Academic

Data for Rigorous Financial Research

Advance your research with institutional-grade financial data — 30+ years of clean historical records across equities, fundamentals, macroeconomics, and alternative datasets, accessible programmatically via a well-documented REST API.

Prices, statements, corporate actions

Equities & Fundamentals

80,000+ global equities with decades of OHLCV pricing, income statements, balance sheets, financial ratios, earnings surprises, dividend history, and corporate actions — the foundation for empirical asset pricing and event study research.

Economics, ESG, COT, insider trades

Macro & Alternative Data

Macroeconomic time series (GDP, CPI, interest rates), ESG ratings, Commitment of Traders reports, insider trading disclosures, and institutional 13F holdings — for research beyond traditional price and fundamental datasets.

About FMP

Financial market data built for academic and empirical research.

Cross-country coverage

Equities, economics, and company data across every major economy — supporting international finance, comparative markets, and cross-sectional return research.

80,000+ securities

Broad universe including small-cap and international equities often absent from commercial databases — reducing survivorship bias in empirical studies.

Alternative datasets

ESG scores, Commitment of Traders reports, insider trading disclosures, Senate and House trading data, and 13F institutional holdings for non-traditional research questions.

30+ years of clean history

Multi-decade records spanning several market cycles — sufficient for long-horizon studies, calendar anomaly research, and survival bias analysis.

Research-Grade Data Infrastructure

Programmatic REST API with consistent formatting that integrates with Python, R, and standard academic data workflows without manual data cleaning overhead.

99.99% uptime SLA

Stable, reproducible data delivery for research requiring consistent, replicable datasets across long time horizons.

Sub-second latency

Academic researchers choose FMP for the breadth, depth, and accessibility of financial data that serious empirical work demands.