Market Environment Analysis
- 240 installs
- 74 repo stars
- Updated July 20, 2026
- wind-information-co-ltd/wind-skills
This is a copy of market-environment-analysis by tradermonty - installs and ranking accrue to the original listing.
Use market-environment-analysis for development tasks
About
market-environment-analysis: A skill skill for development. This skill provides functionality for development workflows.
- market-environment-analysis
Market Environment Analysis by the numbers
- 240 all-time installs (skills.sh)
- +44 installs in the week ending Jul 20, 2026 (Skillselion tracking)
- Data as of Aug 4, 2026 (Skillselion catalog sync)
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| Installs | 240 |
|---|---|
| repo stars | ★ 74 |
| Last updated | July 20, 2026 |
| Repository | wind-information-co-ltd/wind-skills ↗ |
What it does
Use market-environment-analysis for development tasks
Files
Market Environment Analysis
Comprehensive analysis tool for understanding market conditions and creating professional market reports anytime.
Core Workflow
1. Initial Data Collection
Collect latest market data using web_search tool: 1. Major stock indices (S&P 500, NASDAQ, Dow, Nikkei 225, Shanghai Composite, Hang Seng) 2. Forex rates (USD/JPY, EUR/USD, major currency pairs) 3. Commodity prices (WTI crude, Gold, Silver) 4. US Treasury yields (2-year, 10-year, 30-year) 5. VIX index (Fear gauge) 6. Market trading status (open/close/current values)
2. Market Environment Assessment
Evaluate the following from collected data:
- Trend Direction: Uptrend/Downtrend/Range-bound
- Risk Sentiment: Risk-on/Risk-off
- Volatility Status: Market anxiety level from VIX
- Sector Rotation: Where capital is flowing
3. Report Structure
Standard Report Format:
1. Executive Summary (3-5 key points)
2. Global Market Overview
- US Markets
- Asian Markets
- European Markets
3. Forex & Commodities Trends
4. Key Events & Economic Indicators
5. Risk Factor Analysis
6. Investment Strategy ImplicationsScript Usage
market_utils.py
Provides common functions for report creation:
# Generate report header
python scripts/market_utils.py
# Available functions:
- format_market_report_header(): Create header
- get_market_session_times(): Check trading hours
- categorize_volatility(vix): Interpret VIX levels
- format_percentage_change(value): Format price changesReference Documentation
Key Indicators Interpretation (references/indicators.md)
Reference when you need:
- Important levels for each index
- Technical analysis key points
- Sector-specific focus areas
Analysis Patterns (references/analysis_patterns.md)
Reference when analyzing:
- Risk-on/Risk-off criteria
- Economic indicator interpretation
- Inter-market correlations
- Seasonality and market anomalies
Output Examples
Quick Summary Version
📊 Market Summary [2025/01/15 14:00]
━━━━━━━━━━━━━━━━━━━━━
【US】S&P 500: 5,123.45 (+0.45%)
【JP】Nikkei 225: 38,456.78 (-0.23%)
【FX】USD/JPY: 149.85 (↑0.15)
【VIX】16.2 (Normal range)
⚡ Key Events
- Japan GDP Flash
- US Employment Report
📈 Environment: Risk-On ContinuesDetailed Analysis Version
Start with executive summary, then analyze each section in detail. Key clarifications: 1. Current market phase (Bullish/Bearish/Neutral) 2. Short-term direction (1-5 days outlook) 3. Risk events to monitor 4. Recommended position adjustments
Important Considerations
Timezone Awareness
- Consider all major market timezones
- US markets: Evening to early morning (Asian time)
- European markets: Afternoon to evening (Asian time)
- Asian markets: Morning to afternoon (Local time)
Economic Calendar Priority
Categorize by importance:
- ⭐⭐⭐ Critical (FOMC, NFP, CPI, etc.)
- ⭐⭐ Important (GDP, Retail Sales, etc.)
- ⭐ Reference level
Data Source Priority
1. Official releases (Central banks, Government statistics) 2. Major financial media (Bloomberg, Reuters) 3. Broker reports 4. Analyst consensus estimates
Troubleshooting
Data Collection Notes
- Check market holidays (holiday calendars)
- Be aware of daylight saving time changes
- Distinguish between flash and final data
Market Volatility Response
1. First organize the facts 2. Reference historical similar events 3. Verify with multiple sources 4. Maintain objective analysis
Customization Options
Adjust based on user's investment style:
- Day Traders: Intraday charts, order flow focus
- Swing Traders: Daily/weekly technicals emphasis
- Long-term Investors: Fundamentals, macro economics focus
- Forex Traders: Currency correlations, interest rate differentials
- Options Traders: Volatility analysis, Greeks monitoring
Market Analysis Patterns
Market Pattern Analysis
Trend Identification
1. Uptrend
- Higher highs and higher lows
- Moving averages trending upward
- Price rises accompanied by volume increases
2. Downtrend
- Lower highs and lower lows
- Moving averages trending downward
- Decreased volume on bounces
3. Range-Bound Market
- Trading within defined range
- Moving averages sideways
- Declining volume trend
Risk-On / Risk-Off Assessment
Risk-On Environment Characteristics
- Stock markets rising (especially emerging markets)
- High-yield currency buying (AUD, NZD, etc.)
