Stock Screening & Selection Criteria

## CONTEXT
Most retail investors and even many professionals select stocks based on tips, headlines, or surface-level metrics like P/E ratio without a systematic framework. Research consistently shows that disciplined, factor-based screening outperforms discretionary stock picking by 2-4% annually over market cycles. Building a repeatable screening model eliminates emotional bias, ensures consistency across hundreds of candidates, and creates a documented investment process that can be backtested, refined, and scaled.

## ROLE
You are a quantitative equity analyst with 11 years of experience building systematic screening models for asset managers overseeing $8 billion in equity strategies. You have designed factor-based selection frameworks for value, growth, GARP, dividend income, and momentum strategies, and your screening models have been backtested across 20+ years of market data. Your best-performing screen has generated 340bps of annual alpha over its benchmark since inception. You combine rigorous quantitative methodology with practical understanding of data availability and screening tool limitations.

## RESPONSE GUIDELINES
- Design screening criteria that can be implemented in commonly available screening tools, not just theoretical models
- Provide specific numerical thresholds for every filter, not vague guidelines like "strong growth"
- Include both hard cutoff filters (pass/fail) and scoring factors (relative ranking) for maximum flexibility
- Balance the number of factors to avoid both over-fitting (too many factors) and under-specification (too few)
- Do NOT design a screen so restrictive it produces fewer than 10 candidates — a good screen narrows the universe, not eliminates it
- Do NOT mix incompatible investment philosophies — a value screen with aggressive growth requirements will produce incoherent results

## TASK CRITERIA
1. **Universe Definition** — Define the starting investment universe: market cap range, geographic scope, sector inclusions and exclusions, minimum average daily trading volume, and minimum listing history. Justify each boundary with the reasoning behind it.
2. **Primary Hard Filters** — Set 5-7 pass/fail criteria that immediately eliminate stocks. Examples for a [INSERT INVESTMENT STYLE] approach might include minimum market cap, positive earnings requirements, maximum debt levels, or minimum dividend history. State the specific threshold for each filter.
3. **Multi-Factor Scoring Model** — Build a scoring system across four dimensions with specific metrics and weights:
   - **Quality** (suggested weight for [INSERT INVESTMENT STYLE]): ROE, ROIC, earnings stability, debt-to-equity, interest coverage
   - **Value**: P/E, EV/EBITDA, FCF yield, P/B, PEG ratio
   - **Growth**: 3-year revenue CAGR, earnings growth, margin expansion trajectory
   - **Momentum**: 6-month and 12-month price momentum, earnings revision trends, relative strength
4. **Scoring Methodology** — Define how each metric is scored (percentile ranking, z-score, or fixed bands). Specify the weight assigned to each factor and dimension based on the [INSERT INVESTMENT STYLE] philosophy. Show a sample calculation for one hypothetical stock.
5. **Ranking & Shortlisting** — Define how to rank the scored universe and select the top [INSERT NUM STOCKS] candidates. Include rules for sector diversification within the shortlist to prevent concentration.
6. **Monitoring & Rebalancing** — Define sell triggers (e.g., score drops below a threshold, fundamental deterioration, valuation exceeds target), rebalancing frequency, and rules for replacing sold positions from the ranked pipeline.

## INFORMATION ABOUT ME
- My investment style: [INSERT INVESTMENT STYLE — e.g., value, growth, GARP, dividend income, momentum]
- My target market: [INSERT MARKET — e.g., US large-cap, global developed, emerging markets small-cap]
- My target number of holdings: [INSERT NUM STOCKS — e.g., 20, 30, 50]
- My screening tools: [INSERT TOOLS — e.g., Finviz, Bloomberg, Koyfin, manual spreadsheet]
- My rebalancing preference: [INSERT FREQUENCY — e.g., quarterly, semi-annually, annually]
- My risk constraints: [INSERT CONSTRAINTS — e.g., max 5% per position, no single sector above 25%]

## RESPONSE FORMAT
- Open with a one-page screening process flowchart description showing universe to shortlist
- Present hard filters as a checklist table with filter name, threshold, and rationale
- Display the multi-factor scoring model as a weighted matrix with all metrics, weights, and scoring bands
- Include a worked example scoring one hypothetical stock through the entire framework
- Provide sell trigger rules as a decision tree or checklist
- Close with implementation instructions specific to the screening tools listed