锌）与经济/政治风险
  • 农产品（小麦、玉米、大豆）与天气/政策
  • 稀土元素和关键矿物（中国主导、供应安全）
  • 区域地缘政治框架（中东、俄欧、亚太、拉美）
  • 相关性汇总表
  • 时间 horizon 考量
corporate_news_impact.md - 大盘股分析框架：
  • “七大科技股”（NVIDIA、Apple、Microsoft、Amazon、Meta、Google、Tesla）
  • 金融行业大盘股（JPMorgan、Bank of America等）
  • 医疗保健行业大盘股（UnitedHealth、Pfizer、J&J、Merck）
  • 能源行业大盘股（Exxon Mobil、Chevron）
  • 必需消费品大盘股（P&G、Coca-Cola、PepsiCo）
  • 工业大盘股（Boeing、Caterpillar）
  • 财报影响框架、产品发布、并购、监管问题
  • 行业传染模式
  • 影响程度框架
trusted_news_sources.md - 来源可信度指南：
  • 一级主要来源（央行、政府机构、SEC）
  • 二级主流财经新闻（Bloomberg、Reuters、WSJ、FT、CNBC）
  • 三级专业来源（能源、科技、新兴市场、中国特定、加密货币）
  • 四级分析与研究（独立研究、央行出版物、智库）
  • 搜索和聚合工具
  • 来源质量评估标准
  • 速度与准确性的权衡
  • 10天分析的推荐搜索策略
  • 来源可信度框架
  • 需避免的警示来源

Important Notes

重要说明

  • 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)
  • 所有分析思考必须使用英文
  • 所有输出Markdown文件必须使用英文
  • 使用WebSearch和WebFetch工具自动收集新闻
  • 聚焦参考资料中定义的可信新闻来源
  • 按影响得分（价格影响×广度×前瞻重要性）对事件排名
  • 目标分析周期：当前日期过去10天
  • 重点分析美国股票市场和大宗商品
  • FOMC及其他央行政策决策为最高优先级分析对象
  • 严格区分相关性与因果关系
  • 用具体百分比量化所有市场反应
  • 根据收集到的新闻类型加载相应的参考文件
  • 生成按市场影响排序的全面报告（影响最高的排在前面）