Etf

Screening Filters

1. monthly_average_dollar_volume ≥ $100,000

   • Purpose: Ensure the ETFs are reasonably liquid and practical to trade.
   • Rationale:
     • A minimum average dollar volume of $100k per month helps filter out very illiquid, obscure ETFs that can have wide bid–ask spreads and price slippage.
     • For someone just asking for ETF information/analysis (without specifying micro-cap or niche products), it’s reasonable to assume they’re better served by ETFs with sufficient trading activity.

2. themes: ['Large Cap Blend Equities', 'Global Equities', 'All Cap Equities', 'Foreign Large Cap Equities', 'Emerging Markets Equities']

   • Purpose: Focus on broad, diversified equity ETFs across major market segments.
   • Rationale:
     • The user asked generally about ETFs, with no narrow theme like “energy only” or “AI only.”
     • These themes capture the core building blocks of many portfolios:
       • Large Cap Blend Equities: broad U.S. large-cap exposure (e.g., S&P 500–style funds).
       • Global Equities: worldwide stock exposure (U.S. + international).
       • All Cap Equities: broad market ETFs including small, mid, and large caps.
       • Foreign Large Cap Equities: developed markets outside the U.S.
       • Emerging Markets Equities: exposure to faster-growing but riskier emerging economies.
     • Collectively, these are the main “core” ETF categories people usually mean when discussing general ETF investing, rather than narrow sector or leveraged products.

3. stock_position_pct: ['MoreThan90Pct']

   • Purpose: Restrict to ETFs that invest at least 90% in stocks (equities).
   • Rationale:
     • This avoids bond funds, commodity funds, alternative strategies, or heavily derivative-based ETFs.
     • It aligns with the selected themes, which are all equity-based.
     • When someone asks for ETF information without specifying asset class, analysts often start with equity ETFs because they are the most common and widely used.

4. expense_ratio ≤ 0.30%

   • Purpose: Filter for relatively low-cost ETFs.
   • Rationale:
     • An expense ratio cap of 0.30% screens out many higher-fee, niche, or actively managed funds.
     • For broad-market equity exposure (the kinds of ETFs implied by the themes), costs are a key criterion; many investors look for inexpensive, index-based ETFs.
     • Staying below 0.30% helps ensure the list is dominated by cost-efficient choices that are more appropriate as core holdings or examples in an analysis.

5. inception_date ≤ 2023-01-01 (using max: '2023-01-01')

   • Purpose: Require ETFs to have at least about a year of history (depending on current date).
   • Rationale:
     • Very new ETFs (incepted after early 2023) may have limited performance track records, low assets, and uncertain viability.
     • For meaningful analysis—return history, volatility, drawdowns, tracking error—you need more than just a few months of data.
     • Filtering for ETFs launched on or before this date increases the likelihood that you can discuss their behavior over different market conditions.

Why Results Match the User’s Request

• The user asked broadly for information or analysis about ETFs without specifying a niche, sector, or highly speculative angle.
• The filters collectively:
  • Focus on mainstream, diversified equity ETFs (via themes and stock_position_pct).
  • Ensure practical investability and tradability (via the dollar volume filter).
  • Emphasize cost-efficiency, which is central to ETF evaluation (expense ratio ≤ 0.30%).
  • Require a reasonable performance history so any analysis is grounded in enough data (inception date filter).

In combination, these filters target established, liquid, low-cost, broad equity ETFs that are well-suited as examples or candidates for general ETF analysis, which aligns with the open-ended nature of the user’s request.