What are the best performing efts

Screening Filters

1. monthly_average_dollar_volume ≥ 100,000

   • Purpose: Ensure ETFs are reasonably liquid and practical to trade.
   • Rationale:
     • “Best-performing” should be investable in the real world. An ETF that is up a lot but only trades a few thousand dollars a day can have huge bid–ask spreads and be hard to get in or out of without moving the price.
     • A minimum average dollar volume of $100K helps filter out obscure, thinly traded ETFs and focus on those with enough market participation to be usable by most investors.

2. year_price_change_pct ≥ 0%

   • Purpose: Filter for ETFs that have at least not lost money over the past year, then rank within that group by performance.
   • Rationale:
     • “Best-performing” implies positive and relatively strong recent returns. Requiring non‑negative 1‑year performance removes clearly underperforming ETFs from consideration.
     • Using 1‑year price change as a performance metric gives a standardized, widely used timeframe to compare ETFs across asset classes and strategies. From that subset, you can then highlight those with the highest returns.

3. expense_ratio ≤ 1.0%

   • Purpose: Exclude excessively expensive ETFs that erode returns through high fees.
   • Rationale:
     • True “best-performing” in a practical sense isn’t just about gross price return; fees matter for net returns to the investor.
     • A 1% cap is loose enough to keep specialized or niche ETFs (which often have higher fees) but cuts out very high‑cost products that are unlikely to be attractive to most investors over time.

4. inception_date ≤ 2024-01-01

   • Purpose: Require ETFs to have at least some history before being labeled as strong performers.
   • Rationale:
     • Very new ETFs (launched after Jan 1, 2024) may show eye‑catching short‑term moves but have no real performance track record and may be extremely illiquid.
     • By excluding the most recently launched funds, the screen focuses on ETFs with at least a modest operating history, making performance data more meaningful and less driven by launch timing or one-off events.

Why Results Match the User’s Request

• The year_price_change filter directly targets recent performance, which is the core of “best‑performing.”
• The liquidity filter (monthly_average_dollar_volume) ensures the ETFs are realistically tradable, aligning with what investors typically mean when they ask for “best” options they can actually buy and sell.
• The expense ratio cap refines the list to ETFs where strong performance is not being offset by excessive fees.
• The inception date filter keeps the focus on ETFs with enough history to make their “best performance” more credible, rather than short‑lived spikes in brand‑new funds.

Together, these filters aim to surface ETFs in the U.S. market that are:

• Performing well over the last year,
• Reasonably liquid,
• Not prohibitively expensive to hold, and
• Established enough to have a meaningful track record.