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)

Indicator Condition Points

SMA20 Price > SMA20 +1.0

SMA50 Price > SMA50 +1.0

RSI 50-70 (bullish) +1.0

30-50 (neutral) +0.5

<30 (oversold) +0.25

MACD MACD > Signal +1.0

Histogram rising +0.5

ADX

25 with +DI > -DI +1.5

+DI > -DI only +0.5

Momentum 3mo return / 20 -1 to +2

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