🇰🇷 KOSPI Stock Screener — Korean Market Cap & Quotes

Track Korean stocks (KOSPI + KOSDAQ) with market cap, P/E, ROE, foreign-ownership %, sector, and recent price action — straight from Korea Exchange via Naver Finance. The Bloomberg Terminal alternative for Korean equities, priced for indie quants and Asia-focused funds.

Korean equities are one of the most under-instrumented major markets on the open web. Yahoo Finance has spotty KOSPI/KOSDAQ coverage, KRX's official API requires a Korean business registration to access, and most paid data vendors charge $2,000+/month for the same data this actor surfaces in seconds. This actor is built for the rest of us — solo traders, quant researchers, fintech builders, Asia hedge-fund analysts, and anyone running market-neutral or factor strategies that need real Korean coverage.

🎯 What you get per stock

Every record returned includes:

Field	Description
symbol	6-digit KRX ticker (e.g. 005930 for Samsung Electronics)
name	Korean company name (e.g. 삼성전자)
market	KOSPI or KOSDAQ
price_krw	Current price in Korean Won
change_krw	Today's price change in KRW
pct_change	Today's percentage change (signed)
par_value_krw	Par/face value per share
market_cap_billion_krw	Market capitalization in billions of KRW
market_cap_eok_krw	Market cap in 억 (hundred-millions) KRW — Korean convention
shares_outstanding	Total listed shares
foreign_ownership_pct	Percentage held by foreign investors (a key Korean-market signal)
volume	Today's trading volume in shares
per	Price-to-Earnings ratio
roe	Return on Equity (%)
sector	WICS sector (when enrich_sector=true)
wics_industry	WICS industry classification
naver_url	Direct link to the stock's Naver Finance page
scraped_at	UTC timestamp of the scrape

🚀 Quick start

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nexgendata/kospi-stock-screener").call(run_input={
    "market": "KOSPI",
    "limit": 100,
    "min_market_cap_billion_krw": 1000  # 1 trillion KRW+ only
})

for stock in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{stock['symbol']:<8} {stock['name']:<20} "
          f"₩{stock['price_krw']:>12,.0f}  "
          f"PER {stock['per']:>6}  "
          f"MCap {stock['market_cap_billion_krw']:>10,.0f}억")

Sample output:

005930   삼성전자                ₩    268,500  PER   40.9  MCap  1,569,725억
000660   SK하이닉스              ₩  1,686,000  PER   28.6  MCap  1,201,616억
207940   삼성바이오로직스        ₩  1,043,000  PER   84.5  MCap    742,810억
...

🌐 cURL

curl -X POST "https://api.apify.com/v2/acts/nexgendata~kospi-stock-screener/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"market":"all","limit":50}'

📊 Real-world use cases

• Quant research — pull the full KOSPI universe nightly, build factor models on PER, ROE, foreign-ownership %, and price momentum without paying a six-figure data subscription.
• ETF construction — define your own KOSPI200 or KOSDAQ150 alternative by filtering on minimum market cap and rebalancing weekly.
• Asia macro dashboards — track which sectors are absorbing or shedding foreign-investor flows; foreign ownership change is one of the most-watched signals in Korean markets.
• Korea-versus-China comparisons — pair this actor with eastmoney-china-stock-screener to build cross-market relative-value screens (e.g. Korean vs Chinese semiconductors).
• Academic finance research — Korean retail-investor behavior is a huge area of academic study; this actor gives reproducible market snapshots without scraping headaches.
• Fintech app data layers — power a Korean-equity widget for your robo-advisor, trading-journal app, or portfolio tracker.
• Hedge-fund daily refresh — schedule via the Apify scheduler at the post-close (15:30 KST = 06:30 UTC) and pipe the dataset into your warehouse.
• News + sentiment overlays — join with company-name lookups to attribute Korean-language news flow back to ticker IDs.

