📈 Multpl Scraper - S&P 500 PE Ratio & Economic Data

🚀 Export S&P 500 P/E ratios, Shiller CAPE, dividend yield, inflation (CPI), earnings and more to CSV, Excel, JSON or XML in seconds.

🕒 Last updated: 2026-05-22 · 📊 9 fields per record · 1,800+ monthly data points per metric · 7 metrics available

Multpl.com is the go-to public source for long-run S&P 500 and U.S. macroeconomic time series. This actor extracts any of the 7 supported metrics - P/E ratio, Shiller CAPE, dividend yield, earnings per share, annual returns, CPI inflation, and S&P 500 price - as clean structured records. Data goes back to the late 1800s for most metrics.

All data is fetched live from Multpl.com HTML tables. No cache, no stale data.

Coverage: 7 metrics covering S&P 500 valuation, income, and U.S. macroeconomics. Monthly data back to 1871 (depending on metric). Annual aggregates also available.

Audience	Use Cases
Quant analysts	Backtest valuation-based strategies using P/E or CAPE
Financial researchers	Study long-run market cycles and inflation regimes
Data journalists	Chart historical S&P 500 valuations with context
Portfolio managers	Monitor current P/E and dividend yield vs. historical averages
Economists	Track CPI inflation and real S&P 500 earnings over decades
Developers	Feed financial dashboards and alerting systems

📋 What the Multpl Scraper does

• Fetches live HTML tables from Multpl.com - no stale cached data
• Supports 7 metrics: P/E Ratio, Shiller P/E (CAPE), Dividend Yield, Earnings Per Share, Annual Returns, CPI Inflation, S&P 500 Price
• Returns monthly or annual granularity per metric
• Parses and cleans numeric values (removes % and $ symbols)
• Normalizes dates to ISO 8601 format (YYYY-MM-DD)
• Limits free users to 10 items automatically - paid users get up to 1,000,000
• Outputs clean records ready for CSV/Excel/JSON/XML download

💡 Why it matters: Multpl.com is one of the only free public sources for S&P 500 P/E ratio history going back to 1871. This actor turns those HTML tables into structured, downloadable datasets with a single click.

🎬 Full Demo

🚧 Coming soon

⚙️ Input

Field	Type	Default	Description
maxItems	integer	10	Maximum number of records to return
metric	select	s-p-500-pe-ratio	Which metric to fetch (7 options)
period	select	monthly	Monthly or annual granularity

Example - Fetch last 100 monthly P/E ratios:

{
  "metric": "s-p-500-pe-ratio",
  "period": "monthly",
  "maxItems": 100
}

Example - Fetch all annual Shiller CAPE history:

{
  "metric": "shiller-pe",
  "period": "annual",
  "maxItems": 1000000
}

⚠️ Good to Know: Free users are automatically limited to 10 records. To unlock the full historical dataset (1,800+ monthly records per metric), create a paid account.

📊 Output

Field	Type	Description
📊 metric	string	Metric slug (e.g. s-p-500-pe-ratio)
📋 metricName	string	Human-readable metric name
📅 date	string	ISO 8601 date (YYYY-MM-DD)
💹 value	number	Numeric value (cleaned)
🔢 valueRaw	string	Original string value as scraped
🗓️ period	string	monthly or annual
🔗 url	string	Source URL fetched
🕒 scrapedAt	string	ISO 8601 scrape timestamp
❌ error	string	Error message if failed, otherwise null

Sample records (real output from cloud run):

[
  {
    "metric": "s-p-500-pe-ratio",
    "metricName": "S&P 500 P/E Ratio",
    "date": "2026-05-21",
    "value": 32.06,
    "valueRaw": "32.06",
    "period": "monthly",
    "url": "https://www.multpl.com/s-p-500-pe-ratio/table/by-month",
    "scrapedAt": "2026-05-22T00:29:26.952Z",
    "error": null
  },
  {
    "metric": "s-p-500-pe-ratio",
    "metricName": "S&P 500 P/E Ratio",
    "date": "2026-05-01",
    "value": 31.42,
    "valueRaw": "31.42",
    "period": "monthly",
    "url": "https://www.multpl.com/s-p-500-pe-ratio/table/by-month",
    "scrapedAt": "2026-05-22T00:29:26.952Z",
    "error": null
  },
  {
    "metric": "s-p-500-pe-ratio",
    "metricName": "S&P 500 P/E Ratio",
    "date": "2026-04-01",
    "value": 29.72,
    "valueRaw": "29.72",
    "period": "monthly",
    "url": "https://www.multpl.com/s-p-500-pe-ratio/table/by-month",
    "scrapedAt": "2026-05-22T00:29:26.952Z",
    "error": null
  }
]

✨ Why choose this Actor

Feature	Details
🕒 Live data	Fetches directly from Multpl.com on every run - no stale cache
📅 Deep history	P/E data back to January 1871 (155 years)
📊 7 metrics	P/E, CAPE, Dividend Yield, Earnings, Returns, CPI, S&P 500 Price
🗓️ Dual granularity	Monthly or annual aggregates per metric
🔢 Clean output	ISO dates, numeric values, raw strings all included
💾 Multi-format	Export as CSV, Excel, JSON, or XML
🌐 No login required	All data is publicly accessible

📈 How it compares to alternatives

Feature	Multpl Scraper	Manual copy-paste	Premium data vendors
Automation	Yes - runs on schedule	No	Yes
Free to start	Yes (10 items free)	Yes	No
Export formats	CSV, Excel, JSON, XML	Manual	Varies
Full history (155 years)	Yes	Yes (tedious)	Yes
7 metrics in one actor	Yes	No	Varies
API integration	Yes (Apify API)	No	Yes

🚀 How to use

1. Create a free Apify account w/ $5 credit
2. Open the Multpl Scraper actor page
3. Select your metric (e.g. S&P 500 P/E Ratio)
4. Choose monthly or annual period
5. Set maxItems (10 for preview, up to 1,000,000 for full history)
6. Click Start and wait a few seconds
7. Download your dataset as CSV, Excel, JSON, or XML

💼 Business use cases

Quantitative Finance

Build valuation-based trading signals. The P/E ratio and Shiller CAPE are widely used to identify over- and under-valued market conditions. Pull monthly data since 1871 to backtest mean-reversion strategies or build macro regime classifiers.

