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BytesAgain β€Ί Skills β€Ί Trading Research
πŸ¦€ ClawHub

Trading Research

by @fpsjago

Binance cryptocurrency trading research, technical analysis, and position management. Triggers on requests for crypto prices, market data, trading analysis, DCA planning, position sizing, whale activity, or any trading research questions about Bitcoin, altcoins, or crypto markets.

Versionv1.0.0
Downloads5,213
Installs26
Stars⭐ 5
#crypto-defi#research#legal#automation#productivity
TERMINAL
clawhub install trading-research

πŸ“– About This Skill

name: trading-research description: Binance cryptocurrency trading research, technical analysis, and position management. Triggers on requests for crypto prices, market data, trading analysis, DCA planning, position sizing, whale activity, or any trading research questions about Bitcoin, altcoins, or crypto markets.

Trading Research Skill

Comprehensive cryptocurrency trading research and analysis focused on Binance markets. Designed for conservative-moderate risk traders using DCA (Dollar Cost Averaging) strategies with technical analysis support.

When to Use This Skill

Activate when user requests:

  • Current crypto prices or market data
  • Technical analysis (RSI, MACD, Bollinger Bands, etc.)
  • DCA strategy planning or schedule calculation
  • Position sizing with risk management
  • Market scanning for opportunities
  • Whale tracking or large order monitoring
  • Trading strategy advice or risk assessment

    • Core Philosophy

  • Conservative first: Preserve capital, minimize risk
  • DCA-focused: Time in market > timing the market
  • Risk management: Never risk more than 1-2% per trade
  • Data-driven: Use technical indicators for confirmation, not prediction
  • Transparent: Show calculations, explain reasoning

    • Available Tools

    1. Market Data (binance_market.py)

    Fetch real-time Binance market data.

    Use when: User asks for price, volume, orderbook, recent trades, or funding rates.

    Common commands: 

    # Current price and 24h stats (default)
python3 scripts/binance_market.py --symbol BTCUSDT
    Orderbook depth
    
python3 scripts/binance_market.py --symbol BTCUSDT --orderbook --depth 20
    Candlestick data
    
python3 scripts/binance_market.py --symbol BTCUSDT --klines 1h --limit 100
    Recent trades
    
python3 scripts/binance_market.py --symbol BTCUSDT --trades --limit 100
    Funding rate (futures)
    
python3 scripts/binance_market.py --symbol BTCUSDT --funding
    All data at once
    
python3 scripts/binance_market.py --symbol BTCUSDT --all
    JSON output (for piping)
    
python3 scripts/binance_market.py --symbol BTCUSDT --json > btc_data.json

    Intervals: 1m, 5m, 15m, 30m, 1h, 4h, 1d, 1w

    2. Technical Analysis (technical_analysis.py)

    Calculate and interpret technical indicators.

    Use when: User asks for TA, indicators, buy/sell signals, or market analysis.

    Common commands: 

    # Full analysis (default: 1h timeframe, 200 candles)
python3 scripts/technical_analysis.py --symbol BTCUSDT
    Different timeframe
    
python3 scripts/technical_analysis.py --symbol BTCUSDT --interval 4h
    Custom RSI period
    
python3 scripts/technical_analysis.py --symbol BTCUSDT --rsi-period 21
    From saved klines JSON
    
python3 scripts/technical_analysis.py --input btc_klines.json
    JSON output
    
python3 scripts/technical_analysis.py --symbol BTCUSDT --json

    What it analyzes:

  • Trend direction (SMA 20/50, EMA 12/26)
  • RSI (14) - overbought/oversold
  • MACD - momentum and crossovers
  • Bollinger Bands - volatility and position
  • Support/resistance levels
  • Volume analysis
  • Trading signals and recommendations

    • 3. DCA Calculator (dca_calculator.py)

    Plan Dollar Cost Averaging strategies.

    Use when: User wants to set up DCA, calculate investment schedules, or compare strategies.

    Common commands: 

    # Basic DCA plan
python3 scripts/dca_calculator.py --total 5000 --frequency weekly --duration 180
    With current price for projections
    
python3 scripts/dca_calculator.py --total 10000 --frequency monthly --duration 365 --current-price 100000
    Show scenario analysis
    
python3 scripts/dca_calculator.py --total 5000 --frequency weekly --duration 180 --current-price 100000 --scenarios
    Custom start date
    
python3 scripts/dca_calculator.py --total 5000 --frequency weekly --duration 180 --start-date 2026-03-01
    JSON output
    
python3 scripts/dca_calculator.py --total 5000 --frequency weekly --duration 180 --json

    Frequencies: daily, weekly, biweekly, monthly

    Output includes:

  • Purchase schedule with dates and amounts
  • Number of purchases and amount per purchase
  • Scenario analysis (flat, bull, bear markets)
  • Comparison to lump sum approach

    • 4. Position Sizer (position_sizer.py)

    Calculate safe position sizes using risk management rules.