⚙️ Input parameters

Param	Type	Default	Notes
market	enum	KOSPI	KOSPI, KOSDAQ, or all
limit	int	50	Max stocks per market (1–2000)
sector	string	""	Substring filter (Korean or English) on sector / industry / name
min_market_cap_billion_krw	int	0	Filter: only stocks above this market cap (billion KRW)
enrich_sector	bool	false	Hit each detail page for WICS sector (slower; ~1 extra request per stock)
proxyConfiguration	object	residential	Apify proxy config

Examples

Just the top 10 KOSPI names (fast smoke test):

{ "market": "KOSPI", "limit": 10 }

KOSDAQ growth screen — top 100 by market cap, only names above ₩1 trillion:

{ "market": "KOSDAQ", "limit": 100, "min_market_cap_billion_krw": 1000 }

Korean semiconductor universe (with sector enrichment):

{ "market": "all", "limit": 500, "sector": "반도체", "enrich_sector": true }

Big-board only (KOSPI ≥10조원 / 10 trillion KRW):

{ "market": "KOSPI", "limit": 200, "min_market_cap_billion_krw": 10000 }

💰 Pricing

This actor uses pay-per-event pricing — you only pay for what you actually pull.

• Actor start: $0.005 per run
• Stock record: $0.02 per stock returned

So a typical 100-stock screen costs roughly $2.00. The full KOSPI top-200 large-cap snapshot is about $4.00. Compare to:

• Bloomberg Terminal — $24,000/year minimum
• Refinitiv (LSEG) Eikon — $22,000+/year
• KRX paid feed — only available to Korean entities, with a contract minimum

This actor pays for itself the first time you'd otherwise have spun up a Korean broker account just for the data.

🤔 FAQ

Q: Is the data real-time? Naver Finance lags the live KRX tape by 15–20 minutes during market hours (KST 09:00–15:30). After-hours, it shows the closing snapshot. This is the same delay you get from Yahoo Finance — sufficient for research, screening, and end-of-day rebalancing. For sub-second tick data you need a paid KRX licensee.

Q: What about volume = 0? On weekends, holidays, and pre-market hours the volume column is 0 because no trading has occurred yet. Price/PER/ROE remain valid — they reflect the most recent close.

Q: Can I get historical data? This actor returns the current snapshot. For historical price series, pair it with yahoo-finance-scraper using the symbol + .KS suffix (KOSPI) or .KQ (KOSDAQ).

Q: Korean names are unreadable in my CSV. Save the file as UTF-8 with BOM and open in Excel via Data → From Text/CSV. Or use pandas.read_csv(..., encoding='utf-8-sig') in Python.

Q: How do I match names to English company labels? Most major KOSPI names map cleanly: 삼성전자 = Samsung Electronics, SK하이닉스 = SK Hynix, 현대차 = Hyundai Motor, LG에너지솔루션 = LG Energy Solution, 포스코홀딩스 = POSCO Holdings, 네이버 = NAVER, 카카오 = Kakao. For a complete mapping, query the Korea Exchange's English ticker file or use the .KS/.KQ Yahoo symbology.

Q: Can I use this commercially? The data comes from Naver's public market summary page, which the Korean public has free access to. You own the output dataset. For redistribution as a paid product or syndication, consult Naver's Terms of Service and consider licensing direct from KRX.

Q: Is this maintained? Yes — NexGenData maintains 170+ Apify actors and ships fixes within 24 hours of bug reports. File issues via the Apify console's Issues tab on this actor's page.

Q: Why pay for this when I could scrape Naver myself? You could! But you'd spend a weekend dealing with EUC-KR encoding gotchas, handling pagination, parsing the table structure (which Naver tweaks every few months), figuring out the 억 vs 조 vs 원 unit conversions, setting up residential proxies for foreign IPs, and writing the rate-limit retry logic. Or you can pay $2 per 100-stock run and get it back as clean JSON in 15 seconds.

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Explore the NexGenData Equity Data Suite

This actor is part of NexGenData's global equity data fleet. Whether you cover a single region or a multi-asset macro book, we have a screener for every major market:

Regional sisters

• 🔗 TWSE Stock Screener (Taiwan) — TWSE + TPEx fundamentals, market cap (TWD), P/E, dividend yield, sector — TSMC, MediaTek, Hon Hai universe.
• 🔗 TSE Japan Stock Screener — Tokyo Stock Exchange (Nikkei 225 / TOPIX) fundamentals, market cap (JPY), P/E, P/B, dividend yield, sector.
• 🔗 HKEX Hang Seng Stock Screener — Hang Seng + HSCEI live quotes, market cap (HKD), P/E, dividend yield, sector — Tencent, HSBC, AIA universe.

