Bullish Scanner

Scans symbols for bullish trends and ranks them by composite score.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python scripts/scan.py SYMBOLS [--top N] [--period PERIOD]

Arguments

• SYMBOLS - Comma-separated ticker symbols (e.g., AAPL,MSFT,GOOGL,NVDA)
• --top - Number of top results to return (default: 30)
• --period - Historical period for analysis: 1mo, 3mo, 6mo (default: 3mo)

Scoring System (max ~8 points)

Output

Returns JSON with:

• scan_date - Timestamp of scan
• symbols_scanned - Total symbols analyzed
• results - Array sorted by score (highest first):
  • symbol, score, price
  • next_earnings, earnings_timing (BMO/AMC)
  • period_return_pct, pct_from_sma20, pct_from_sma50
  • rsi, macd, adx, dmp, dmn
  • signals - List of triggered conditions

Examples

# Scan a few symbols
uv run python scripts/scan.py AAPL,MSFT,GOOGL,NVDA,TSLA

# Get top 10 from larger list
uv run python scripts/scan.py AAPL,MSFT,GOOGL,NVDA,TSLA,AMD,AMZN,META --top 10

# Use 6-month lookback
uv run python scripts/scan.py AAPL,MSFT,GOOGL --period 6mo

Interpretation

• Score > 6: Strong bullish trend
• Score 4-6: Moderate bullish
• Score 2-4: Neutral/weak
• Score < 2: Bearish or no trend

Dependencies

• pandas
• pandas-ta
• yfinance

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.