# Finviz Stock Screener Scraper (`parseforge/finviz-scraper`) Actor Screen 11,000+ US-listed stocks on Finviz with 30+ signal presets and 9 filter dimensions. Enriches each ticker with 70+ fundamental and technical fields. No API key required. - **URL**: https://apify.com/parseforge/finviz-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $18.75 / 1,000 result items This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ![ParseForge Banner](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner.jpg) ## 📈 Finviz Stock Screener Scraper > 🚀 **Screen 11,000+ US-listed stocks and ETFs in seconds.** Filter by signal, sector, market cap, and 30+ technical or fundamental knobs, then pull 80+ data points per ticker. No API key, no login, no manual CSV wrangling. > 🕒 **Last updated:** 2026-05-17 · **📊 85 fields** per record · **11,138 tickers** in the universe · **33 signal presets** · **152 industries · 62 countries** Finviz is the visual screener traders open every morning. It crunches price action, fundamentals, ownership, analyst recommendations, and chart patterns into one searchable grid covering essentially every stock and ETF listed on NASDAQ, NYSE, AMEX, and CBOE. The site exposes filters that span valuation (P/E, PEG, P/B, P/S, EV/EBITDA), profitability (ROE, ROA, margins), growth (EPS and sales Y/Y, quarter-over-quarter), technicals (SMA, RSI, ATR, beta, chart patterns), ownership (insider, institutional, short interest), and event-driven signals (earnings dates, upgrades, downgrades, unusual volume). Pulling all of that data into a spreadsheet, watchlist, or quant pipeline normally means glueing together a CSV export tool, a paid API, and a handful of manual lookups. This scraper does the glue. Hand it a signal preset like **Top Gainers** or **Recent Insider Buying**, narrow with sector and market cap filters, or just feed it a list of tickers. It returns clean JSON with **85 fields per row**, merging the screener result with the dedicated quote page so you also get target prices, analyst ratings, dividend history, earnings dates, 52-week range distance, and full technical context. Built on the same fast Bun + fetch stack we use for our other markets actors, with retries and Apify residential proxy support baked in. | 🎯 Target Audience | 💡 Primary Use Cases | |---|---| | 📈 Retail traders building rule-based watchlists | Find the next breakout: top gainers, unusual volume, new highs | | 🧮 Quantitative analysts and backtesters | Pull factor data (value, momentum, quality) for thousands of tickers | | 🏦 Hedge fund research desks tracking flows | Track insider transactions and institutional ownership changes daily | | 🤖 Trading bot and signal app builders | Feed live fundamentals and technicals into systematic strategies | | 📰 Financial bloggers, newsletters, podcasts | Pull screened tables for daily market commentary and content | | 🧑‍🎓 Students and finance educators | Build coursework datasets covering the full US equity universe | --- ### 📋 What the Finviz Stock Screener Scraper does - 📡 **One unified screen.** Combine signal presets, sector, industry, country, market cap, exchange, and index filters, plus raw Finviz filter expressions for advanced screens. - 📊 **80+ fields per ticker.** Pulls Overview screener row, then enriches with the dedicated quote page for fundamentals, technicals, ownership, analyst, and dividend data. - 🔍 **Signal presets in one click.** 33 built-in scans including Top Gainers, Top Losers, Most Active, Unusual Volume, Overbought, Oversold, Recent Insider Buying, Earnings Before / After Hours, and 16 chart patterns. - 🚀 **Whole-universe coverage.** Walks pagination across the full 11,138-stock Finviz universe so a single run can sweep up to 1M records. - 💾 **Stable output schema.** Same 85 columns whether you screen one ticker or ten thousand, so it drops straight into your warehouse or notebook. - 🛰️ **Residential proxies, retries, jitter.** Apify residential US proxy by default with exponential back-off so longer runs do not stall. Each record covers the ticker, company name, sector, industry, country, exchange, market cap (string and numeric), price, daily change, volume, valuation ratios (P/E, forward P/E, PEG, P/S, P/B, P/C, P/FCF, EV/EBITDA, EV/Sales), growth (EPS this year, next 5Y, past 3/5Y, Q/Q, Y/Y; same for sales), profitability (gross / operating / profit margin, ROA, ROE, ROI), balance sheet (current ratio, quick ratio, debt/equity, LT debt/equity, book/sh, cash/sh), ownership (insider, institutional, short float, short ratio), analysts (target price, recommendation 1-5), technicals (SMA20, SMA50, SMA200, RSI, beta, ATR, volatility, 52W high/low distance), performance (week, month, quarter, half-year, year, YTD), dividends (yield, payout ratio), and event data (earnings date, IPO date, index membership). > 💡 **Why it matters:** Yahoo Finance is great for prices, but the analytical framework, the screening grid, the chart pattern detection, the insider transaction feed, all of that lives on Finviz. Pulling it programmatically lets you stop watching the morning grid and start automating against it. --- ### 🎬 Full Demo 🚧 Coming soon: a 3-minute walkthrough showing how to run a signal preset, refine with sector filters, and pipe the JSON into a spreadsheet or trading bot. --- ### ⚙️ Input
FieldTypeRequiredDescription
tickersarray of stringsNoRestrict the screen to a specific list (e.g. AAPL, NVDA). Leave empty to scan the full universe.