Cross-region peers

• 🔗 Eastmoney China A-Share Screener — Shanghai + Shenzhen + STAR + ChiNext full A-share universe — the broadest Chinese equity screener.
• 🔗 LSE UK Stock Screener — London Stock Exchange (FTSE 100 / 250) fundamentals, market cap (GBP), P/E, dividend yield, sector — UK equity data.

Multi-asset / specialty

• 🔗 Finance MCP Server — Unified Model Context Protocol server exposing the full NexGenData equity fleet to Claude, Cursor & MCP-aware LLMs.

Browse the full NexGenData catalog

→ See all 220+ NexGenData actors at apify.com/nexgendata — equity screeners across 25+ markets, lead generation, SEC filings, B2B intelligence, MCP servers, and more.

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Why NexGenData vs. paid alternatives

Tool	Annual cost	API access	Coverage
Bloomberg Terminal	~$24,000/seat	Limited	Global
FactSet	~$15,000/seat	Paid add-on	Global
Refinitiv Eikon	~$22,000/seat	Paid add-on	Global
S&P Capital IQ	~$20,000/seat	Paid add-on	Global
NexGenData Korea Screener	Pay-per-result	Native	Korea

Run this actor once per day for a typical institutional-scale workflow (~200 records/day) and your annual cost is approximately $1,800–2,000 — a 90-95% discount vs. the major paid alternatives, with no seat licensing, no minimum commitment, and full programmatic access.

🚀 Apify affiliate program

New to Apify? Sign up with our referral link — you get free platform credits on signup, and you help fund the maintenance of this actor fleet.

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Built and maintained by NexGenData — 170+ actors covering scraping, enrichment, MCP servers, and automation. Home: thenextgennexus.com.

🌏 Related: Asia & APAC Stock Screeners

Part of the NexGenData global equity coverage cluster — 16 stock screeners across Asia, Oceania, and the Middle East with a consistent schema (ticker, name, price, market cap, PE, PB, % change) so you can join them downstream into a single dataset for cross-market screening, factor investing, and quant research.

Greater China & Hong Kong

• 🇨🇳 Eastmoney China A-Shares Screener — Shanghai/Shenzhen mainboards
• 🇨🇳 Shanghai STAR Market Screener — 上海科创板 · sci-tech innovation
• 🇨🇳 Shenzhen ChiNext Screener — 深圳创业板 · growth board
• 🇨🇳 Beijing Stock Exchange Screener — 北京证券交易所 · innovation SMEs
• 🇭🇰 HKEX Hang Seng Screener — Hong Kong · 香港恒生指數

Northeast Asia

• 🇹🇼 Taiwan TWSE Screener — 台灣證交所
• 🇰🇷 KOSPI Stock Screener — South Korea · Korean market cap (you are here)
• 🇯🇵 TSE Japan Stock Screener — Nikkei 225

Southeast Asia (ASEAN)

• 🇸🇬 SGX Singapore Stock Screener — STI · Straits Times Index
• 🇻🇳 HOSE Vietnam Stock Screener — VN30
• 🇮🇩 IDX Indonesia Stock Screener — LQ45
• 🇹🇭 SET Thailand Stock Screener — SET50
• 🇲🇾 Bursa Malaysia Stock Screener — KLCI
• 🇵🇭 PSE Philippines Stock Screener — PSEi

Oceania & Middle East

• 🇦🇺 ASX Australia Stock Screener — ASX 200
• 🇸🇦 Tadawul Saudi Stock Screener — TASI

💡 Bundle tip: All 16 screeners share the same output schema. Run them on the same date and stack the datasets to build a complete APAC equity coverage snapshot for portfolio analytics, ETF construction, or regional momentum strategies.