Use Cases

Financial Data API for Academic Research

Free tier for researchers. Point-in-time data. Citation-ready. Python and R SDKs. The academic financial data and free research data API for university finance research.

Get free access

Free access for researchers

Free tier

1,000 API calls per day. No credit card. No paywall.

Point-in-time data

Survivorship-bias-free. Backtest-safe. Publication-ready.

Citation-ready

Stable schemas. Reproducible. Documented methodology.

Python & R SDKs

Native packages for quantitative research workflows.

100+ years history

Long-run studies. Event studies. Factor research.

Global coverage

Equities, fixed income, macro, fundamentals.

Data quality for rigorous research

01

Point-in-time fundamentals

No look-ahead bias. Data as it was known at each date.

02

Survivorship-bias-free

Delisted firms included. No cherry-picking.

03

Structured JSON

Typed schemas. No parsing. Direct to pandas/R.

04

Documented methodology

Transparent definitions. Replicable results.

Python and R examples

Python
import eulerpool
import pandas as pd

client = eulerpool.Client("ep_live_xxx")
df = client.equity.fundamentals(
    "AAPL", as_of="2020-01-15"
)
print(df.head())
R
library(eulerpool)

client <- eulerpool_client("ep_live_xxx")
fundamentals <- equity_fundamentals(
  client, "AAPL",
  as_of = "2020-01-15"
)
head(fundamentals)

Frequently asked questions

Yes. Eulerpool provides point-in-time, survivorship-bias-free data that meets academic research standards. 100+ years of historical data, delisted companies included, and GAAP/IFRS-normalized fundamentals make it suitable for published research and dissertations.

Yes. The free tier (1,000 calls/day) is sufficient for most academic projects. Additional academic discounts are available for universities and research institutions. Contact us for institutional pricing that covers entire departments or research groups.

Yes. Eulerpool data can be cited in academic publications. We provide data provenance documentation and methodology descriptions suitable for peer review. Many published papers in finance and economics use Eulerpool as a data source.

Yes. Point-in-time financial statements, survivorship-bias-free price data, and pre-calculated ratios (P/E, P/B, ROE) enable factor research. The Python SDK integrates with pandas, numpy, and common backtesting frameworks for quantitative analysis.

Eulerpool provides similar data coverage to CRSP (prices) and Compustat (fundamentals) via a modern REST API. Key advantages include global coverage (not US-only), real-time data, point-in-time storage, and a free tier. The API format makes it easier to integrate into modern research workflows.

Start your research today.

Free academic access. No credit card. No sales calls.

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