signalenumNoOne of 33 Finviz signal presets: Top Gainers, Top Losers, Most Active, Unusual Volume, Overbought, Oversold, Recent Insider Buying, Major News, Wedge Up, and many more.
exchangeenumNoAMEX, CBOE, NASDAQ, NYSE.
indexenumNoS&P 500, NDX, DJIA, Russell 2000 constituents only.
sectorenumNoOne of 11 GICS-style sectors (Technology, Healthcare, Financial, Energy, etc.).
industryenumNoOne of 152 industries, plus shortcuts for Stocks Only or Stocks Only excluding Funds & Shell Companies.
countryenumNoOne of 62 countries of headquarters (USA, China, UK, Canada, etc.).
marketCapenumNoMega, Large, Mid, Small, Micro, Nano, or combined buckets like Large+ or Small-.
customFiltersstringNoAdvanced: raw Finviz filter expression to append (e.g. fa_pe_low20,ta_sma200_pa).
sortByenumNoColumn used to order results (market cap, P/E, change, volume, RSI, etc.).
sortDirectionenumNoAscending or descending. Defaults to descending.
enrichbooleanNoPull the dedicated quote page for each ticker to merge 70+ extra fields. On by default.
maxItemsintegerNoFree plan: 10. Paid plan: up to 1,000,000.
Example: pull today's top 25 gainers across all US exchanges with full enrichment. ```json { "signal": "ta_topgainers", "maxItems": 25, "enrich": true } ```` Example: scan Technology mega-caps in the S\&P 500, sorted by P/E ascending. ```json { "index": "sp500", "sector": "technology", "marketCap": "large", "sortBy": "pe", "sortDirection": "asc", "maxItems": 50, "enrich": true } ``` > ⚠️ **Good to Know:** Some fields (P/E, dividend yield, payout ratio) come back null for unprofitable companies, ETFs, or recent IPOs. That mirrors the source. Set `enrich: false` if you only need the screener row and want to save one HTTP request per ticker. *** ### 📊 Output Each record is a flat JSON object with one ticker per row. The schema is stable regardless of which filters you apply. #### 🧾 Schema | Field | Type | Example | |---|---|---| | 🏷️ ticker | string | `AAPL` | | 🏢 company | string | `Apple Inc` | | 🗂️ sector | string | `Technology` | | 🏭 industry | string | `Consumer Electronics` | | 🌍 country | string | `USA` | | 🏛️ exchange | string | `NASD` | | 💰 marketCap | string | `4409.59B` | | 🔢 marketCapValue | number | `4409590000000` | | 💲 price | number | `300.23` | | 📈 changePercent | number | `0.68` | | 📊 volume | number | `54669886` | | 🔁 relativeVolume | number | `1.25` | | 📐 pe / forwardPe / peg | number | `36.32 / 31.31 / 2.57` | | 📏 ps / pb / pc / pfcf | number | `9.77 / 41.35 / 64.37 / 34.14` | | 🏦 evEbitda / evSales | number | `27.67 / 9.80` | | 💵 dividendYield / payoutRatio | number | `0.35 / 13.66` | | 💹 eps / epsNextY / epsNextQ | number | `8.27 / 9.59 / 1.88` | | 📈 epsYoyTtm / salesYoyTtm | number | `28.91 / 12.76` | | 🧮 grossMargin / operMargin / profitMargin | number | `47.86 / 32.64 / 27.15` | | 🏆 roa / roe / roi | number | `34.91 / 141.47 / 67.76` | | ⚖️ currentRatio / quickRatio | number | `1.07 / 1.02` | | 🔻 debtEq / ltDebtEq | number | `0.80 / 0.70` | | 👥 insiderOwn / instOwn | number | `0.12 / 66.02` | | 🔄 insiderTrans / instTrans | number | `-1.93 / 0.53` | | 🩳 shortFloat / shortRatio | number | `0.92 / 3.09` | | 🎯 targetPrice / recommendation | number | `312.56 / 1.92` | | 📉 sma20 / sma50 / sma200 | number | `6.64 / 12.79 / 15.86` | | 🌡️ rsi / beta / atr | number | `75.66 / 1.07 / 6.24` | | 📅 perfWeek / perfMonth / perfYear / perfYTD | number | `2.36 / 13.98 / 41.99 / 10.44` | | 📆 earningsDate / ipoDate | string | `Apr 30 AMC / Dec 12, 1980` | | 🏷️ indexMembership | string | `DJIA, NDX, S&P 500` | | 🔗 url | string | `https://finviz.com/quote.ashx?t=AAPL` | | ⏱️ scrapedAt | string | `2026-05-17T14:46:28.244Z` | #### 📦 Sample records
