Real-time intelligent investment analysis for global markets excluding China A-shares (US, HK, Europe, Japan, Singapore stocks). Fetches live financial news, company announcements, macro data, and social sentiment. Provides multi-dimensional stock analysis, market trend tracking, and opportunity identification with cross-validated data sources. Use when analyzing international stocks, researching global markets, tracking market movements, or evaluating investment opportunities in non-China-A-share markets.
清晰的买入/卖出信号、具体价格、概率评估：
📈 BUY @ $145.50 → Target: $150-170 | Stop: $140 | Win Rate: 70%
- 白话化术语 (RSI → "买卖热度", Support → "买入底线")
- 彩色符号指示 (📈📉➡️)
- 分步操作建议
- BUY/SELL/HOLD 信号
- 入场价、止损、止盈价格
- 上升/下降/盘整的概率
- 关键看点和风险
# 生成简化版报告（推荐！）
python scripts/investment_advisor.py AAPL --format simple
# 专业版详细分析
python scripts/investment_advisor.py AAPL --format md
# 数据集成
python scripts/investment_advisor.py AAPL --format json📖 详见: COMPLETION_SUMMARY.md 和 scripts/IMPROVEMENT_GUIDE.md
Global Market Intelligent Investment Analysis Core Principles Real-time + Accuracy First: All analysis must prioritize current data freshness and multi-source validation.
Data Freshness Requirements Market data: Within 15 minutes for active trading hours News/announcements: Within 1 hour of publication Social sentiment: Within 24 hours Macro data: Latest available release Accuracy Validation Cross-validate critical data points across ≥2 independent sources Flag conflicting information explicitly Distinguish between facts, analyst opinions, and speculation Always cite data sources and timestamps Analysis Workflow Follow this structured workflow for each analysis request:
Task Progress:
- Step 1: Define analysis scope and ticker
- Step 2: Gather real-time market data
- Step 3: Collect news and announcements
- Step 4: Analyze macro environment
- Step 5: Assess social sentiment
- Step 6: Cross-validate and synthesize
- Step 7: Generate structured report Step 1: Define Analysis Scope Clarify with the user:
Target: Specific ticker(s) or market sector? Timeframe: Intraday, short-term (1-4 weeks), medium-term (1-3 months)? Focus areas: Technical, fundamental, sentiment, or comprehensive? Risk tolerance: Conservative, moderate, aggressive? If unspecified, default to comprehensive analysis with 1-3 month horizon.
Step 2: Gather Real-Time Market Data Required data points (fetch via web search):
Current price, day change %, volume vs average 52-week high/low position Key technical levels (support/resistance) Recent price momentum (1d, 1w, 1m, 3m) Market cap, P/E ratio, dividend yield (if applicable) Sources to check:
Yahoo Finance, Bloomberg, Reuters for pricing TradingView for technical indicators Company investor relations for official metrics Validation: Compare prices across ≥2 sources; flag discrepancies >0.5%.
Step 3: Collect News and Announcements Search strategy:
Company-specific (last 7 days):
Earnings releases, guidance updates M&A activity, regulatory filings Product launches, management changes Sector/industry (last 14 days):
Industry trends, competitive dynamics Regulatory changes, policy impacts Market-moving events (last 48 hours):
Geopolitical developments Central bank decisions Major economic data releases Sources:
Reuters, Bloomberg, CNBC for breaking news SEC EDGAR (US), HKEXnews (HK), company IR pages for filings Financial Times, Wall Street Journal for analysis Critical: Note exact publication times; prioritize most recent information.
Step 4: Analyze Macro Environment Key macro factors by market:
US Stocks:
Fed policy stance, interest rate trajectory Latest CPI, employment data, GDP growth USD strength/weakness trends HK Stocks:
Hong Kong economic indicators (retail sales, property market) HKD-USD peg stability Regional trade flows and connectivity European Stocks:
ECB monetary policy Eurozone inflation, manufacturing PMI Energy prices, geopolitical risks Japanese Stocks:
BOJ policy, yen exchange rate Japan CPI, wage growth data Export demand indicators Singapore Stocks:
MAS policy stance Regional trade data, commodity prices SGD exchange rate trends Action: Search for latest macro data releases (within 1 week); assess directional impact on target market/sector.
Step 5: Assess Social Sentiment Sentiment indicators:
Twitter/X mentions volume and tone (bullish/bearish %) Reddit discussions (r/investing, r/stocks, market-specific subs) StockTwits sentiment index (if available) Analyst rating changes (upgrades/downgrades last 30 days) Interpretation:
Extreme bullish sentiment → potential contrarian signal Extreme bearish sentiment → potential oversold bounce Rising mention volume → increasing attention/volatility Caution: Social sentiment is noisy; use as supplementary indicator only.
