Stock Screener

Surface investment ideas via quantitative screens or thematic sweeps.

Step 1: Define Screen

If user provides criteria, use them. Otherwise ask:

• Market: AR (BYMA panel general/lider, CEDEARs) / US / Both
• Direction: Long / Short / Both
• Style: Value / Growth / Momentum / Income / Quality
• Sector/Theme: (optional) specific sector or thematic filter
• Size: Large / Mid / Small / Any
• Constraints: (optional) liquidity minimums, max P/E, min dividend, etc.

Step 2: Quantitative Screen

Apply filters based on style:

Value: P/E < sector median, P/B < 1.5, EV/EBITDA below peers, FCF yield > 5% Growth: Revenue growth > 15% YoY, EPS growth > 20%, expanding margins Momentum: Price > 50-day MA > 200-day MA, RSI 50-70, positive earnings revisions Income: Dividend yield > 3%, payout ratio < 70%, dividend growth > 5% CAGR Quality: ROE > 15%, debt/equity < 1.0, consistent earnings (no losses in 5yr)

AR-specific filters:

• CEDEARs: check premium/discount vs ADR parity — flag opportunities where discount > 5%
• BYMA local: volume filter (>$1M ARS daily), exclude penny stocks
• Bonds: TIR vs inflation expectations, duration bucket, credit quality

Step 3: Results Table

Step 4: Quick Thesis for Top 3-5

For each top idea, provide:

• Why it passes: 2-3 sentences on what the screen caught
• Bull case: best scenario in 1 sentence
• Bear case: worst scenario in 1 sentence
• Catalyst: what could move it in next 3-6 months
• Risk: primary risk factor

Step 5: Output

═══ SCREEN: [criteria summary] ═══
Market: [AR/US/Both]
Style: [value/growth/momentum/income/quality]
Results: [N] names passed filters
Date: [today]

[Results table]

TOP IDEAS:
1. [TICKER] — [one-liner thesis]
2. [TICKER] — [one-liner thesis]
3. [TICKER] — [one-liner thesis]

Notes

• ALWAYS use current market data — never training data prices
• For AR screens, note if market was open/closed and last trading date
• CEDEARs: always show both CEDEAR price (ARS) and underlying price (USD) with CCL
• Screens are idea generators, not buy recommendations — each needs full thesis development
• If using Cotiza API for AR data, note the data source