About EPFR’s Fund Flows and Allocations Data and Insights
Unparalleled understanding of how money is moving and why
Our best-in-class Fund Flows and Allocations Data helps you reveal the investible truth by looking at market trends, investor sentiment, liquidity, risk signals and corporate actions, and can be tailored to your specific use case.
$55T+
93%
151K+
$7T+
25+
Primary benefits
Industry-leading timeliness and granularity
Supports both bottom-up and top-down asset allocation strategies
Illustrated analysis of key factors driving current flow trends
Critical insights at macro and stock levels
Unique views on fund manager and investor sentiment
Insight into the fixed Income fund market at a bond ownership and security level
Connecting the dots with EPFR’s Fund Flows
Dating back to 1995, our fund flow data provides as-reported coverage of the net flows into and out of a universe of over 151,000 share classes and more than $55 trillion in assets tracked (AUM), helping our clients reveal the investible truth from:
- Equity Fund Flows
- Bond Fund Flows
- All other major asset classes, including: Money Market Flows, Alternative Fund Flows, and Multi-Asset Flows
Trusted by:
%
of the Bulge Bracket (the world’s largest investment banks)
%
of the “top 20” global asset management firms (by AUM)
%
of the Bulge Bracket (the world’s largest central banks)
%
of the “top 20” global asset mgmt firms (by AUM)
Our data and insights are highly cited in
Latest Insights
Thought leadership and analysis that help you find a signal in the noise
Rotating from new to old in mid-February
Funds dedicated to the old world and conventional asset classes enjoyed a rare moment in the sun during the second week of February, which ended with the new US administration promising reciprocal tariffs on trading partners and a higher-than-expected February inflation number for the world’s largest economy.
Plenty of uncertainty for investors to balk at
Reports that a Chinese company had built and trained an open-source artificial intelligence (AI) model in record time, and at a fraction of the costs incurred by US developers, roiled US equity markets during the final week of January. Investors found themselves revisiting assumptions about the major drivers of US markets such as Nvidia, Alphabet and Meta.
Has DeepSeek deep-sixed tech sector momentum?
Reports that a Chinese company had built and trained an open-source artificial intelligence (AI) model in record time, and at a fraction of the costs incurred by US developers, roiled US equity markets during the final week of January. Investors found themselves revisiting assumptions about the major drivers of US markets such as Nvidia, Alphabet and Meta.
Rotating from new to old in mid-February
Funds dedicated to the old world and conventional asset classes enjoyed a rare moment in the sun during the second week of February, which ended with the new US administration promising reciprocal tariffs on trading partners and a higher-than-expected February inflation number for the world’s largest economy.
Plenty of uncertainty for investors to balk at
Reports that a Chinese company had built and trained an open-source artificial intelligence (AI) model in record time, and at a fraction of the costs incurred by US developers, roiled US equity markets during the final week of January. Investors found themselves revisiting assumptions about the major drivers of US markets such as Nvidia, Alphabet and Meta.
Has DeepSeek deep-sixed tech sector momentum?
Reports that a Chinese company had built and trained an open-source artificial intelligence (AI) model in record time, and at a fraction of the costs incurred by US developers, roiled US equity markets during the final week of January. Investors found themselves revisiting assumptions about the major drivers of US markets such as Nvidia, Alphabet and Meta.
Playing with dynamite
In this Quant’s Corner, we will look at the growing number of single-security Leveraged Funds in EPFR’s database and explore ways to generate alpha-creating signals from their unique characteristics.