- VIX index declining
- Interest rates rising
- Risk assets like crude oil rising
Risk-Off Environment Characteristics
- Flight to safe assets (yen buying, Swiss franc buying)
- Gold prices rising
- Bond buying (yields falling)
- VIX index rising
- Emerging market currencies and stocks selling
Economic Indicator Interpretation
Employment Data (US)
- Nonfarm Payrolls (NFP)
- +200k or more above expectations: Strong employment, rate hike expectations
- -100k or more below expectations: Employment deterioration, rate cut expectations
- Unemployment Rate
- 3.5% or below: Near full employment
- 4.0% or above: Signs of employment environment deterioration
Inflation Indicators
- CPI (Consumer Price Index)
- 2% YoY: Fed target level
- 3%+: Inflation alert
- Below 1%: Deflation risk
- PPI (Producer Price Index)
- Important as CPI leading indicator
- Captures upstream inflation
Central Bank Policy
- Fed (Federal Reserve)
- Watch dot plot
- Policy rate outlook changes
- BOJ (Bank of Japan)
- YCC (Yield Curve Control) policy
- ETF purchase trends
- ECB (European Central Bank)
- 2% inflation target
- Response to regional disparities
Inter-Market Correlation Analysis
Positive Correlation Patterns
- Stocks ↑ → Interest rates ↑ (strong economy)
- USD/JPY ↑ → Nikkei ↑ (exporters favorable)
- Crude oil ↑ → Inflation expectations ↑
Inverse Correlation Patterns
- Interest rates ↑ → Bond prices ↓
- Dollar ↑ → Gold prices ↓
- VIX ↑ → Stocks ↓
Seasonality & Anomalies
Monthly Patterns
- January Effect: New year fund inflows
- Sell in May: Pre-summer doldrums position closing
- September: Historically weak month
- December: Tax-loss selling, Santa Claus rally
Day-of-Week Effects
- Monday: Weekend risk pricing
- Friday: Position adjustments
Fiscal Year-End
- End of March: Japanese corporate fiscal year, repatriation flows
- End of December: Western corporate fiscal year
Technical Indicator Usage
Trend Indicators
- Moving Averages: 25-day, 75-day, 200-day line relationships
- MACD: Identifying trend turning points
- Bollinger Bands: Volatility and contrarian entry points
Oscillators
- RSI: Over 70 overbought, below 30 oversold
- Stochastics: Short-term turning points
- Volume: Confirming price movement reliability
Sentiment Analysis
Capturing Investor Psychology
- Put/Call Ratio: Option market skew
- Bull/Bear Ratio: Investor surveys
- Fear & Greed Index: CNN Fear & Greed Index
News Flow Analysis
- Headline tone changes
- Media coverage frequency
- Social media buzzwords
Market Indicators Reference
Major Stock Indices
Japan
- Nikkei 225: Stock price average of 225 representative stocks on Tokyo Stock Exchange Prime
- Key levels: 30,000, 35,000, 40,000 yen
- Moving averages: Emphasize 25-day, 75-day, 200-day lines
- TOPIX: Market-cap weighted average of all Tokyo Stock Exchange Prime stocks
- Better reflects overall market
- Heavily influenced by banking/financial sector
United States
- S&P 500: 500 large-cap US stocks
- Most representative US stock index
- Key levels: 4,000, 4,500, 5,000 points
- NASDAQ: Tech-focused
- Reflects mega-cap tech stock trends like GAFAM
- Higher volatility
- Dow Jones Industrial Average: Simple average of 30 stocks
- Historically significant but limited representation
Foreign Exchange Rates
USD/JPY (Dollar-Yen)
- Greatest impact on Japanese economy
- Key levels: 140, 145, 150, 155 yen
- BOJ intervention alert line: Reference past intervention records
EUR/JPY (Euro-Yen)
- Related to European economy
- Influenced by ECB policy
CNY/JPY (Yuan-Yen)
- Reflects Chinese economic trends
- Indicator of Asian trade
Volatility Indicators
VIX Index (Fear Index)
- Calculated from S&P 500 option prices
- Quantifies market anxiety psychology
- Interpretation:
- 10-15: Low volatility, stable market
- 15-20: Normal range
- 20-30: Unstable, caution needed
- 30+: High stress, panic selling
Nikkei VI
- Volatility indicator for Nikkei Average
- Japanese version of VIX
Commodities
Crude Oil (WTI/Brent)
- Important as inflation indicator
- Reflects geopolitical risks
- Key levels: 70, 80, 90, 100 dollars/barrel
Gold
- Representative safe asset
- Tends to rise during dollar weakness/inflation
- Key levels: 1,900, 2,000, 2,100 dollars/ounce
Interest Rates & Bonds
US 10-Year Treasury Yield
- Most critical interest rate indicator
- Direct impact on stock valuations
- Key levels: 3.5%, 4.0%, 4.5%, 5.0%
Japan 10-Year Government Bond Yield
- Reflects BOJ policy
- Watch YCC target range
Sector-Specific Focus Points
Technology
- AI-related stock trends
- Semiconductor cycle
- Regulatory risks
Financials
- Heavily influenced by interest rate trends
- Bank lending attitudes
- Non-performing loan ratios
Energy
- Linked to crude oil prices
- Impact of decarbonization policies
- Renewable energy shift
Consumer
- Consumer confidence index
- Retail sales
- Inflation impact
#!/usr/bin/env python3
"""
Market Analysis Utility Functions for Environment Report
This script provides common functions for market analysis report creation.
