Generating Trading Signals

Generating Trading Signals

Overview

Multi-indicator signal generation system that analyzes price action using 7 technical indicators and produces composite BUY/SELL signals with confidence scores and risk management levels.

Indicators Used:

• RSI (Relative Strength Index) - Overbought/oversold
• MACD (Moving Average Convergence Divergence) - Trend and momentum
• Bollinger Bands - Mean reversion and volatility
• Trend (SMA 20/50/200 crossovers) - Trend direction
• Volume - Confirmation of moves
• Stochastic Oscillator - Short-term momentum
• ADX (Average Directional Index) - Trend strength

Prerequisites

Install required dependencies:

pip install yfinance pandas numpy

Optional for visualization:

pip install matplotlib

Instructions

Step 1: Quick Signal Scan

Scan multiple assets for trading opportunities:

python {baseDir}/scripts/scanner.py --watchlist crypto_top10 --period 6m

Output shows signal type (STRONG_BUY/BUY/NEUTRAL/SELL/STRONG_SELL) and confidence for each asset.

Step 2: Detailed Signal Analysis

Get full indicator breakdown for a specific symbol:

python {baseDir}/scripts/scanner.py --symbols BTC-USD --detail

Shows each indicator's contribution:

• Individual signal (BUY/SELL/NEUTRAL)
• Indicator value
• Reasoning (e.g., "RSI oversold at 28.5")

Step 3: Filter and Rank Signals

Find the best opportunities:

# Only buy signals with 70%+ confidence
python {baseDir}/scripts/scanner.py --filter buy --min-confidence 70 --rank confidence

# Rank by most bullish
python {baseDir}/scripts/scanner.py --rank bullish

# Save results to JSON
python {baseDir}/scripts/scanner.py --output signals.json

Step 4: Use Custom Watchlists

Available predefined watchlists:

python {baseDir}/scripts/scanner.py --list-watchlists
python {baseDir}/scripts/scanner.py --watchlist crypto_defi

Watchlists: crypto_top10, crypto_defi, crypto_layer2, stocks_tech, etfs_major

Output

Signal Summary Table

================================================================================
  SIGNAL SCANNER RESULTS
================================================================================

  Symbol       Signal         Confidence          Price    Stop Loss
--------------------------------------------------------------------------------
  BTC-USD      STRONG_BUY          78.5%     $67,234.00  $64,890.00
  ETH-USD      BUY                 62.3%      $3,456.00   $3,312.00
  SOL-USD      NEUTRAL             45.0%        $142.50         N/A
--------------------------------------------------------------------------------

  Summary: 2 Buy | 1 Neutral | 0 Sell
  Scanned: 3 assets | [timestamp]
================================================================================

Detailed Signal Output

======================================================================
  BTC-USD - STRONG_BUY
  Confidence: 78.5% | Price: $67,234.00
======================================================================

  Risk Management:
    Stop Loss:   $64,890.00
    Take Profit: $71,922.00
    Risk/Reward: 1:2.0

  Signal Components:
----------------------------------------------------------------------
    RSI              | STRONG_BUY   | Oversold at 28.5 (< 30)
    MACD             | BUY          | MACD above signal, positive momentum
    Bollinger Bands  | BUY          | Price near lower band (%B = 0.15)
    Trend            | BUY          | Uptrend: price above key MAs
    Volume           | STRONG_BUY   | High volume (2.3x) on up move
    Stochastic       | STRONG_BUY   | Oversold (%K=18.2, %D=21.5)
    ADX              | BUY          | Strong uptrend (ADX=32.1)
----------------------------------------------------------------------

Signal Types

Confidence Interpretation

Configuration

Edit {baseDir}/config/settings.yaml:

indicators:
  rsi:
    period: 14
    overbought: 70
    oversold: 30

signals:
  weights:
    rsi: 1.0
    macd: 1.0
    bollinger: 1.0
    trend: 1.0
    volume: 0.5

Error Handling

See {baseDir}/references/errors.md for common issues:

• API rate limits
• Insufficient data handling
• Network errors

Examples

See {baseDir}/references/examples.md for detailed examples:

• Multi-timeframe analysis
• Custom indicator parameters
• Combining with backtester
• Automated scanning schedules

Integration with Backtester

Test signals historically:

# Generate signal
python {baseDir}/scripts/scanner.py --symbols BTC-USD --detail

# Backtest the strategy that generated the signal
python {baseDir}/../trading-strategy-backtester/skills/backtesting-trading-strategies/scripts/backtest.py \
  --strategy rsi_reversal --symbol BTC-USD --period 1y

Files

Resources

• yfinance for price data
• pandas/numpy for calculations
• Compatible with trading-strategy-backtester plugin