New dataset showcases investor interest for individual fixed income securities across both mutual funds and ETFs
BOSTON, Feb. 22, 2022 /PRNewswire/ -- EPFR, a subsidiary of Informa Financial Intelligence and worldwide industry leader in providing fund flows and allocation data to financial institutions, launches the EPFR Fixed Income Flows and Holdings dataset providing exclusive monthly, fund-level securities data. The new dataset helps clients strengthen their understanding of ownership and demand for over 50,000 fixed income securities.
The EPFR Fixed Income Flows and Holdings dataset provides insight into bond ownership across multiple fund groups and gives clients a wide range of tools to filter the data. These include fund geo-focus, sector focus, trading currency and maturity date. Clients can also run comparative analysis using active vs passive, institutional vs retail and foreign vs domestic filters. The dataset currently offers history back to 2018, opening the door to quantitative analysis and modeling.
"We are delighted to release this new EPFR data offering, to provide clients with the ability to view individual securities that are held by funds, as they are bought and sold and roll up to various allocations-and gain access to data updates on a monthly, rather than quarterly basis," said Mike Digris, EPFR Head of Data. "Access to this information and the associated securities metadata paves the way for better investment decisions."
Clients such as Debt Capital Markets (DCM) desks can use this data to provide corporate issuers with a clear picture of who is holding their debt, which managers are increasing their positions and which funds are attracting inflows. DCM desks can incorporate data insight into pitch books to distinguish themselves from competitors when vying for business from those issuers.
"We know DCM teams work in fast-paced environments and require very up-to-date data on fixed-income markets," said Cameron Brandt, EPFR Director of Research. "With the Fixed Income Flows and Holdings dataset, they have a far more granular view of the markets. They can sharpen their competitive edge with fresh, individual security level insights on the impact of major market forces."
The Fixed Income Flows and Holdings dataset utilizes a subset of the 142,500 globally domiciled funds tracked by EPFR on a daily, weekly and monthly basis. By combining the flows, allocations and holdings information reported by over 2,000 funds, the new dataset provides clients with a window into the appetite of mutual funds and ETFs for individual corporate, sovereign and other bond types. With historical data dating back to October 2018, quant analysts can run regression analysis and back tests to create investible signals based on how individual and groups of bonds trade.
"Our combination of flows, and holdings level data is not available anywhere else in the marketplace," said Digris. "Quant analysts now have the ability to run analysis using these smaller building blocks to create whatever they imagine."
Findings from the EPFR research team determined that the data has predictive capabilities. "Among the bonds tracked in the new dataset, several are issued by Chinese real estate developer, Evergrande," noted Brandt. "Applying an EPFR Smart Factor - in this instance, a simple factor, 'Fund Count' - showed that funds holding this debt began shedding it before Evergrande's problems hit its market valuation."
About EPFR:
EPFR, a subsidiary of Informa plc (LSE: INF), provides fund flows and asset allocation data to financial institutions around the world. Tracking over 142,000 traditional and alternative funds domiciled globally with more than $52.5 trillion in total assets, we deliver a complete picture of institutional and retail investor flows and fund manager allocations driving global markets. Our market moving data services include daily, weekly and monthly equity and fixed income fund flows and monthly fund allocations by country, sector and industry. For more information, please visit https://financialintelligence.informa.com/epfr.
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