Typical - AAPL (mega-cap, fully populated) ```json { "ticker": "AAPL", "company": "Apple Inc", "sector": "Technology", "industry": "Consumer Electronics", "country": "USA", "exchange": "NASD", "marketCap": "4409.59B", "marketCapValue": 4409590000000, "price": 300.23, "changePercent": 0.68, "volume": 54669886, "avgVolume": "43.61M", "pe": 36.32, "forwardPe": 31.31, "peg": 2.57, "ps": 9.77, "pb": 41.35, "dividendYield": 0.35, "payoutRatio": 13.66, "eps": 8.27, "epsYoyTtm": 28.91, "salesYoyTtm": 12.76, "roe": 141.47, "profitMargin": 27.15, "insiderOwn": 0.12, "instOwn": 66.02, "shortFloat": 0.92, "targetPrice": 312.56, "recommendation": 1.92, "sma200": 15.86, "rsi": 75.66, "beta": 1.07, "perfYear": 41.99, "earningsDate": "Apr 30 AMC", "indexMembership": "DJIA, NDX, S&P 500", "url": "https://finviz.com/quote.ashx?t=AAPL" } ```
Edge case - SPY (ETF, fundamentals legitimately null) ```json { "ticker": "SPY", "company": "SPDR S&P 500 ETF Trust", "sector": "Financial", "industry": "Exchange Traded Fund", "country": "USA", "exchange": "NYSE", "price": 739.17, "changePercent": -1.20, "volume": 59581107, "pe": null, "ps": null, "dividendYield": 1.00, "eps": null, "insiderOwn": null, "instOwn": null, "targetPrice": null, "sma200": 9.33, "rsi": 67.93, "beta": 1.01, "perfYear": 25.19, "indexMembership": "S&P 500 Index", "ipoDate": "Jan 29, 1993", "url": "https://finviz.com/quote.ashx?t=SPY" } ```
Sparse - HCWB (small-cap top gainer, many fundamentals undefined) ```json { "ticker": "HCWB", "company": "HCW Biologics Inc", "sector": "Healthcare", "industry": "Biotechnology", "country": "USA", "exchange": "NASD", "marketCap": "8.22M", "marketCapValue": 8220000, "price": 1.22, "changePercent": 262.02, "volume": 389109584, "relativeVolume": 41.19, "pe": null, "forwardPe": null, "peg": null, "ps": 1.25, "eps": -9.46, "profitMargin": -274.84, "roe": -27725.80, "insiderOwn": 24.24, "shortFloat": 11.19, "targetPrice": 2.00, "recommendation": 1.00, "rsi": 82.62, "perfWeek": 271.16, "perfYear": -85.12, "earningsDate": "May 14 AMC", "url": "https://finviz.com/quote.ashx?t=HCWB" } ```
*** ### ✨ Why choose this Actor | | Capability | |---|---| | 🧠 | **Single unified schema.** Same 85 columns whether you screen one ticker or the entire 11K universe. No special cases per screen. | | 🛰️ | **Apify residential proxy by default.** Set up automatically inside the actor. Cleaner runs and rotates around rate limits. | | 🚦 | **33 signal presets ready to use.** Same scans that Finviz Elite users pay for, callable by enum value in one input field. | | 🧮 | **Quote-page enrichment baked in.** 70+ fundamentals beyond what the screener row alone returns, including target price and analyst rating. | | 🔁 | **Robust pagination.