How about only stocks under $20

Screening Filters

1. Price ≤ $20 (price: {max: 20})

   • Purpose: Limit results to lower-priced stocks under $20 per share.
   • Rationale: Directly implements your updated request to only include stocks under $20, which can be attractive for position sizing and for traders with smaller capital.

2. Monthly Average Dollar Volume ≥ $1,000,000 (monthly_average_dollar_volume: {min: 1000000})

   • Purpose: Ensure sufficient liquidity.
   • Rationale: Swing trades need tight spreads and the ability to enter/exit without moving the price much. A minimum dollar volume filter helps avoid illiquid “dead” tickers that are hard to trade.

3. Price Above 20-day and 200-day Moving Averages (moving_average_relationship: ['PriceAboveMA20', 'PriceAboveMA200'])

   • Purpose: Focus on stocks in an established uptrend on both short- and long-term horizons.
   • Rationale: For swing trading, being above the 20-day MA suggests near-term strength; above the 200-day MA indicates a broader uptrend. This combination targets pullbacks/continuations within healthy uptrends rather than fighting downtrends.

4. Moderate RSI (rsi_category: ['moderate'])

   • Purpose: Avoid stocks that are extremely overbought or oversold.
   • Rationale: Extreme RSI can signal exhaustion or sharp mean-reversion risk. “Moderate” RSI often aligns with more sustainable trends and cleaner swing setups, rather than late entries after big spikes.

5. 1-Month Price Change between +5% and +30% (month_price_change_pct: {min: 5, max: 30})

   • Purpose: Capture names with recent positive momentum, but not runaway movers.
   • Rationale: For swing trading, you usually want some demonstrated strength (≥ +5%) but not parabolic moves that are prone to violent reversals (> +30% in a month). This range balances momentum with risk control.

6. Technology-Oriented Sectors (sector: ['Technology', 'Software & IT Services', 'Technology Equipment'])

   • Purpose: Restrict results to technology-related businesses.
   • Rationale: These sector tags operationalize your request for “technology stocks,” covering core tech, software, and hardware/equipment companies.

7. NASDAQ Listing (list_exchange: ['XNAS'])

   • Purpose: Only include stocks listed on the NASDAQ exchange.
   • Rationale: This directly matches your requirement for “on Nasdaq” and excludes NYSE/AMEX or other exchanges.

8. US Region (region: ['United States'])

   • Purpose: Ensure the companies are US-based.
   • Rationale: Implements your “based in USA” constraint, filtering out foreign listings or ADRs.

9. Non-negative Predicted 1-Week Return (one_week_predict_return: {min: 0})

   • Purpose: Remove names where the model expects negative short-term performance.
   • Rationale: For swing trades, you generally want at least a non-negative expected edge, even if it’s modest. This is a probabilistic filter, not a guarantee, but it tilts the list toward names the model doesn’t see as unfavorable in the very near term.

10. Non-negative 1-Week Rise Probability (one_week_rise_prob: {min: 0})

• Purpose: Act as a soft gate for model-based probability of a rise.
• Rationale: A minimum of 0 means almost everything passes, but this field is primarily useful for ranking (e.g., preferring higher rise probabilities). It supports the swing-trade objective by helping prioritize names with stronger modeled odds of short-term gains.

Why Results Match Your Request

• Under $20: Implemented via price: {max: 20}.
• NASDAQ only: Enforced with list_exchange: ['XNAS'].
• Technology stocks: Targeted using tech-related sector filters.
• Based in USA: Ensured through region: ['United States'].
• Swing-trade friendly:
  • Trend filters (above 20- and 200-day MAs) and 1-month performance band focus on healthy uptrends with manageable volatility.
  • Liquidity and RSI filters support practical, tradable swing setups rather than illiquid or overstretched names.
  • Predictive fields help nudge the list toward better short-term prospects.

All requested constraints are supported and have been translated directly into the filters above, with additional swing-trading–oriented filters to improve the quality and tradability of the results.