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 Signal Score Meaning STRONG_BUY +2 Multiple strong buy signals aligned BUY +1 Moderate buy signals NEUTRAL 0 No clear direction SELL -1 Moderate sell signals STRONG_SELL -2 Multiple strong sell signals aligned Confidence Interpretation Confidence Interpretation 70-100% High conviction, strong signal 50-70% Moderate conviction 30-50% Weak signal, mixed indicators 0-30% No clear direction, avoid trading 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 File Purpose scripts/scanner.py Main signal scanner scripts/signals.py Signal generation logic scripts/indicators.py Technical indicator calculations config/settings.yaml Configuration Resources yfinance for price data pandas/numpy for calculations Compatible with trading-strategy-backtester plugin