** Walks `r=` offsets up to 11,121 with backoff so the actor finishes even on the largest screens. | | 📤 | **Drop-in CSV, JSON, Excel.** Apify dataset exports straight to spreadsheets, databases, or webhooks. | | 💸 | **No subscription, no API key.** Finviz Elite is paid for the export feature. This actor pulls the same public data without that cost. | > 📊 The full Finviz universe is **11,138 stocks** as of the last run, refreshed nightly upstream. *** ### 📈 How it compares to alternatives | Approach | Cost | Coverage | Refresh | Filters | Setup | |---|---|---|---|---|---| | **⭐ Finviz Stock Screener Scraper** *(this Actor)* | Apify usage only | 11,138 US tickers | Live | 33 signals + 9 dropdowns + raw | One-click run | | Official paid screeners | $25-100+ / month | Varies, usually deep | Live | Strong | Account, login, billing | | Free brokerage tools | Free with account | Limited to their universe | Live | Basic | Account, KYC | | Paid market-data APIs | $50-500+ / month | Excellent but raw | Live | None, you build the screen | API key, schema mapping | | Manual CSV scrape | Free, brittle | Whatever you copy-paste | Snapshot | None | Spreadsheet labor | The actor delivers the same screening grid as paid alternatives, with no ongoing subscription. *** ### 🚀 How to use 1. ▶️ **Click Try for free.** It opens the actor on Apify; you can sign up with [Apify](https://console.apify.com/sign-up?fpr=vmoqkp) in seconds, no credit card required. 2. ⚙️ **Pick a signal or filters.** Choose a preset like Top Gainers, or combine sector, market cap, and country dropdowns. Optionally pin specific tickers. 3. 🔢 **Set Max items.** Free runs return up to 10 records; paid runs go up to 1,000,000. 4. 🚀 **Press Start.** The actor handles pagination, proxies, retries, and per-ticker enrichment. 5. 📤 **Export.** Download the dataset as JSON, CSV, Excel, or pull it via the Apify API into your own pipeline. > ⏱️ **Total time:** under 2 minutes from sign-up to first dataset. *** ### 💼 Business use cases
#### 📈 Retail traders and chartists - Build morning watchlists from Top Gainers, Unusual Volume, and Most Active signals - Track 52-week high break-outs across an entire sector overnight - Filter by RSI, SMA50, and chart patterns for technical entries - Spot earnings-before-the-open candidates with one filter #### 🧮 Quantitative researchers - Pull cross-sectional factor data (P/E, ROE, growth) on the full universe - Track insider transactions and institutional ownership over time - Backtest momentum and reversal strategies with the supplied 52-week stats - Build sector-rotation models with the 11-sector breakdown
#### 🏦 Hedge funds and prop desks - Monitor analyst recommendation changes daily for idea generation - Filter for short-squeeze setups (high short float + rising RSI + insider buying) - Track event-driven plays: upgrades, downgrades, earnings dates - Feed cleaned fundamentals straight into Bloomberg-replacement dashboards #### 🤖 Trading bots and signal apps - Power notification apps with new-high or new-low triggers - Build chart-pattern alerting (Wedge, Head and Shoulders, Channel, etc.) - Schedule overnight pulls into a database for premarket screens - Drive paper-trading and backtest pipelines with fresh fundamental cuts
