Stock Market Screener API

The Screener API filters the whole covered stock universe in a single request — by market capitalisation, exchange, sector, industry, EPS, dividend yield, recent performance and traded volume — and returns the matching tickers with the values you filtered on. It is the endpoint behind “top gainers today”, “large-cap technology companies”, “high-yield dividend payers” and similar screens.

Filters are passed as a JSON array of conditions that all have to hold at once, sorting is a single field with a direction, and results are paginated with limit and offset. Values come from the latest completed trading day — every row carries the date it was taken from in last_day_data_date.

How to call the Screener API

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&filters=[["exchange","=","us"],["market_capitalization",">",10000000000]]&sort=market_capitalization.desc&limit=10&offset=0

Parameters

Request Example

The five largest companies by market capitalisation, no filters:

URL cURL PHP Python R Chat GPT

https://eodhd.com/api/screener?api_token=YOUR_TOKEN&sort=market_capitalization.desc&limit=5

(Sign up for free to get an API token)

curl --location "https://eodhd.com/api/screener?api_token=YOUR_TOKEN&sort=market_capitalization.desc&limit=5&fmt=json"

(Sign up for free to get an API token)

$curl = curl_init();

curl_setopt_array($curl, array(
    CURLOPT_URL => 'https://eodhd.com/api/screener?api_token=YOUR_TOKEN&sort=market_capitalization.desc&limit=5&fmt=json',
    CURLOPT_RETURNTRANSFER => true,
    CURLOPT_ENCODING => '',
    CURLOPT_MAXREDIRS => 10,
    CURLOPT_TIMEOUT => 0,
    CURLOPT_FOLLOWLOCATION => true,
    CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
    CURLOPT_CUSTOMREQUEST => 'GET',
));

$data = curl_exec($curl);
curl_close($curl);

try {
    $data = json_decode($data, true, 512, JSON_THROW_ON_ERROR);
    var_dump($data);
} catch (Exception $e) {
    echo 'Error. '.$e->getMessage();
}

(Sign up for free to get an API token)

import requests

url = f'https://eodhd.com/api/screener?api_token=YOUR_TOKEN&sort=market_capitalization.desc&limit=5&fmt=json'
data = requests.get(url).json()

print(data)

(Sign up for free to get an API token)

library(httr)
library(jsonlite)

url <- 'https://eodhd.com/api/screener?api_token=YOUR_TOKEN&sort=market_capitalization.desc&limit=5&fmt=json'
response <- GET(url)

if (http_type(response) == "application/json") {
    content <- content(response, "text", encoding = "UTF-8")
    cat(content)
} else {
    cat("Error while receiving data\n")
}

(Sign up for free to get an API token)

New to coding? Our ChatGPT assistant can generate code in any language tailored to our API. Simply describe how you want to use our data, and get a working piece of code. Don’t forget to replace the API token with your own.

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How to use it (YouTube)

Response Example

{
    "data": [
        {
            "code": "AAPL",
            "name": "Apple Inc.",
            "last_day_data_date": "2026-08-12",
            "adjusted_close": 302.25,
            "refund_1d": -2.66,
            "refund_1d_p": -0.87,
            "refund_5d": -8.482,
            "refund_5d_p": -2.73,
            "exchange": "US",
            "currency_symbol": "$",
            "market_capitalization": 4411090796544,
            "earnings_share": 8.72,
            "dividend_yield": 0.0034,
            "sector": "Technology",
            "industry": "Consumer Electronics",
            "avgvol_1d": 40588500,
            "avgvol_200d": 49738504
        }
    ]
}

Response Fields

Filter fields

Fourteen fields can be filtered on, and each of them can also be used for sorting. String fields take the string operations, number fields take the numeric ones.

Exchange codes come from the Exchanges API. The full sector and industry taxonomy is available as a CSV download.

Not every ticker carries a value for the fundamentals-derived fields — market capitalisation, EPS, dividend yield, sector, industry and average volume are all missing for a sizeable share of the global universe, mostly on secondary listings and smaller venues. Filtering on one of those fields therefore also excludes every ticker where the value is absent, which is a different result from “every company that fails the condition”. Where that distinction matters, screen per exchange and compare the row counts.