Step 6: Cross-Validate and Synthesize Triangulation framework:
Dimension Bullish Signals Bearish Signals Neutral/Unclear Price action Above key MA, breakout Below support, breakdown Sideways, low volume Fundamentals Beat earnings, raise guidance Miss, cut guidance In-line, maintain News flow Positive catalysts Negative headlines Mixed/no major news Macro tailwinds Favorable policy/data Headwinds Ambiguous impact Sentiment Improving, not extreme Deteriorating, panic Stable/mixed Synthesis rules:
Strong conviction: ≥4 dimensions aligned same direction Moderate conviction: 3 dimensions aligned, others neutral Low conviction/Uncertain: ≤2 aligned or conflicting signals Explicitly state conviction level in report Step 7: Generate Structured Report Use this template:
Analysis Date: [YYYY-MM-DD HH:MM UTC]
Data Freshness: [e.g., "Price data: 5 min old | News: within 2 hrs"]
Conviction Level: [High/Medium/Low]
[2-3 sentences: Current situation, key drivers, overall outlook]
Key Takeaway: [One-sentence bottom line]
- Price: $X.XX ([+/-]X.X% today)
- Volume: X.XM ([+/-]X% vs avg)
- 52-week range: $X - $X (current position: X%)
- Market cap: $X.XB
- Key technical levels: Support $X | Resistance $X
- Latest earnings: [Beat/Miss/Inline] EPS $X vs $X expected
- Revenue growth: [X% YoY]
- Guidance: [Raised/Maintained/Lowered]
- P/E: X.X (vs sector avg: X.X)
- P/S: X.X
- Dividend yield: X.X% (if applicable)
Assessment: [Undervalued/Fairly valued/Overvalued] relative to peers and history
- [Date]: [Headline] - [Impact: Positive/Negative/Neutral]
- [Date]: [Headline] - [Impact]
- [Date]: [Event: e.g., Earnings, product launch, regulatory decision]
- [Date]: [Event]
Relevant macro factors:
- [Factor 1]: [Current state] → [Impact on stock: Positive/Negative/Neutral]
- [Factor 2]: [Current state] → [Impact]
Overall macro backdrop: [Supportive/Headwind/Mixed]
- Social media tone: [Bullish X% / Bearish Y% / Neutral Z%]
- Analyst consensus: [X Buy, Y Hold, Z Sell] (recent changes: [note upgrades/downgrades])
- Insider activity: [Net buying/selling/neutral] (last 90 days)
Sentiment signal: [Positive/Negative/Neutral/Mixed]
- [Risk 1]: [Description] - Probability: [High/Medium/Low] - Impact: [High/Medium/Low]
- [Risk 2]: ...
- [Opportunity 1]: [Description] - Probability: [High/Medium/Low] - Impact: [High/Medium/Low]
[2-3 bullet points: Why this could outperform]
[2-3 bullet points: Why this could underperform]
Overall Outlook: [Bullish/Neutral/Bearish] for [timeframe]
Key Levels to Watch:
- Breakout above $X → [implication]
- Breakdown below $X → [implication]
Suggested Actions (not financial advice):
- For existing holders: [Hold/Add/Reduce/Exit] with rationale
- For potential buyers: [Wait for pullback to $X / Enter on breakout above $X / Avoid until clarity on Y]
Critical Monitoring Items:
- [Item 1 to watch closely]
- [Item 2]
Direction: 📈 Bullish / 📉 Bearish / ➡️ Neutral
(Choose one based on overall conviction)
Probability Assessment:
- Upside probability: [X]%
- Downside probability: [Y]%
- Sideways probability: [Z]% (Probabilities should sum to ~100%; based on technical, fundamental, and sentiment factors)
Price Target (Next 1-3 Months):
- Expected move: [+/- X%] or [$X - $Y range]
- Best case: +X% (if bullish catalysts materialize)
- Worst case: -Y% (if bearish risks trigger)
Simple Recommendation: [One sentence: e.g., "Consider buying on dips below $X" or "Take profits near $Y" or "Wait for clearer signals before entering"]
Key Trigger Events:
- Bullish trigger: [What would confirm upside? e.g., "Break above $X with volume"]
- Bearish trigger: [What would confirm downside? e.g., "Drop below $Y support"]
- Price data: [Source] as of [timestamp]
- News: [Sources] from [date range]
- Macro data: [Sources] released [dates]
- Sentiment: [Sources] as of [timestamp]
Disclaimer: This analysis is for informational purposes only and does not constitute financial advice. Always conduct your own research and consult with a qualified financial advisor before making investment decisions. Special Scenarios Earnings Season Analysis When analyzing around earnings:
Pre-earnings (1-7 days before):
Consensus estimates vs company guidance Options implied volatility (expectations) Historical earnings reaction patterns Post-earnings (within 48 hours):