*** ### 🌟 Beyond business use cases Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.
#### 🎓 Research and academia - Empirical datasets for papers, thesis work, and coursework - Longitudinal studies tracking changes across snapshots - Reproducible research with cited, versioned data pulls - Classroom exercises on data analysis and ethical scraping #### 🎨 Personal and creative - Side projects, portfolio demos, and indie app launches - Data visualizations, dashboards, and infographics - Content research for bloggers, YouTubers, and podcasters - Hobbyist collections and personal trackers
#### 🤝 Non-profit and civic - Transparency reporting and accountability projects - Advocacy campaigns backed by public-interest data - Community-run databases for local issues - Investigative journalism on public records #### 🧪 Experimentation - Prototype AI and machine-learning pipelines with real data - Validate product-market hypotheses before engineering spend - Train small domain-specific models on niche corpora - Test dashboard concepts with live input
*** ### 🔌 Automating Finviz Stock Screener Scraper Run the actor from any script or backend. Pull the dataset on a schedule, route alerts to Slack, push to BigQuery, or chain it into a downstream model. - 🟦 [**Node.js / TypeScript client**](https://docs.apify.com/api/client/js) for typed Apify SDK access - 🐍 [**Python client**](https://docs.apify.com/api/client/python) for notebooks and data science work - 📚 [**Apify API docs**](https://docs.apify.com/api/v2) for raw REST integration Use Apify Schedules to run the screener every market open, every hour, or every Sunday night. Combine with webhooks to push fresh signals into your inbox, your Slack channel, or your trading platform. *** ### ❓ Frequently Asked Questions
🛒 Can I use the data commercially? Yes. The actor pulls publicly accessible information from Finviz. You are responsible for complying with Finviz's terms of service and any redistribution rules in your jurisdiction.
💳 Do I need a paid Apify plan? No. Free runs return up to 10 records, which is enough to test the schema or look at a handful of tickers. Paid plans go up to 1,000,000 items per run for full-universe sweeps.
🛟 What happens if a run fails? The actor retries each HTTP call up to four times with exponential back-off. If a page still fails, that ticker is skipped with a warning in the log and the rest of the run continues. You only pay for usage actually consumed.
⚖️ Is this legal? The actor accesses only publicly visible pages on Finviz, without bypassing logins or paywalls. Use the data responsibly and consult your legal counsel for redistribution.
🔁 How fresh is the data? Live. Each run hits Finviz in real time, so the figures reflect whatever the screener shows at that moment. Daily change figures update during US market hours.
🔢 How many stocks does Finviz cover? 11,138 US-listed instruments at last check, including common stocks, ADRs, and ETFs across NASDAQ, NYSE, AMEX, and CBOE.
📦 Can I get only the screener row without enrichment? Yes. Set `enrich` to false. You get the 10 base columns from the screener (ticker, company, sector, industry, country, market cap, P/E, price, change, volume) without an extra HTTP request per ticker. Much faster for whole-universe sweeps.
🎯 Can I screen for chart patterns? Yes. The `signal` field exposes Finviz's 16 chart-pattern scans: Horizontal S/R, TL Support, TL Resistance, Wedge, Channel Up/Down, Double Top/Bottom, Head and Shoulders, and more.
🧪 Can I write custom filter expressions? Yes. The `customFilters` field accepts a comma-separated raw Finviz filter expression (for example `fa_pe_low20,ta_sma200_pa`). Combined with the dropdown selections via logical AND.
🌐 Does it work for international tickers? Finviz indexes US-listed instruments only. ADRs of foreign companies (BABA, TSM, NVO) are included, but native foreign listings (e.g. LSE-only or Tokyo-only) are not.
⏱️ How long does a full-universe scrape take? A 1,000-ticker screen with enrichment runs in roughly 5-7 minutes. A 10,000-ticker sweep takes about an hour. Without enrichment, those drop to seconds and a few minutes respectively.
📤 How do I export to CSV or Excel? Once the run finishes, the dataset page offers download buttons for CSV, Excel, JSON, JSON Lines, RSS, and HTML. You can also fetch the dataset programmatically via the Apify API.