Operations

• match matches from the start of a word, and an asterisk extends the prefix: “Apple” and “App*” both find Apple Inc., while a mid-word fragment such as “pple” matches nothing.
• in and not in take a JSON array as the value, for example [“exchange”,”in”,[“us”,”to”]] or [“sector”,”not in”,[“Technology”,”Energy”]]. A single-element array is fine.
• String comparisons are case-insensitive: “aapl” and “AAPL” behave the same, as do “technology” and “Technology”.
• Applying a numeric operation to a string field, or the other way round, returns HTTP 422 with an invalid-operation error. A screen that matches nothing returns HTTP 200 with an empty data array, and a missing or invalid token returns HTTP 401.

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Signals

Signals are pre-calculated conditions that would be awkward to express as a filter. Pass them comma-separated in the signals parameter. Several signals narrow the result rather than widen it — a ticker has to satisfy every signal listed — and signals combine with filters the same way.

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&signals=bookvalue_neg,200d_new_lo&limit=10

New signals are added over time, and we can build one on request — write to support@eodhistoricaldata.com or raise it in the community subreddit.

Screener API examples

Top gainers of the last trading day

Sort by the one-day percentage change and put a volume floor under it, so the list is not dominated by illiquid micro-caps:

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&filters=[["exchange","=","us"],["avgvol_1d",">",1000000]]&sort=refund_1d_p.desc&limit=10

Large-cap technology companies on NASDAQ

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&filters=[["exchange","=","NASDAQ"],["sector","=","Technology"],["market_capitalization",">",10000000000],["earnings_share",">",0]]&sort=market_capitalization.desc&limit=10

Dividend payers above five percent

Yield is a fraction, so five percent is 0.05. The upper bound and the exchange condition keep the mis-scaled foreign listings out:

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&filters=[["exchange","=","us"],["dividend_yield",">",0.05],["dividend_yield","<",0.25],["market_capitalization",">",1000000000]]&sort=dividend_yield.desc&limit=10

Partial name search across two exchanges

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&filters=[["exchange","in",["us","to"]],["name","match","Apple*"]]&limit=10

More examples

Four screens that combine several conditions at once. Each one was run against the live endpoint and returns real matches.

Income screen with excluded sectors

Profitable US dividend payers above 2 billion, liquid enough to trade, with financials, utilities and real estate left out and the yield capped at a plausible 15% so the mis-scaled rows cannot creep in:

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&filters=[["exchange","=","us"],["sector","not in",["Financial Services","Utilities","Real Estate"]],["earnings_share",">",0],["dividend_yield",">",0.04],["dividend_yield","<",0.15],["market_capitalization",">",2000000000],["avgvol_1d",">",300000]]&sort=dividend_yield.desc&limit=25

Seven conditions in one request. The not in operation takes a JSON array, and the two dividend_yield conditions form a band, since the API has no between operation.

Large caps trading below the analyst target

A signal and a filter set working together: liquid US companies above 10 billion whose price sits under the Wall Street target:

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&signals=wallstreet_lo&filters=[["exchange","=","us"],["adjusted_close",">",5],["market_capitalization",">",10000000000],["avgvol_200d",">",1000000]]&sort=market_capitalization.desc&limit=25

The price and volume floors matter more than they look: without them a signal screen fills up with sub-cent tickers that technically satisfy the condition.

One industry across four markets

Semiconductor companies above 1 billion, listed in the US, Toronto, London or XETRA:

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&filters=[["exchange","in",["us","to","lse","xetra"]],["industry","match","Semiconductors"],["market_capitalization",">",1000000000]]&sort=market_capitalization.desc&limit=25

This is the screen that shows the currency caveat in action. The same company comes back several times — once per listing — and the capitalisations are not comparable, because each is expressed in its own listing currency. Read currency_symbol on every row before ranking them.

NASDAQ mid-caps by name prefix

Companies whose name starts with “Bio”, listed on NASDAQ, with a reported EPS and a capitalisation between 300 million and 20 billion:

https://eodhd.com/api/screener?api_token=YOUR_API_TOKEN&filters=[["sub_exchange","=","NASDAQ"],["name","match","Bio*"],["earnings_share","!=",0],["market_capitalization",">=",300000000],["market_capitalization","<=",20000000000]]&sort=market_capitalization.desc&limit=25

Four techniques in one request: venue selection through sub_exchange, a wildcard name prefix through match, exclusion of unreported EPS through !=, and a capitalisation band built from two inclusive bounds.

Where to go next

The screener returns tickers; the detail comes from the other endpoints. Pull statements and ratios for a match from the Fundamental Data API, price history from the End-of-Day API, and indicators such as RSI or SMA from the Technical Indicators API. To resolve a code you got back into every venue it trades on, use the Search API.

Screening without writing code is possible too: the screener ships inside our Google Sheets and Excel add-ons and in the Python library.