    Use when: User wants to enter a trade and needs to know position size, stop loss, or take profit levels.

    Common commands: 

    # Basic position sizing (2% risk recommended)
python3 scripts/position_sizer.py --balance 10000 --risk 2 --entry 100000 --stop-loss 95000
    Conservative 1% risk
    
python3 scripts/position_sizer.py --balance 10000 --risk 1 --entry 100000 --stop-loss 97000
    Custom take-profit ratios
    
python3 scripts/position_sizer.py --balance 10000 --risk 2 --entry 100000 --stop-loss 95000 --take-profit 2 3 5
    Ladder strategy (scaling in)
    
python3 scripts/position_sizer.py --balance 10000 --risk 2 --entry 100000 --stop-loss 95000 --ladder 3
    JSON output
    
python3 scripts/position_sizer.py --balance 10000 --risk 2 --entry 100000 --stop-loss 95000 --json

    Output includes:

  • Position size in units and dollar value
  • Risk amount in dollars
  • Stop loss percentage
  • Take profit levels at multiple R:R ratios
  • Position as percentage of account
  • Warnings if position too large

    • Rules:

  • Conservative: Risk 1% per trade
  • Moderate: Risk 2% per trade
  • Never exceed 3% risk per trade
  • Position should be <50% of account

    • 5. Market Scanner (market_scanner.py)

    Scan all Binance USDT pairs for opportunities.

    Use when: User wants to find top movers, volume spikes, or new opportunities.

    Common commands: 

    # Full market scan (default)
python3 scripts/market_scanner.py
    Top gainers only
    
python3 scripts/market_scanner.py --gainers --limit 20
    High volume pairs
    
python3 scripts/market_scanner.py --volume
    Most volatile pairs
    
python3 scripts/market_scanner.py --volatile
    Breakout candidates (near 24h high with volume)
    
python3 scripts/market_scanner.py --breakout
    Filter by minimum volume
    
python3 scripts/market_scanner.py --min-volume 500000
    JSON output
    
python3 scripts/market_scanner.py --json

    Categories scanned:

  • Top gainers (24h price change)
  • Top losers (24h price change)
  • Highest volume pairs
  • Most volatile pairs (high-low spread)
  • Potential breakouts (near 24h high + volume)

    • 6. Whale Tracker (whale_tracker.py)

    Monitor large trades and orderbook imbalances.

    Use when: User asks about whale activity, large orders, or orderbook pressure.

    Common commands: 

    # Full whale analysis (default)
python3 scripts/whale_tracker.py --symbol BTCUSDT
    Large trades only
    
python3 scripts/whale_tracker.py --symbol BTCUSDT --trades
    Orderbook imbalances only
    
python3 scripts/whale_tracker.py --symbol BTCUSDT --orderbook
    Custom orderbook depth
    
python3 scripts/whale_tracker.py --symbol BTCUSDT --orderbook --depth 50
    Adjust threshold (default 90th percentile)
    
python3 scripts/whale_tracker.py --symbol BTCUSDT --threshold 95
    JSON output
    
python3 scripts/whale_tracker.py --symbol BTCUSDT --json

    Output includes:

  • Large trades (top 10% by value)
  • Buy vs sell pressure from large trades
  • Orderbook bid/ask imbalance
  • Orderbook walls (large orders)
  • Market sentiment (bullish/bearish/neutral)

    • Quick Start Workflows

    "What's BTC doing?"

    # Get overview
python3 scripts/binance_market.py --symbol BTCUSDT --ticker
    Technical analysis
    
python3 scripts/technical_analysis.py --symbol BTCUSDT --interval 1h

    "Should I buy now?"

    # Check technicals first
python3 scripts/technical_analysis.py --symbol BTCUSDT
    Check whale activity
    
python3 scripts/whale_tracker.py --symbol BTCUSDT
    If signals look good, calculate position size
    
python3 scripts/position_sizer.py --balance 10000 --risk 2 --entry  --stop-loss

    "Set up a DCA plan"

    # Plan the strategy
python3 scripts/dca_calculator.py --total 5000 --frequency weekly --duration 180 --current-price  --scenarios
    Show them the schedule and explain

    "Find me opportunities"

    # Scan market
python3 scripts/market_scanner.py
    For interesting pairs, do deeper analysis
    
python3 scripts/technical_analysis.py --symbol 
python3 scripts/whale_tracker.py --symbol

    "What's the market sentiment?"