*** ### 🔌 Integrate with any app - [**Zapier**](https://zapier.com/apps/apify/integrations) - trigger an Apify run from any Zapier event and route the dataset onward - [**Make**](https://www.make.com/en/integrations/apify) - drag-and-drop scenarios that mix Apify with Slack, Notion, Sheets, and more - [**Slack**](https://docs.apify.com/platform/integrations/slack) - push run alerts and dataset summaries straight to a channel - [**Google Sheets**](https://docs.apify.com/platform/integrations/google-sheets) - sync each run's dataset into a live spreadsheet - [**Airbyte**](https://docs.airbyte.com/integrations/sources/apify-dataset) - stream Apify datasets into Snowflake, BigQuery, Redshift, or Postgres - [**Webhooks**](https://docs.apify.com/platform/integrations/webhooks) - call any HTTP endpoint when a run finishes *** ### 🔗 Recommended Actors - [**📊 FRED Economic Data Scraper**](https://apify.com/parseforge/fred-scraper) - pull macro indicators from the St Louis Fed FRED database; perfect partner for top-down macro context - [**🏛️ SEC Form D Scraper**](https://apify.com/parseforge/sec-form-d-scraper) - track private placements and Regulation D filings to spot pre-IPO activity - [**🕵️ FINRA BrokerCheck Scraper**](https://apify.com/parseforge/finra-brokercheck-scraper) - background check brokers and registered investment advisors - [**⚖️ Business Bankruptcy Filings Scraper**](https://apify.com/parseforge/business-bankruptcy-filings-scraper) - distressed equity and credit watchlist source - [**🗳️ FEC Campaign Finance Contributions Scraper**](https://apify.com/parseforge/fec-campaign-finance-contributions-scraper) - track political donations for thematic and event-driven plays > 💡 **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for more scrapers covering markets, public records, and beyond. *** **🆘 Need Help?** [**Open our contact form**](https://tally.so/r/BzdKgA) and we will get back within a business day. *** > ⚠️ **Disclaimer:** This actor scrapes only public Finviz pages for personal, research, and business intelligence use. Always check Finviz's terms of service before redistributing data. Nothing here is investment advice; double-check anything you trade on against the source. # Actor input Schema ## `tickers` (type: `array`): Restrict the screen to a specific list of tickers. Up to ~500 symbols. Leave empty to scan the full 11,000+ universe with the filters below. ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000. ## `signal` (type: `string`): Top gainers, latest insider buys, oversold, earnings tonight, etc. Apply a Finviz built-in scan in one click. ## `exchange` (type: `string`): Stock exchange. ## `index` (type: `string`): Only include constituents of a major index. ## `sector` (type: `string`): GICS-style sector grouping. ## `industry` (type: `string`): Specific industry. Use Stocks only / Stocks only ex-Funds to exclude ETFs. ## `country` (type: `string`): Country of company headquarters. ## `marketCap` (type: `string`): Market capitalization bucket. ## `customFilters` (type: `string`): Advanced: raw Finviz filter expression to append, comma separated, without the leading f= (e.g. fa\_pe\_low20,ta\_sma200\_pa). Combined AND with the dropdowns above. ## `sortBy` (type: `string`): Column used to order results. ## `sortDirection` (type: `string`): Ascending or descending. ## `enrich` (type: `boolean`): For each ticker, also fetch the dedicated Finviz quote page and merge 70+ extra fundamentals, technicals, ownership, and analyst fields. Adds one HTTP request per ticker. ## Actor input object example ```json { "tickers": [ "AAPL", "MSFT", "NVDA", "TSLA", "META" ], "maxItems": 10, "signal": "", "exchange": "", "index": "", "sector": "", "industry": "", "country": "", "marketCap": "", "sortBy": "", "sortDirection": "desc", "enrich": true } ``` # Actor output Schema ## `overview` (type: `string`): Table view with the most-used fields across the dataset. ## `fullData` (type: `string`): Complete dataset with every extracted field. