Global Stock Exchange Screener

Screen 26 global stock exchanges in a single API call — from Xetra and the LSE to the TSE, HKEX, NSE and the China A-share boards. Returns either a flat list of per-stock rows or a per-exchange market summary as clean JSON. Built for analysts, quant researchers, fintech builders and AI agents. Factual public data — not financial or investment advice.

📊 Sample Output

exchange	country	region	currency	snapshot_ts	median_change_pct
TSE_JAPAN	Japan	Asia-Pacific	JPY	2026-09-25T00:06:00.278889Z	-0.725
HKEX	Hong Kong	Asia-Pacific	HKD	2026-09-25T00:06:00.352956Z	-0.18
LSE_UK	United Kingdom	Europe	GBP	2026-09-25T00:06:00.376656Z	-0.44999999999999996

Real rows from run IfagltBm1KZ0c1a4i on build 0.0.8 (2026-09-25), unedited apart from masked emails/phones and shortened long text; fields the source does not publish are empty.

🔧 Input reference

Field	Type	Default	What it does
exchanges	array of string	["TSE_JAPAN", "HKEX", "LSE_UK"]	List of exchange codes to include in this snapshot. Pick any subset of the 25 supported exchanges (KOSPI, TWSE, NSE_INDIA, BSE_INDIA, B3_BRAZIL, HKEX, SGX, HOSE_VIETNAM, TSE_JAPAN…
outputMode	string (per_exchange_summary, per_stock)	"per_exchange_summary"	Shape of the dataset rows. per_exchange_summary returns ONE aggregated row per exchange (top 5 gainers, top 5 losers, top 10 by market cap, advancers/decliners, median change) —…
topN	integer	50	How many stocks to fetch per exchange. In per_exchange_summary mode this controls the underlying universe used to compute aggregates (default 50 is sufficient for top-movers / i…
maxParallel	integer	5	How many sub-actors to run concurrently. Higher = faster wall-clock but more peak memory + risk of provider rate-limits. 5 is the sweet spot for a global snapshot across 25 exchan…
subActorTimeoutSecs	integer	300	Maximum seconds to wait for any one sub-actor run to complete. If a single exchange screener stalls (regional outage, captcha), it will be cut off and the error recorded in that e…

🧾 JSON sample record

One real record from run IfagltBm1KZ0c1a4i (emails/phones masked, long text shortened):

{
  "exchange": "TSE_JAPAN",
  "country": "Japan",
  "region": "Asia-Pacific",
  "currency": "JPY",
  "snapshot_ts": "2026-09-25T00:06:00.278889Z",
  "stock_count": 50,
  "top_gainers": [
    {
      "symbol": "5802",
      "name": "Sumitomo Electric Industries, Ltd.",
      "price": 2200.5,
      "change_pct": 5.77,
      "market_cap": 6860000000000
    },
    {
      "symbol": "6752",
      "name": "Panasonic Holdings Corporation",
      "price": 4508,
      "change_pct": 5.16,
      "market_cap": 10530000000000
    },
    {
      "symbol": "6857",
      "name": "Advantest Corporation",
      "price": 33060,
      "change_pct": 3.15,
      "market_cap": 23930000000000
    },
    {
      "symbol": "6503",
      "name": "Mitsubishi Electric Corporation",
      "price": 5274,
      "change_pct": 2.89,
      "market_cap": 10800000000000
    },
    {
      "symbol": "6954",
      "name": "Fanuc Corporation",
      "price": 6021,
      "change_pct": 2.89,
      "market_cap": 5620000000000
    }
  ],
  "top_losers": [
    {
      "symbol": "6098",
      "name": "Recruit Holdings Co., Ltd.",
      "price": 16000,
      "change_pct": -7.78,
      "market_cap": 22270000000000
    },
    {
      "symbol": "8725",
      "name": "MS&AD Insurance Group Holdings, Inc.",
      "price": 4970,
      "change_pct": -4.73,
      "market_cap": 7160000000000
    },
    {
      "symbol": "8001",
      "name": "ITOCHU Corporation",
      "price": 2220.5,
      "change_pct": -3.73,
      "market_cap": 15340000000000
    },
    {
      "symbol": "8766",
      "name": "Tokio Marine Holdings, Inc.",
      "price": 7932,
      "change_pct": -3.27,
      "market_cap": 15070000000000
    },
    {
      "symbol": "8058",
      "name": "Mitsubishi Corporation",
      "price": 4811,
      "change_pct": -2.75,
      "market_cap": 17620000000000
    }
  ],
  "top_by_market_cap": [
    {
      "symbol": "8306",
      "name": "Mitsubishi UFJ Financial Group, Inc.",
      "price": 3573,
      "change_pct": -1.3,
      "market_cap": 40220000000000
    },
    {
      "symbol": "9984",
      "name": "SoftBank Group Corp.",
      "price": 6352,
      "change_pct": 0.59,
      "market_cap": 36200000000000
    },
    {
      "symbol": "7203",
      "name": "Toyota Motor Corporation",
      "price": 2969,
      "change_pct": -1.85,
      "market_cap": 35070000000000
    },
    {
      "symbol": "8316",
      "name": "Sumitomo Mitsui Financial Group, Inc.",
      "price": 6679,
      "change_pct": -2.21,
      "market_cap": 25120000000000
    },
    {
      "symbol": "6501",
      "name": "Hitachi, Ltd.",
      "price": 5497,
      "change_pct": -0.49,
      "market_cap": 24650000000000
    },
    {
      "symbol": "8035",
      "name": "Tokyo Electron Limited",
      "price": 53920,
      "change_pct": 1.53,
      "market_cap": 24510000000000
    },
    {
      "symbol": "6857",
      "name": "Advantest Corporation",
      "price": 33060,
      "change_pct": 3.15,
      "market_cap": 23930000000000
    },
    {
      "symbol": "6098",
      "name": "Recruit Holdings Co., Ltd.",
      "price": 16000,
      "change_pct": -7.78,
      "market_cap": 22270000000000
    },
    "…"
  ],
  "median_change_pct": -0.725,
  "advancers": 18,
  "decliners": 32,
  "unchanged": 0,
  "error": null
}

