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Point-in-time data for cross-sectional asset pricing research

Free
for academics
30+
years history
$25K+
annual savings

The challenge

A finance PhD program needed survivorship-bias-free data for cross-sectional asset pricing research. CRSP + Compustat licenses cost $25,000+ per year and required institutional procurement processes. Graduate students needed programmatic access for large-scale empirical studies.

The solution

Eulerpool's free tier provided 1,000 API calls per day — enough for comprehensive factor research. The Python SDK and R package let students query point-in-time fundamentals, price data, and financial ratios directly from their research notebooks. Delisted companies are included, eliminating survivorship bias.

The results

The department replaced their CRSP + Compustat subscription entirely for student research projects. Graduate students published papers using Eulerpool data with full reproducibility. Annual savings: $25,000+. Student access: unlimited (free tier per student).

Free
for academics
30+
years history
$25K+
annual savings

APIs used

FundamentalsHistorical DataFinancial RatiosPython SDK

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