> ## Documentation Index
> Fetch the complete documentation index at: https://docs.focusalpha.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# ETF Screening

> Select ETFs by wrapper tier, holdings-derived classification, assets, expense ratio, concentration, geography, duration, flows and premium.

ETF Screening selects exchange-traded funds by conditions rather than by name. A screen returns one row per US-listed share class, filtered on what the fund is labelled as and on what its book measures. It answers questions that start from a condition — the cheapest large-cap biotech funds by size, leveraged funds bleeding assets, short-duration treasury funds under ten basis points.

<Info>
  **Plan:** Fund · **Credits:** 1 per call; screen facets are free
</Info>

## What You Can Use ETF Screening For

## Detailed ETF Filter Pages

<CardGroup cols={3}>
  <Card title="By asset class" href="/screening/etf/by-asset-class">The four-level taxonomy filters.</Card>
  <Card title="By geography" href="/screening/etf/by-geography">Measured US/EM shares and region/country segments.</Card>
  <Card title="By wrapper & structure" href="/screening/etf/by-wrapper">The nine tiers and filed flags.</Card>
  <Card title="By size & fees" href="/screening/etf/by-size-and-fees">Class-level AUM and expense ratios.</Card>
  <Card title="By portfolio shape" href="/screening/etf/by-portfolio-shape">Concentration, cap bands, duration.</Card>
  <Card title="By flows & premium" href="/screening/etf/by-flows-and-premium">20-day flows and premium/discount.</Card>
</CardGroup>

Build a peer group from scratch. Find funds whose measured portfolio contradicts their name. Rank a segment by fee, size, concentration or twenty-day flow. Locate the funds most exposed to a region or a cap band without relying on the fund's own marketing label.

## Start With ETF Screen Facets

Call the ETF screen facets endpoint first. It is free and returns the label vocabulary **as it is actually carried by funds**, with a count for each value, plus measured coverage totals.

This matters for two reasons. It is the only place ETF coverage is a number rather than prose. And an empty result from a label filter almost always means the code was misspelled rather than that no such funds exist — the facets response settles which.

## Two ETF Label Axes That Are Not the Same Question

`tier` filters on the **wrapper** — what kind of instrument the fund is. It takes a comma-separated list of the nine values: `leveraged_inverse`, `structured_outcome`, `option_income`, `physical_commodity`, `futures_commodity`, `crypto`, `currency`, `alternative`, `plain_beta`.

`asset_class`, `category`, `segment` and `specializations` filter on the **holdings-derived taxonomy** — what the fund actually holds. `taxonomy_prefix` matches a dotted-path prefix at any level, so `equity.sector` finds every sector fund in one filter.

A fund can be a leveraged wrapper around a health-care segment. Filtering on one axis says nothing about the other.

## Measured Filters Versus Label Filters

Some filters read a label; others read a measurement taken from the fund's holdings. The distinction decides how a question must be phrased.

Sector funds carry no cap-band label, because cap bands are a separate facet. "Large-cap biotech" is therefore not one label but a segment plus a specialization plus a measured floor: `segment=equity.sector.health_care`, `specializations=equity.sector.health_care.biotechnology`, `min_large_share=0.5`. The cap share is measured from holdings.

The measured filters are `min_n_holdings`, `min_top10_share` and `max_top10_share` for concentration; `min_us_share` and `min_em_share` for geography; `min_large_share`, `max_large_share` and `min_small_share` for cap bands; `min_duration`, `max_duration` and `min_treasury_share` for bond books; `min_flow_20d` and `max_flow_20d` for flows; `min_premium` and `max_premium` for premium and discount.

## How ETF Screen Sorting Handles Unknowns

Sorting drops rows whose sort key is null, and on this dataset that is a large and non-random group.

Ranking by expense ratio drops every trust that files no fee table, SPY and GLD included. Ranking by assets drops multi-class portfolios with no derivable class-level size.

When that happens the response carries an `unranked` block saying how many funds matched the filters but could not be ranked. An apparently empty first page with a large `unranked` count means the filters worked and the sort did not — re-run with `sort=ticker` to see the matches.

## Two Cadences in One ETF Screen Row

Labels are recomputed monthly; the measured columns — assets, flows, premium, expense coverage — refresh daily. A newly launched fund can therefore carry a complete set of labels while every measured column is still null. A label filter finds it; any numeric sort moves it into the `unranked` count.

## How ETF Assets Are Measured in a Screen

`aum` is the class-level figure. It is either filed by the fund or derived as published NAV multiplied by published shares on multi-class portfolios, and `aum_is_derived` says which. A portfolio-level number is never served as a share class's size.

