EODHD vs FinancialModelingPrep for Fundamentals

EODHD vs FinancialModelingPrep for Fundamentals

Global breadth against fundamentals depth. The comparison turns on coverage, point-in-time records, and the event data both leave out.

What You Are Really Comparing

EOD Historical Data and FinancialModelingPrep are both affordable APIs offering prices and fundamentals, and they lean in different directions. EODHD emphasizes wide global exchange coverage, while FinancialModelingPrep emphasizes deeper, more normalized fundamentals. For fundamentals-driven research, the choice is about geography versus depth and how point-in-time each one is.

A concrete example shows the trade. Suppose you are backtesting a strategy across European and Asian mid-caps. EODHD's wide exchange coverage is exactly the draw, and a US-centric specialist would leave gaps in your universe. Now suppose you are running a US fundamentals screen that depends on deeply normalized statements and reliable point-in-time records. FinancialModelingPrep's depth on US names is the better fit, and EODHD's generalist breadth is not the binding feature. Geography points one way and fundamentals depth points the other, which is the whole decision.

EODHD: Strengths and Trade-offs

EODHD covers more than sixty global exchanges with EOD prices, fundamentals, dividends, and splits at a low flat-rate price. Its strength is international breadth, which is hard to match cheaply, making it well suited to research spanning many markets. For globally diversified, daily-frequency work, that coverage is the draw.

The trade-offs are depth and point-in-time rigor in any single market. A generalist that spans the world is thinner in deeply normalized US fundamentals than a specialist, so the breadth comes at some cost to depth, as we note in the wider context of our FinancialModelingPrep alternatives guide.

FinancialModelingPrep: Strengths and Trade-offs

FinancialModelingPrep provides broad fundamentals, ratios, statements, and screening through a straightforward API, with deeper normalized financials than a pure breadth play. Its strength is fundamentals depth and developer ergonomics at a flat rate, which suits screening and statement-driven strategies. For US-centric fundamental research, it is the more focused tool.

The trade-offs are coverage scope relative to a global generalist and the need to verify how point-in-time the historical records are for your period. Depth in fundamentals is its draw, and point-in-time behavior is the property to check before trusting a backtest.

Head-to-Head

Where Each Wins

EODHD wins when international breadth is the priority and you want one low-cost source spanning many exchanges. FinancialModelingPrep wins when fundamentals depth and screening lead the workflow on mainly US names. Historical size and fundamentals deserve care in either case, as our note on historical market cap data explains.

The deciding factor is usually whether your binding constraint is geographic coverage or fundamentals depth, since each provider optimizes for one of those.

The Layer Both Omit

Both deliver prices and fundamentals, not research structure. Neither ships a point-in-time universe or dated corporate events, so a fundamentals backtest on either can leak restated data or miss financing events unless you add that layer, a discipline covered in our explainer on point-in-time market data.

Alphanume's historical market cap dataset supplies point-in-time size, and the dilution events feed adds dated financing events, layering on top of either fundamentals API.

Which Should You Choose?

Choose EODHD for global breadth and FinancialModelingPrep for fundamentals depth, verifying point-in-time behavior either way. The deeper point is that fundamentals depth and research structure are different things. Whichever you pick, add a point-in-time research layer for size, universe, and events, because that is what turns a fundamentals feed into a trustworthy backtest.