💰 Pricing

Event	Price (USD)	When it is charged
Actor Start (apify-actor-start)	$5e-05	Charged when the Actor starts running. Number of events charged depends on Actor memory (one event per GB, minimum one event).
Stock or exchange snapshot (apify-default-dataset-item)	$0.05	Charged per result returned - one item per exchange in summary mode, or one item per stock in per_stock mode.

Pay-per-event: you pay only for what the run delivers. A run that delivers nothing bills no result events (only the actor-start event, when the actor defines one). Example: a run that delivers 100 results costs 100 × $0.05 = $5.00 plus the start fee.

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Full catalog: NexGenData on Apify.

📊 What you get

Two output modes (outputMode):

per_stock — one record per stock across the exchanges you select:

• symbol — Exchange ticker symbol
• name — Company name
• exchange — Source exchange
• country / region — Market location
• price / currency — Latest price and its currency
• change_pct — Daily percent change
• market_cap — Market capitalization
• sector — Sector classification
• volume — Trading volume
• raw — The full source row from that exchange's screener

per_exchange_summary — one record per exchange:

• exchange / country / region — Market identity
• stock_count — Number of stocks covered
• advancers / decliners / unchanged — Breadth counts
• median_change_pct — Median daily change
• top_by_market_cap / top_gainers / top_losers — Leader lists
• snapshot_ts — Snapshot timestamp

Pricing: $0.05 per record (Pay-Per-Event) — about 20 per $1. Actor start fee $5e-05 per run. Live prices are in the Pricing table below.

🤖 Use with AI agents

This is the single-call front door to NexGenData's screener franchise: instead of orchestrating 26 separate actors, an agent points here, picks its exchanges and output mode, and gets a unified, structured result. Works with Claude, the OpenAI Agents SDK, n8n, or any MCP-aware client.

Sample agent prompt:

Give me a per-exchange market summary for the LSE, TSE and NSE, then the top 10 stocks by market cap on each as JSON.

Agentic payments (x402): Supports agentic payment via x402 — agents can call this actor with USDC, no API key required.

⏰ Run on a schedule

Refresh a multi-market snapshot weekly:

{
  "exchanges": ["XETRA_GERMANY", "LSE_UK", "TSE_JAPAN", "NSE_INDIA"],
  "outputMode": "per_exchange_summary",
  "topN": 50
}

🔗 Related screeners

Agent-native front door: Global Equities Screener MCP — the same coverage as an MCP server for AI agents.

Single-market screeners: Germany (Xetra), UK (LSE), Japan (TSE), Hong Kong (HKEX), India (NSE) — and 21 more national exchanges.

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Aggregates NexGenData's per-exchange screeners from public market data. Factual public data — not financial or investment advice.