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "tickers": [ "AAPL", "MSFT", "NVDA", "TSLA", "META" ], "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/finviz-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "tickers": [ "AAPL", "MSFT", "NVDA", "TSLA", "META", ], "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("parseforge/finviz-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "tickers": [ "AAPL", "MSFT", "NVDA", "TSLA", "META" ], "maxItems": 10 }' | apify call parseforge/finviz-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/finviz-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Finviz Stock Screener Scraper", "description": "Screen 11,000+ US-listed stocks on Finviz with 30+ signal presets and 9 filter dimensions. Enriches each ticker with 70+ fundamental and technical fields. No API key required.", "version": "0.1", "x-build-id": "VuRScgFPNP0w11eWO" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~finviz-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-finviz-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~finviz-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-finviz-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~finviz-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-finviz-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "tickers": { "title": "Tickers", "type": "array", "description": "Restrict the screen to a specific list of tickers. Up to ~500 symbols. Leave empty to scan the full 11,000+ universe with the filters below.", "items": { "type": "string" } }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000." }, "signal": { "title": "Signal preset", "enum": [ "", "ta_topgainers", "ta_toplosers", "ta_newhigh", "ta_newlow", "ta_mostvolatile", "ta_mostactive", "ta_unusualvolume", "ta_overbought", "ta_oversold", "n_downgrades", "n_upgrades", "n_earningsbefore", "n_earningsafter", "it_latestbuys", "it_latestsales", "n_majornews", "ta_p_horizontal", "ta_p_tlresistance", "ta_p_tlsupport", "ta_p_wedgeup", "ta_p_wedgedown", "ta_p_wedgeresistance", "ta_p_wedgesupport", "ta_p_wedge", "ta_p_channelup", "ta_p_channeldown", "ta_p_channel", "ta_p_doubletop", "ta_p_doublebottom", "ta_p_multipletop", "ta_p_multiplebottom", "ta_p_headandshoulders", "ta_p_headandshouldersinv" ], "type": "string", "description": "Top gainers, latest insider buys, oversold, earnings tonight, etc. Apply a Finviz built-in scan in one click.", "default": "" }, "exchange": { "title": "Exchange", "enum": [ "", "amex", "cboe", "nasd", "nyse" ], "type": "string", "description": "Stock exchange.", "default": "" }, "index": { "title": "Index membership", "enum": [ "", "sp500", "ndx", "dji", "rut" ], "type": "string", "description": "Only include constituents of a major index.", "default": "" }, "sector": { "title": "Sector", "enum": [ "", "basicmaterials", "communicationservices", "consumercyclical", "consumerdefensive", "energy", "financial", "healthcare", "industrials", "realestate", "technology", "utilities" ], "type": "string", "description": "GICS-style sector grouping.", "default": "" }, "industry": { "title": "Industry", "enum": [ "", "stocksonly", "stocksonlyspac", "exchangetradedfund", "advertisingagencies", "aerospacedefense", "agriculturalinputs", "airlines", "airportsairservices", "aluminum", "apparelmanufacturing", "apparelretail", "assetmanagement", "automanufacturers", "autoparts", "autotruckdealerships", "banksdiversified", "banksregional", "beveragesbrewers", "beveragesnonalcoholic", "beverageswineriesdistilleries", "biotechnology", "broadcasting", "buildingmaterials", "buildingproductsequipment", "businessequipmentsupplies", "capitalmarkets", "chemicals", "closedendfunddebt", "closedendfundequity", "closedendfundforeign", "cokingcoal", "communicationequipment", "computerhardware", "confectioners", "conglomerates", "consultingservices", "consumerelectronics", "copper", "creditservices", "departmentstores", "diagnosticsresearch", "discountstores", "drugmanufacturersgeneral", "drugmanufacturersspecialtygeneric", "educationtrainingservices", "electricalequipmentparts", "electroniccomponents", "electronicgamingmultimedia", "electronicscomputerdistribution", "engineeringconstruction", "entertainment", "farmheavyconstructionmachinery", "farmproducts", "financialconglomerates", "financialdatastockexchanges", "fooddistribution", "footwearaccessories", "furnishingsfixturesappliances", "gambling", "gold", "grocerystores", "healthcareplans", "healthinformationservices", "homeimprovementretail", "householdpersonalproducts", "industrialdistribution", "informationtechnologyservices", "infrastructureoperations", "insurancebrokers", "insurancediversified", "insurancelife", "insurancepropertycasualty", "insurancereinsurance", "insurancespecialty", "integratedfreightlogistics", "internetcontentinformation", "internetretail", "leisure", "lodging", "lumberwoodproduction", "luxurygoods", "marineshipping", "medicalcarefacilities", "medicaldevices", "medicaldistribution", "medicalinstrumentssupplies", "metalfabrication", "mortgagefinance", "oilgasdrilling", "oilgasep", "oilgasequipmentservices", "oilgasintegrated", "oilgasmidstream", "oilgasrefiningmarketing", "otherindustrialmetalsmining", "otherpreciousmetalsmining", "packagedfoods", "packagingcontainers", "paperpaperproducts", "personalservices", "pharmaceuticalretailers", "pollutiontreatmentcontrols", "publishing", "railroads", "realestatedevelopment", "realestatediversified", "realestateservices", "recreationalvehicles", "reitdiversified", "reithealthcarefacilities", "reithotelmotel", "reitindustrial", "reitmortgage", "reitoffice", "reitresidential", "reitretail", "reitspecialty", "rentalleasingservices", "residentialconstruction", "resortscasinos", "restaurants", "scientifictechnicalinstruments", "securityprotectionservices", "semiconductorequipmentmaterials", "semiconductors", "shellcompanies", "silver", "softwareapplication", "softwareinfrastructure", "solar", "specialtybusinessservices", "specialtychemicals", "specialtyindustrialmachinery", "specialtyretail", "staffingemploymentservices", "steel", "telecomservices", "textilemanufacturing", "thermalcoal", "tobacco", "toolsaccessories", "travelservices", "trucking", "uranium", "utilitiesdiversified", "utilitiesindependentpowerproducers", "utilitiesregulatedelectric", "utilitiesregulatedgas", "utilitiesregulatedwater", "utilitiesrenewable", "wastemanagement" ], "type": "string", "description": "Specific industry. Use Stocks only / Stocks only ex-Funds to exclude ETFs.", "default": "" }, "country": { "title": "Country", "enum": [ "", "usa", "notusa", "asia", "europe", "latinamerica", "bric", "argentina", "australia", "bahamas", "belgium", "benelux", "bermuda", "brazil", "canada", "caymanislands", "chile", "china", "chinahongkong", "colombia", "cyprus", "denmark", "finland", "france", "germany", "greece", "hongkong", "hungary", "iceland", "india", "indonesia", "ireland", "israel", "italy", "japan", "jordan", "kazakhstan", "luxembourg", "malaysia", "malta", "mexico", "monaco", "netherlands", "newzealand", "norway", "panama", "peru", "philippines", "portugal", "russia", "singapore", "southafrica", "southkorea", "spain", "sweden", "switzerland", "taiwan", "thailand", "turkey", "unitedarabemirates", "unitedkingdom", "uruguay", "vietnam" ], "type": "string", "description": "Country of company headquarters.", "default": "" }, "marketCap": { "title": "Market Cap", "enum": [ "", "mega", "large", "mid", "small", "micro", "nano", "largeover", "midover", "smallover", "microover", "largeunder", "midunder", "smallunder", "microunder" ], "type": "string", "description": "Market capitalization bucket.", "default": "" }, "customFilters": { "title": "Custom raw filters", "type": "string", "description": "Advanced: raw Finviz filter expression to append, comma separated, without the leading f= (e.g. fa_pe_low20,ta_sma200_pa). Combined AND with the dropdowns above." }, "sortBy": { "title": "Sort by", "enum": [ "", "ticker", "company", "sector", "industry", "country", "marketcap", "pe", "forwardpe", "peg", "ps", "pb", "pc", "dividendyield", "eps_yoy_ttm", "sales_yoy_ttm", "roa", "roe", "roi", "grossmargin", "opermargin", "profitmargin", "insiderown", "insidertransactions", "instown", "insttrans", "shortfloat", "beta", "volatility", "rsi", "perf1w", "perf4w", "perf13w", "perf26w", "perfytd", "perf52w", "price", "change", "volume", "averagevolume", "relativevolume" ], "type": "string", "description": "Column used to order results.", "default": "" }, "sortDirection": { "title": "Sort direction", "enum": [ "asc", "desc" ], "type": "string", "description": "Ascending or descending.", "default": "desc" }, "enrich": { "title": "Enrich with full quote data", "type": "boolean", "description": "For each ticker, also fetch the dedicated Finviz quote page and merge 70+ extra fundamentals, technicals, ownership, and analyst fields. Adds one HTTP request per ticker.", "default": true } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```