📈 Macrotrends Scraper

🚀 Export decades of financial and macro data in seconds. Scrape stock revenue, earnings, PE ratios, GDP, inflation, unemployment, and 1,000+ other historical time-series from Macrotrends - no API key required, fully automated.

The Macrotrends Scraper extracts historical time-series data directly from Macrotrends chart pages. It supports both stock financial charts (revenue, EPS, PE ratio, free cash flow, and more) and global macro charts (GDP, inflation, unemployment, interest rates). Data is parsed from the embedded JavaScript data layer - no browser required, results in seconds.

The dataset covers S&P 500 companies with quarterly and annual data going back to the 1970s for stocks, and annual macro data from the 1960s onward for countries worldwide.

Coverage

• Stock charts: Revenue, Net Income, EPS, PE Ratio, Free Cash Flow, Gross Profit, EBITDA, and 100+ other metrics for any ticker on Macrotrends
• Macro charts: GDP, Inflation (CPI), Unemployment, Interest Rates, National Debt, and more for 200+ countries
• History: Up to 50+ years of quarterly or annual data per series
• 7 output fields per record including date, value, metric name, ticker, source URL, and timestamp

Target Audience / Use Cases

Who	How they use it
Financial analysts	Build revenue and earnings models for public companies
Economists	Track macro trends across countries and time periods
Quant researchers	Backtest strategies using historical PE ratios and earnings data
Data journalists	Verify and visualize long-run economic narratives
Business intelligence teams	Enrich dashboards with external benchmarks
Academic researchers	Collect ground-truth financial data for studies

📋 What the Macrotrends Scraper does

• Scrapes any Macrotrends stock chart URL (e.g. Apple Revenue, Tesla PE Ratio, Microsoft EPS)
• Scrapes any Macrotrends global-metrics URL (e.g. US GDP, Germany Inflation, Japan Unemployment)
• Returns one record per time period with date, value, metric name, and ticker
• Automatically detects URL type and selects the correct data extraction path
• Limits output to maxItems for cost control; free users get up to 10 records as a preview

💡 Why it matters: Macrotrends is one of the richest free sources of historical financial and macro data on the internet. This scraper makes that data programmatically accessible for any workflow - financial modeling, macro research, dashboard enrichment, or academic study.

📊 Data fields

Each record includes: date, metric, results, scrapedAt, ticker, url, value. These field names come straight from the actor's dataset schema, so what you see here is what lands in your dataset.

🚀 How to use

1. Create a free Apify account with $5 in free credit
2. Open this Actor in the Apify Console
3. Paste any Macrotrends chart URL into the startUrl field
4. Set maxItems to control how many records you want (10 for preview, or higher for full history)
5. Click Start and wait a few seconds
6. Download your dataset as CSV, Excel, JSON, or XML

🔗 Recommended Actors

Actor	Description
HUD User Data Scraper	Scrape US housing data from HUD including fair market rents and income limits
FINRA BrokerCheck Scraper	Extract financial advisor and broker records from FINRA
USGS Earthquake Scraper	Real-time and historical seismic data from USGS
EPA AQS Air Quality Scraper	Air quality monitoring data from the EPA AQS database
World Bank Data Scraper	16,000+ World Bank economic indicators by country

💡 Pro Tip: browse the complete ParseForge collection to find scrapers for financial data, government databases, job boards, and more.

Disclaimer: This actor is not affiliated with, endorsed by, or sponsored by Macrotrends. It accesses only publicly available data. Use in accordance with Macrotrends' terms of service and applicable laws. Data accuracy depends on the source; always verify critical figures before use in financial decisions.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

For faster answers, join our Discord. It's the best place to get support and suggest new actors.