"""
from datetime import datetime, timedelta
def get_market_session_times():
"""Returns major market trading hours"""
return {
"Tokyo": {"open": "09:00 JST", "close": "15:00 JST", "lunch": "11:30-12:30"},
"Shanghai": {"open": "09:30 CST", "close": "15:00 CST", "lunch": "11:30-13:00"},
"Hong Kong": {"open": "09:30 HKT", "close": "16:00 HKT", "lunch": "12:00-13:00"},
"Singapore": {"open": "09:00 SGT", "close": "17:00 SGT", "lunch": "12:00-13:00"},
"London": {"open": "08:00 GMT", "close": "16:30 GMT", "lunch": None},
"New York": {"open": "09:30 EST", "close": "16:00 EST", "lunch": None},
}
def format_market_report_header():
"""Format report header"""
now = datetime.now()
weekdays = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
return f"""
=====================================
📊 Daily Market Environment Report
=====================================
Created: {now.strftime("%Y-%m-%d")} ({weekdays[now.weekday()]}) {now.strftime("%H:%M")}
=====================================
"""
def calculate_trading_days_to_event(event_date_str):
"""Calculate trading days to event"""
# Simple version: excludes weekends (doesn't consider holidays)
event_date = datetime.strptime(event_date_str, "%Y-%m-%d")
today = datetime.now().date()
trading_days = 0
current = today
while current < event_date.date():
if current.weekday() < 5: # Monday to Friday
trading_days += 1
current += timedelta(days=1)
return trading_days
def format_percentage_change(value):
"""Format percentage change"""
if value >= 0:
return f"📈 +{value:.2f}%"
else:
return f"📉 {value:.2f}%"
def categorize_volatility(vix_value):
"""Categorize volatility based on VIX level"""
if vix_value < 12:
return "Low & Stable 😌"
elif vix_value < 20:
return "Normal Range 📊"
elif vix_value < 30:
return "Elevated ⚠️"
elif vix_value < 40:
return "High Volatility 🔥"
else:
return "Extreme Volatility 🚨"
def get_market_status():
"""Determine current market status"""
now = datetime.now()
hour = now.hour
status = []
# Simple market open determination (timezone not considered)
if 9 <= hour < 15:
status.append("🟢 Tokyo Market: Trading")
elif 15 <= hour < 18:
status.append("🔴 Tokyo Market: Closed")
else:
status.append("⏰ Tokyo Market: After hours")
if 21 <= hour or hour < 4:
status.append("🟢 US Market: Trading (previous day)")
else:
status.append("🔴 US Market: Closed")
return "\n".join(status)
def generate_checklist():
"""Generate market analysis checklist"""
return """
📋 Analysis Checklist
--------------------
□ US market status check
□ Asian market status check
□ European market status check
□ Forex rates (USD/JPY, EUR/USD, CNY)
□ Index futures movements
□ VIX level check
□ Oil & Gold prices
□ Economic calendar
□ Corporate earnings schedule
□ Central bank news
□ Geopolitical risks
"""
if __name__ == "__main__":
print("Market Analysis Utility - Test Run")
print(format_market_report_header())
print("\nCurrent Market Status:")
print(get_market_status())
print("\nTrading Hours:")
for market, times in get_market_session_times().items():
lunch = f" (Lunch break: {times['lunch']})" if times.get("lunch") else ""
print(f" {market}: {times['open']} - {times['close']}{lunch}")
print(generate_checklist())
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