## Query the ETF Screen

Use the ETF screen endpoint to select funds. Every filter is combined with AND; a comma-separated value inside one filter means ANY of the listed values. No filter is required.

<ParamField query="tier" type="string">
  Comma-separated wrapper tiers.
</ParamField>

<ParamField query="segment" type="string">
  Comma-separated level-3 taxonomy codes — the peer-group key.
</ParamField>

<ParamField query="taxonomy_prefix" type="string">
  A dotted-path prefix matching any taxonomy level, e.g. `equity.sector`.
</ParamField>

<ParamField query="min_aum" type="number">
  Class-level assets floor in USD. `max_aum` sets the ceiling.
</ParamField>

<ParamField query="max_expense_ratio" type="number">
  Net expense ratio ceiling as a decimal — `0.001` is ten basis points. `min_expense_ratio` sets the floor.
</ParamField>

<ParamField query="min_flow_20d" type="number">
  Twenty-day net flow floor in USD; a negative value finds outflows. `max_flow_20d` sets the ceiling.
</ParamField>

<ParamField query="sort" type="string" default="aum">
  `aum`, `net_expense_ratio`, `flow_20d`, `top10_share`, `premium_discount`, or `ticker`. `aum` defaults to descending; `net_expense_ratio` and `ticker` default to ascending. `order` overrides the direction.
</ParamField>

<ParamField query="limit" type="integer" default="100">
  Rows per page, between 1 and 1000. Page through with `cursor`.
</ParamField>

The full filter set also covers `q`, `exchange`, `active`, `exposure_hidden`, `asset_class`, `category`, `specializations`, `is_index`, `is_fund_of_fund`, `multi_inverse`, and the measured filters listed above.

## Related Datasets

See also [ETF Classification](/etf/classification) for the vocabulary these filters use, [ETF Holdings](/etf/holdings) for the data the measured filters are computed from, [ETF Fees](/etf/fees) for why fee sorting drops funds, and [Company Screening](/companies/screening) and [Adviser Screening](/advisers/screening) for the same pattern on other datasets.

<RequestExample>
  ```bash cURL theme={null}
  curl "https://api.focusalpha.ai/v1/etfs/screen?segment=equity.sector.health_care&min_large_share=0.5&sort=aum" \
    -H "Authorization: Bearer $FOCUSALPHA_API_KEY"
  ```
</RequestExample>

<ResponseExample>
  ```json Response (one row; coverage omitted) theme={null}
  {
    "data": [
      {
        "etf_id": "E000168",
        "portfolio_id": "P000388",
        "ticker": "XLV",
        "name": "State Street Health Care Select Sector SPDR ETF",
        "exchange": "AMEX",
        "currency": "USD",
        "series_class_count": 1,
        "is_sole_class": true,
        "active": true,
        "tier": "plain_beta",
        "exposure_hidden": false,
        "asset_class": "equity",
        "category": "equity.sector",
        "segment": "equity.sector.health_care",
        "specializations": [
          "equity.sector.geo_us",
          "equity.sector.health_care.drug_manufacturers_general"
        ],
        "measured_tags": [],
        "labels_holdings_as_of": "2026-08-28T00:00:00.000Z",
        "is_index": true,
        "is_fund_of_fund": null,
        "is_multi_inverse_index": null,
        "turnover": 0.02,
        "aum": 43909783508.08,
        "aum_is_derived": false,
        "net_assets": 43909783508.08,
        "net_assets_level": "portfolio",
        "net_assets_as_of": "2026-08-31",
        "valuation_date": "2026-08-31",
        "nav": 170.480183,
        "nav_status": "published",
        "shares_outstanding": 257565324,
        "shares_status": "published",
        "premium_discount": 0.03802,
        "gross_expense_ratio": 0.0008,
        "net_expense_ratio": 0.0008,
        "net_is_filed": false,
        "holdings_as_of": "2026-08-28",
        "n_holdings": "62",
        "top1_share": "0.1507",
        "top10_share": "0.6082",
        "us_share": "0.9773",
        "em_share": "0.0000",
        "large_share": "0.8534",
        "mid_share": "0.1466",
        "small_share": "0.0000",
        "duration": null,
        "maturity_years": null,
        "treasury_share": "0.0000",
        "corporate_share": "0.0000",
        "flow_1d": -102719020.2,
        "flow_5d": 277949692.4,
        "flow_20d": 69739330.85
      }
    ],
    "next_cursor": "WyIxOTMwMzc5NTc1My43NiIsIkUwMDAxODEiXQ"
  }
  ```
</ResponseExample>