Idea Generation

Idea Generation

description: Systematic stock screening and investment idea sourcing. Combines quantitative screens, thematic research, and pattern recognition to surface new long and short ideas. Use when looking for new ideas, running screens, or conducting thematic sweeps. Triggers on "idea generation", "stock screen", "find ideas", "what looks interesting", "screen for", "new ideas", or "pitch me something".

Workflow

Step 1: Define Search Criteria

Ask the user for parameters:

• Direction: Long ideas, short ideas, or both
• Market cap: Large, mid, small, micro
• Sector: Specific sector or cross-sector
• Style: Value, growth, quality, special situation, event-driven
• Geography: US, international, global
• Theme: Any specific thematic angle (AI, reshoring, aging demographics, etc.)

Step 2: Quantitative Screens

Run screens based on the style:

Value Screen

• P/E below sector median
• EV/EBITDA below historical average
• Free cash flow yield >5%
• Price/book below 1.5x
• Insider buying in last 90 days
• Dividend yield above market average

Growth Screen

• Revenue growth >15% YoY
• Earnings growth >20% YoY
• Revenue acceleration (growth rate increasing)
• Expanding margins
• High return on invested capital (>15%)
• Strong net retention (>110% for SaaS)

Quality Screen

• Consistent revenue growth (5+ years)
• Stable or expanding margins
• ROE >15%
• Low debt/equity
• High free cash flow conversion
• Insider ownership >5%

Short Screen

• Declining revenue or decelerating growth
• Margin compression
• Rising receivables / inventory vs. sales
• Insider selling
• Valuation premium to peers without justification
• High short interest with deteriorating fundamentals
• Accounting red flags (auditor changes, restatements)

Special Situation Screen

• Recent IPOs / SPACs with lockup expirations
• Spin-offs in last 12 months
• Companies emerging from restructuring
• Activist involvement
• Management changes at underperforming companies

Step 3: Thematic Sweep

For thematic ideas, research the theme and identify beneficiaries:

1. Define the thesis (e.g., "AI infrastructure spending accelerates through 2026")
2. Map the value chain — who benefits directly vs. indirectly?
3. Identify pure-play vs. diversified exposure
4. Assess which names are already "priced in" vs. under-appreciated
5. Look for second-order beneficiaries that the market hasn't connected to the theme

Step 4: Idea Presentation

For each idea that passes the screen, present:

[Company Name] — [Long/Short] — [One-Line Thesis]

Thesis (3-5 bullets):

• Why this is mispriced
• What the market is missing
• Catalyst to realize value

Key Risks:

• What would make this wrong

Suggested Next Steps:

• Build full model? Deep-dive diligence? Expert call?

Step 5: Output

• Shortlist of 5-10 ideas with one-page summaries
• Screening criteria and methodology documented
• Comparison table across all ideas
• Prioritized list: which ideas to research first

Important Notes

• Screens surface candidates, not conclusions — every screen output needs fundamental work
• The best ideas often come from intersections (e.g., quality company at value price due to temporary headwind)
• Avoid crowded trades — check ownership data, short interest, and how many analysts cover the name
• Contrarian ideas need a catalyst — being early without a catalyst is the same as being wrong
• Track idea hit rates over time — which screens and approaches produce the best ideas?
• Short ideas need higher conviction — timing is harder and risk is asymmetric

Hermes Profile Notes

This skill was packaged from pi-financial-services source path plugins/vertical-plugins/equity-research/skills/idea-generation for the Hermes financial-services profile. Use institutional data connectors first when available, cite sources, and stage outputs for qualified human review.

Common Pitfalls

1. Do not present drafts as investment, legal, tax, or accounting advice.
2. Do not use web search as the primary source when an institutional MCP/data connector is available.
3. Do not execute transactions, contact clients, post to a ledger, or approve onboarding. Stage outputs for review.

Verification Checklist

• Inputs, assumptions, dates, and currencies are explicit.
• Numbers tie across tables, models, decks, and memos.
• Sources are cited and institutional data is preferred where available.
• Output is labeled draft / for human review where appropriate.