Actual vs expected (EPS, revenue, key metrics) Management commentary tone Guidance changes Immediate price reaction vs typical pattern Breaking News Response For sudden market-moving events:
Verify: Confirm news across ≥2 reliable sources Assess magnitude: Material vs noise? Contextualize: How does this change the investment thesis? Update: Revise previous analysis if needed Sector Rotation Analysis When comparing multiple stocks/sectors:
Create comparison table (key metrics side-by-side) Identify relative strength/weakness Assess rotation drivers (macro, seasonal, thematic) Rank opportunities by risk-adjusted potential Quality Checks Before delivering analysis, verify:
All data points have source citations and timestamps Critical claims are cross-validated (≥2 sources) Conflicting information is explicitly noted Conviction level matches evidence strength Risks are clearly articulated (not just upside) No outdated information (>1 week old without noting) Analysis distinguishes facts from opinions Recommendations include specific trigger levels Disclaimer is included Common Pitfalls to Avoid ❌ Don't:
Give definitive "buy/sell" recommendations (provide frameworks instead) Ignore contradictory evidence Use stale data without disclosure Overstate conviction without strong evidence Neglect downside risks Make predictions without stating assumptions ✅ Do:
Present balanced bull/bear cases Highlight data limitations and uncertainties Provide actionable trigger levels Update analysis when new material information emerges Acknowledge what you don't know Emphasize this is analysis, not financial advice Tools & Resources Automated Analysis Scripts The skill includes Python scripts for automated data collection and analysis:
- Market Data Fetcher (scripts/fetch_market_data.py)
python scripts/fetch_market_data.py NVDA --av-key YOUR_API_KEY python scripts/fetch_market_data.py 0700.HK --output nvda_data.json 2. Technical Indicator Calculator (scripts/calculate_indicators.py)
python scripts/calculate_indicators.py AAPL --period 1y python scripts/calculate_indicators.py TSLA --indicators rsi,macd,bollinger --output tech.json 3. Chart Generator (scripts/generate_charts.py)
python scripts/generate_charts.py MSFT --period 6mo --type candlestick --output chart.png python scripts/generate_charts.py GOOGL --compare AAPL MSFT AMZN --type comparison 4. News Aggregator (scripts/fetch_news.py)
python scripts/fetch_news.py --ticker NVDA --days 7 --sources reuters,bloomberg,yahoo python scripts/fetch_news.py --ticker BABA --output news.json 5. Complete Workflow (scripts/full_analysis.py)
python full_analysis.py NVDA --period 6mo --output-dir ./nvda_analysis python full_analysis.py 0700.HK --no-charts # Skip chart generation
python full_analysis.py NVDA --include-recommendation 6. Investment Advisor (scripts/investment_advisor.py)
python scripts/investment_advisor.py NVDA --period 6mo python scripts/investment_advisor.py AAPL --timeframe short --output ./aapl_report
python scripts/investment_advisor.py TSLA --format md 7. Scoring Engine (scripts/score_engine.py)
- Strategy Generator (scripts/strategy_generator.py)
Setup Requirements:
pip install -r scripts/requirements.txt
export ALPHA_VANTAGE_KEY=your_key_here See scripts/README.md for detailed setup instructions.
Data Sources (by reliability tier) Tier 1 (Primary):
Official company filings (SEC EDGAR, HKEX, company IR) Major exchanges (NYSE, NASDAQ, HKEX, LSE, TSE, SGX) Central banks (Fed, ECB, BOJ, MAS, HKMA) Tier 2 (Secondary):
Reuters, Bloomberg, Associated Press Financial Times, Wall Street Journal Yahoo Finance, Google Finance Tier 3 (Supplementary):
Twitter/X (verified accounts only) Reddit, StockTwits Seeking Alpha, Motley Fool (opinion pieces) Useful Search Queries "[TICKER] stock price today site:finance.yahoo.com" "[TICKER] latest news site:reuters.com OR site:bloomberg.com" "[TICKER] earnings date 2026" "[TICKER] analyst ratings upgrades downgrades" "[Country/Region] latest GDP inflation data 2026" "[Sector] industry trends 2026" Additional Resources For detailed technical analysis methods, see technical-analysis.md For fundamental valuation frameworks, see valuation-methods.md For example analyses, see examples.md