Fundamental Data API: How to Extract Stock, ETF, Index, Mutual Fund, and Crypto Data (Step-by-Step…

Fundamental Data API: How to Extract Stock, ETF, Index, Mutual Fund, and Crypto Data (Step-by-Step Guide)

If you’ve ever tried to build a serious financial product, screener, dashboard, or data pipeline, you already know the uncomfortable truth:

Getting financial data is easy.
Getting reliable fundamental data is not.

Most projects start the same way:

• “Let’s pull data from Yahoo Finance.”
• “This API is free, good enough for now.”
• “We’ll fix it later.”

Then reality hits:

• Endpoints break without warning
• Scrapers get blocked
• ETFs have no holdings
• Indices have no historical constituents
• Crypto has prices but zero context

At that point, the problem is no longer technical.
It’s architectural.

That’s why choosing the right Fundamental Data API matters.

What Is a Fundamental Data API?

A Fundamental Data API provides structured, long-term financial information about assets, not just prices.

Unlike market data APIs (OHLC, ticks, volume), fundamental data answers deeper questions:

• What does this company actually do?
• How does it make money?
• What is inside this ETF?
• Which companies were in this index in the past?
• What is the real structure behind a crypto project?

What Counts as Fundamental Data?

Stocks

• Company profile (sector, industry, country)
• Financial statements (Income, Balance Sheet, Cash Flow)
• Valuation ratios (P/E, margins, ROE, ROA)
• Dividends and splits
• Market capitalization and key metrics

ETFs

• ETF metadata (issuer, category, AUM)
• Holdings and weights
• Sector and geographic exposure

Mutual Funds

• Fund profile and strategy
• Assets under management
• Financial history

Indices

• Constituents
• Weights
• Historical changes (critical for backtesting)

Crypto

• Project metadata
• Supply and market capitalization
• Official links (website, GitHub, whitepaper)
• Ecosystem statistics

What Is Derived Fundamental Data?

Derived data is what you build on top of fundamentals.

Examples:

• Fundamental scoring models
• Company or ETF rankings
• Quality or value factors
• Sector or exposure analysis

Derived data is only as good as the raw fundamental data behind it.
If the base data is inconsistent, your models will be too.

Why Popular Solutions Fail at Fundamental Data

Yahoo Finance (scraping)

• ❌ No official API
• ❌ Frequent HTML changes
• ❌ Blocking and rate limits
• ❌ Not suitable for commercial products

Trading-focused APIs (brokers)

• ❌ Built for order execution
• ❌ Limited or missing fundamentals
• ❌ Poor ETF, index, and global coverage

Alpha Vantage

• ✅ Easy to start
• ❌ Strict rate limits
• ❌ Limited ETF and index depth
• ❌ Difficult to scale for real products

These tools work for experiments, not for systems.

Why Choose EODHD APIs for Fundamental Data

This is an architectural decision, not a feature checklist.

Key Advantages

• Single fundamental endpoint for multiple asset classes
• Global market coverage, not US-only
• Consistent JSON structure, ideal for normalization
• Native crypto fundamentals via a virtual exchange (.CC)
• Designed for data products, ETL, and SaaS

EODHD APIs scale from scripts to full platforms without changing your data model.

Fundamental Data API Endpoint (Core Concept)

GET https://eodhd.com/api/fundamentals/{SYMBOL}?api_token=YOUR_API_KEY&fmt=json

Symbol examples:

• Stock: AAPL.US
• ETF: SPY.US
• Mutual fund: SWPPX.US
• Crypto: BTC-USD.CC

Python Setup (Reusable)

import requests
import os
API_KEY = os.getenv("EODHD_TOKEN")
BASE_URL = "https://eodhd.com/api"
def get_fundamentals(symbol):
url = f"{BASE_URL}/fundamentals/{symbol}"
r = requests.get(url, params={
"api_token": API_KEY,
"fmt": "json"
})
r.raise_for_status()
return r.json()

How to Extract Stock Fundamental Data Using an API

stock = get_fundamentals("AAPL.US")
print(stock["General"]["Name"])
print(stock["Highlights"]["MarketCapitalization"])
print(stock["Valuation"]["TrailingPE"])

Use cases

• Stock screeners
• Valuation models
• Fundamental scoring systems

How to Extract ETF Data Using an API

ETFs require look-through analysis, not just price tracking.

etf = get_fundamentals("SPY.US")
print(etf["General"]["Name"])
print(etf["ETF_Data"]["Holdings"].keys())

Use cases

• Portfolio exposure analysis
• Backtesting without hidden bias
• Wealth and advisory platforms

How to Extract Mutual Fund Data Using an API

fund = get_fundamentals("SWPPX.US")
print(fund["General"]["Name"])

Use cases

• Fund comparison tools
• Automated reporting
• Wealth management dashboards

How to Extract Index Data Using an API

Indices are not just numbers.

Correct index analysis requires:

• Constituents
• Weights
• Historical changes

Using current constituents for past analysis introduces look-ahead bias.

Recommended workflow

1. Pull index constituents (current or historical)
2. Enrich each component with fundamentals
3. Compute derived metrics

This is essential for:

• Quant models
• Factor research
• Long-term backtesting

How to Extract Crypto Fundamental Data Using an API

Crypto fundamentals are project-level, not just price-based.

btc = get_fundamentals("BTC-USD.CC")
print(btc["General"]["Name"])
print(btc["Statistics"]["MarketCapitalization"])
print(btc["Resources"]["Links"]["source_code"])

Use cases

• Crypto research dashboards
• Project comparison tools
• Hybrid equity + crypto platforms

How to Integrate Fundamental Data Into Real Systems

Typical integrations:

• ETL → PostgreSQL, BigQuery
• Automation → n8n, Airflow
• Dashboards → Streamlit, Metabase
• Reporting → Google Sheets, Notion

Recommended architecture

1. Fetch fundamentals
2. Cache by symbol (daily or weekly)
3. Normalize only required fields
4. Compute derived metrics
5. Serve data to applications

Pros and Cons of a Professional Fundamental Data API

Pros

• Stable and structured data
• Multi-asset support
• Scales to production
• Ideal for derived analytics

Cons

• Requires data modeling
• Not a copy-paste shortcut

That’s a feature, not a drawback.

FAQs — Fundamental Data APIs

What is fundamental data?

Economic and structural information about an asset, not its price.

What is derived fundamental data?

Metrics or scores calculated from raw fundamental data.

Can I combine stocks, ETFs, indices, and crypto?

Yes. That’s one of the main strengths of EODHD APIs.

How often should I update fundamental data?

• Stocks: quarterly
• ETFs and funds: monthly
• Crypto: more frequently

Is fundamental data suitable for SaaS products?

Yes, when sourced from an official and stable API.

If you’re looking for a Fundamental Data API that lets you:

• Extract stock, ETF, mutual fund, index, and crypto data
• build reliable derived financial data
• scale from scripts to real products

Then EODHD APIs provide a clean and professional foundation.

Access the EODHD Fundamental Data API with a discount:

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Fundamental Data API: How to Extract Stock, ETF, Index, Mutual Fund, and Crypto Data (Step-by-Step… was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.