We extract stock screener results, fundamental metrics, technical indicators, and insider trading logs from Finviz. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Stock Screener objects from finviz.com. All fields typed and schema-versioned.
"ticker": "AAPL", "company": "Apple Inc.", "sector": "Technology", "industry": "Consumer Electronics", "market_cap": 2840000000000, "pe_ratio": 29.4, "price": 185.92, "volume": 45892100
| # | ticker | company | sector | industry | country | market_cap |
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Complete list of extractable fields for Fundamentals objects from finviz.com. All fields typed and schema-versioned.
"ticker": "AAPL", "eps_ttm": 6.42, "eps_next_y": 7.15, "roe": 145.2, "debt_to_eq": 1.45, "gross_margin": 43.1, "profit_margin": 25.3
| # | ticker | eps_ttm | eps_next_y | roe | roa | roi |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Technicals objects from finviz.com. All fields typed and schema-versioned.
"ticker": "AAPL", "sma_20": 182.45, "sma_50": 178.9, "sma_200": 165.3, "rsi_14": 58.4, "volatility_w": 1.2, "beta": 1.15
| # | ticker | sma_20 | sma_50 | sma_200 | rsi_14 | volatility_w |
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Complete list of extractable fields for Insider Trading objects from finviz.com. All fields typed and schema-versioned.
"ticker": "NVDA", "owner": "Huang Jen Hsun", "relationship": "President and CEO", "date": "2026-05-10", "transaction": "Sale", "cost": 895.4, "shares": 120000, "value": 107448000
| # | ticker | owner | relationship | date | transaction | cost |
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Complete list of extractable fields for Sector Performance objects from finviz.com. All fields typed and schema-versioned.
"name": "Technology", "market_cap": 14500000000000, "pe_ratio": 32.1, "fwd_pe": 28.5, "change_1d": 1.24, "change_1w": 3.45, "change_1m": -0.85
| # | name | market_cap | dividend_yield | pe_ratio | fwd_pe | peg |
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Our Finviz scraper handles complex table pagination, dynamic screener URL parameters, and rate limit evasion to deliver structured financial data without interruption.
Extract all 70+ filters across descriptive, fundamental, and technical criteria. Capture thousands of matching tickers per run.
Track executive buys and sells. Capture transaction type, share volume, execution price, and direct SEC Form 4 filing links.
Pull moving averages, RSI, ATR, volatility metrics, and support/resistance levels directly from ticker pages.
Extract P/E, PEG, EPS growth, margins, return on equity, and debt ratios for over 8,000 listed equities.
Scrape the aggregated news headlines and analyst rating changes linked to specific tickers on their detail pages.
Extract hierarchical performance data across sectors, industries, and individual components for heatmap recreation.
Configure daily, weekly, or custom interval pipelines to capture end-of-day data exactly when the market closes.
Finviz aggressively blocks high-frequency IP requests. Our infrastructure rotates residential proxies to maintain continuous access.
Monitor short float percentages and short ratios across the entire market to identify potential squeeze candidates.
Brief in. Clean data out.
Provide your exact Finviz screener URLs or target data sets. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management tailored for finviz.com.
Schema validation, null-rate checks, and data type normalisation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Financial data sites deploy strict rate limits and complex DOM structures. Here is how we maintain reliable extraction.
Finviz monitors request velocity and flags data center IPs. Our crawlers use US-based residential ISP proxies with realistic request timing to avoid IP bans and CAPTCHA walls.
Screener results span hundreds of pages. We implement deterministic state tracking to ensure no rows are skipped or duplicated during deep pagination runs.
Finviz stores screener state in complex URL query parameters. We map these parameters programmatically, allowing you to pass human-readable filter criteria to our API.
Financial values appear as strings with suffixes ('1.2B', '4.5M') or percentages. Our pipeline parses and casts these into normalised numeric types suitable for immediate database ingestion.
Every run emits structured logs to our observability stack. We alert on schema drift or coverage drops, ensuring your quantitative models never ingest malformed data.
Hedge funds ingest technical and fundamental indicators to feed multi-factor alpha generation models.
Analysts monitor executive buying patterns to signal conviction and correlate with future price action.
Trading desks aggregate analyst upgrades, downgrades, and news sentiment linked to specific tickers.
Corporate finance teams track peer group valuations, margins, and capital structures across specific industries.
Developers archive daily screener snapshots to build historical datasets for testing trading strategies.
Portfolio managers monitor short interest and volatility metrics to identify overexposed sector allocations.
"Finviz aggregates the most dense technical and fundamental market overview available, but extracting it programmatically requires dedicated infrastructure."
Most teams underestimate the investment required: reliable Finviz scraping requires residential proxies, complex pagination handling, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your quants can focus on alpha generation, not infrastructure maintenance.
Everything supported by our finviz.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright manages interaction flows. Combined via scrapy-playwright middleware for maximum reliability.
We maintain pools of residential ISP proxies. Rotation happens per-request to prevent IP blacklisting and avoid CAPTCHA triggers.
Pipelines run on ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About finviz.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available, non-authenticated market data is generally permissible. DataFlirt targets only public screener results, news feeds, and technical indicators. We do not circumvent authentication walls for Finviz Elite features. Clients should review Finviz Terms of Service and consult legal counsel for specific use cases.
We use US-based residential ISP proxies and enforce polite request delays. Our infrastructure automatically detects rate limit responses and rotates IPs seamlessly to ensure continuous extraction.
Finviz delays public data by 15 minutes. We can configure pipelines to run intraday, but the extracted data will reflect this standard delay. For true real-time feeds, you need direct exchange connections.
Yes. Finviz displays market cap as '2.5B' and percentages as '12.4%'. Our pipeline normalises these fields into raw float and integer types before delivery.
Yes. Every pipeline run produces timestamped snapshots. We can maintain a time-series table of screener results from the date your pipeline is commissioned.
Our smallest packages start at daily end-of-day extracts for specific screener configurations. For full market scans or custom schema requirements, we price based on volume and frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily insider trading dump or continuous stock screener extraction across thousands of tickers, we scope, build, and operate the pipeline. Tell us what you need.