    # Check whale activity
python3 scripts/whale_tracker.py --symbol BTCUSDT
    Check volume and volatility
    
python3 scripts/market_scanner.py --volume --volatile

    Reference Materials

    Located in references/ directory:

    binance-api.md

  • API endpoints and parameters
  • Rate limits
  • Authentication for signed requests
  • Order types and time-in-force
  • Error codes
  • Python examples

    • Use when: Need API details, building custom queries, or troubleshooting

    indicators.md

  • Technical indicator formulas
  • Interpretation guidelines
  • Common settings per timeframe
  • Combining indicators
  • Reliability assessment
  • Common mistakes

    • Use when: Explaining indicators, interpreting signals, or educating user

    strategies.md

  • DCA variations (fixed, value-based, RSI-based, ladder)
  • Risk management (1-2% rule, stop loss strategies)
  • Trend following strategies
  • Entry/exit strategies
  • Position sizing examples
  • Performance tracking

    • Use when: Planning trades, explaining strategies, or risk management questions

    Trading Guidance

    For Conservative Traders

    DCA Approach:

  • Start with weekly or monthly purchases
  • Fixed amount: $50-200 per purchase
  • Duration: 6-12 months minimum
  • Don't try to time the market
  • Accumulate and hold long-term

    • Risk Management:

  • No leverage
  • 50%+ of account in cash/stablecoins
  • Risk 1% per trade maximum
  • Only trade with 3+ confirmations
  • Stop losses always active

    • For Moderate Risk Traders

    Enhanced DCA:

  • Adjust amounts based on RSI (buy more when oversold)
  • Use technical analysis for better entries
  • 60-70% DCA, 30-40% active trading
  • Risk 2% per trade on active positions

    • Position Trading:

  • Wait for confluence of indicators
  • Use position_sizer.py for every trade
  • Risk:Reward ratio minimum 2:1
  • Trail stops as profit grows

    • Red Flags (Don't Trade)

  • RSI >70 and rising (overbought)
  • Low volume breakout (likely false)
  • Against major trend (don't short bull market)
  • Multiple indicators conflicting
  • No clear support level for stop loss
  • Risk:Reward ratio <1.5:1
  • During extreme fear or greed

    • Response Format

    When user asks for analysis:

    1. Current State: Price, trend, key levels 2. Technical View: Indicator readings and what they mean 3. Sentiment: Whale activity, volume, market pressure 4. Recommendation: Buy/wait/sell with reasoning 5. Risk Management: Position size, stop loss, take profit if applicable 6. Caveats: What could go wrong, alternative scenarios

    Always include:

  • Specific numbers (don't just say "oversold", say "RSI at 28")
  • Risk warnings for trades
  • Clear next steps
  • Timeframe context (day trade vs swing trade vs long-term)

    • Important Notes

    API Access

  • All scripts use Binance public API (no authentication needed for data)
  • Respect rate limits (built into scripts)
  • If API blocked by geo-restrictions, scripts will error gracefully

    • Limitations

  • No trading execution: These tools are for research only
  • No real-time WebSocket: Data is snapshot-based (REST API)
  • No futures-specific features: Primarily spot market focused (except funding rates)
  • No backtesting engine: Manual strategy evaluation

    • Authentication Required For

  • Placing orders
  • Checking account balance
  • Viewing open orders
  • Accessing trade history

    • Note: Guide users to Binance API documentation (see references/binance-api.md) for authenticated trading setup.

    Error Handling

    If script fails: 1. Check internet connection 2. Verify symbol format (uppercase, e.g., BTCUSDT not btc-usdt) 3. Check if Binance API accessible in user's location 4. Verify script path and Python availability 5. Check for typos in parameters

    Common errors:

  • HTTP 451: API blocked in location (suggest VPN)
  • Invalid symbol: Check symbol exists on Binance
  • Rate limit: Wait 60 seconds and retry
  • Connection timeout: Network issue or API down

    • Best Practices

    1. Always show your work: Display the command you ran 2. Interpret results: Don't just dump data, explain what it means 3. Context matters: Different advice for day trade vs DCA accumulation 4. Risk first: Mention risk management before entry signals 5. Be honest: If indicators conflict, say so 6. Update knowledge: If market conditions changed, acknowledge it 7. No predictions: Frame as "if X then Y", not "X will happen" 8. Show alternatives: Bull and bear case scenarios

    Skill Maintenance

    Testing

    Run each script monthly to ensure API compatibility: 
    python3 scripts/binance_market.py --symbol BTCUSDT --help
python3 scripts/technical_analysis.py --help
python3 scripts/dca_calculator.py --help
python3 scripts/position_sizer.py --help
python3 scripts/market_scanner.py --help
python3 scripts/whale_tracker.py --help

    Updates Needed If

  • Binance changes API endpoints
  • New technical indicators requested
  • Additional risk management tools needed
  • User feedback suggests improvements

    • Remember: This skill helps users make informed decisions. It does not make decisions for them. Always emphasize personal responsibility and risk disclosure.

    πŸ“‹ Tips & Best Practices

    1. Always show your work: Display the command you ran 2. Interpret results: Don't just dump data, explain what it means 3. Context matters: Different advice for day trade vs DCA accumulation 4. Risk first: Mention risk management before entry signals 5. Be honest: If indicators conflict, say so 6. Update knowledge: If market conditions changed, acknowledge it 7. No predictions: Frame as "if X then Y", not "X will happen" 8. Show alternatives: Bull and bear case scenarios