Research and Academia

Economists and financial researchers use long-run S&P 500 data to study the relationship between equity valuations, inflation (CPI), earnings growth, and market returns. This actor delivers all of those series in a single consistent format.

Financial Journalism and Charting

Data journalists and analysts regularly need historical context for market commentary. Grab the full P/E ratio or dividend yield history to chart where today's market stands vs. historical averages, bubbles, and troughs.

Portfolio Monitoring and Alerting

Connect this actor to Make or Zapier to run on a monthly schedule. Compare the latest P/E ratio against your threshold and trigger a Slack or email alert when valuations breach a level you care about.

🔌 Automating Multpl Scraper

This actor integrates with any automation platform via the Apify API:

• Make (Integromat) - Schedule monthly runs and pipe data to Google Sheets
• Zapier - Trigger downstream workflows when new data is available
• Slack - Alert your team when the P/E ratio crosses a threshold
• Google Sheets - Auto-append the latest monthly data to a spreadsheet
• n8n - Build no-code financial data pipelines
• REST API - Call the actor programmatically from any app

🌟 Beyond business use cases

Personal Finance Education

Teachers and students can use this actor to visualize how S&P 500 valuations have evolved across different economic eras - the dot-com bubble, the 2008 financial crisis, COVID crash, and beyond.

Open Source Research

Academic researchers building open-source financial models can use this actor to generate reproducible datasets from a publicly accessible, well-maintained source.

Non-profit Financial Literacy

Organizations teaching financial literacy can use historical P/E and dividend yield data to illustrate compounding, market cycles, and long-term investing principles in data-driven curriculum.

Experimentation and Prototyping

Developers building financial apps, charting tools, or data science notebooks can use this actor to get a clean, structured time series in under 30 seconds - without writing any scraping code.

🤖 Ask an AI assistant about this scraper

You can ask any AI assistant (Claude, ChatGPT, Gemini):

• "What fields does the Multpl Scraper return?"
• "How do I export S&P 500 P/E ratio history to Excel using Apify?"
• "What is the Shiller P/E (CAPE) ratio and how do I get the full history?"
• "How do I schedule monthly P/E ratio extraction with Make?"

❓ Frequently Asked Questions

🤔 What is Multpl.com?

Multpl.com is a public website that aggregates S&P 500 historical data: P/E ratio, Shiller CAPE, dividend yield, earnings per share, price history, CPI inflation, and more. It is widely used by investors and researchers.

📅 How far back does the data go?

Most metrics go back to the late 1800s. The S&P 500 P/E ratio has monthly data from January 1871 - that is 155 years of history. Annual data for some metrics goes back even further.

🗓️ Can I get both monthly and annual data?

Yes. Use the period input to select monthly (default) or annual. Both return the same fields.

📊 Which metrics are available?

Seven metrics: S&P 500 P/E Ratio, Shiller P/E (CAPE), Dividend Yield, Earnings Per Share, Annual Returns, Inflation Rate (CPI), and S&P 500 Price.

🔢 What format are numeric values in?

The value field is a JavaScript number (e.g. 32.06). The valueRaw field contains the original string from the page (e.g. "32.06"). Percent signs and dollar signs are stripped.

🕒 How current is the data?

The actor fetches live data from Multpl.com on every run. The most recent data point is typically the current month (marked with a dagger symbol on the site indicating it is preliminary).

🔄 Can I schedule this to run automatically?

Yes. Use Apify's built-in scheduler to run monthly or weekly. Combine with Make or Zapier to pipe new data into Google Sheets or a database automatically.

💾 What export formats are supported?

CSV, Excel (XLSX), JSON, and XML. All available from the dataset page after the run completes.

🆓 What can free users access?

Free users get the 10 most recent data points per run. To access the full historical dataset (1,800+ records for monthly P/E), upgrade to a paid plan.

🔑 Do I need a Multpl.com account or API key?

No. All data on Multpl.com is publicly accessible. This actor requires no login and no API key - just your Apify account.

⚡ How fast is the actor?

A typical run completes in under 5 seconds. The site is a simple static HTML page - no JavaScript rendering required.

🌐 Does this work from any country?

Yes. Multpl.com is globally accessible and the actor uses browser-like request headers for reliability.

🔌 Integrate with any app

Connect your Multpl dataset to: Google Sheets - Excel - Power BI - Tableau - Looker - Notion - Airtable - Slack - Discord - Make - Zapier - n8n - Pipedream - Bubble - Retool - REST API - Python (pandas) - R - Julia - MATLAB

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💡 Pro Tip: browse the complete ParseForge collection for 80+ public data scrapers covering finance, government, real estate, jobs, and more.

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Disclaimer: This actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Multpl.com. All data is fetched from publicly accessible pages. Use responsibly and in accordance with Multpl.com's terms of service.