Private Capital Universe Analytics and Benchmarks
Data-driven Insights on Private Capital and Answers on Performance, Cash Flow, and Valuation Behavior
The Burgiss Manager Universe (BMU) is now widely recognized as an industry standard, providing unrivaled breadth and depth of coverage of performance and behavioral data on private capital funds and their holdings. The BMU is a research-quality database, and only includes funds with their complete transactional history.
Today this database consists of over 9,100 private capital funds and fund-of-funds from 1978 to the present, representing nearly $6.6 trillion in committed capital across the full spectrum of private capital strategies, including private equity, private debt, and real assets. See the latest composition statistics here and top line results here.
In the past two years, the BMU has been expanded to cover performance data for more than 70,000 fund holdings, opening up new areas of exploration and possibility. Data is enriched through the Private Capital Classification System (PCCS), a set of strict rules, taxonomies and classifications.
The BMU underpins peer group portfolio and manager benchmarking enabled in the Private i platform; provides the foundation for bespoke engagements with our Applied Research team; helps power 3rd-party risk models; supports independent research with the Private Equity Research Consortium; and powers our universe and benchmarks tool, Private iQ.
Private iQ is a toolset that taps into this data and analytical engine. Calculations are real-time, providing the ultimate in flexibility to help answer questions about the performance, cash flow, and valuation behavior of private capital.
The Measure Reports provide users with the traditional method of summarizing the behavior of funds by allowing the grouping and filtering by Vintage Year, Asset Class, Geography, Industry, Development, and Market. These reports are available in a variety of formats which can provide Point to Point, Trailing Period, and other dynamic calculations.
The Time Series Calculator provides a stream of pooled quarterly time-weighted rates of return for a selected set of funds.
The Profiler presents an intuitive way to examine the performance and cash flow behavior of a selected set of funds over their life.
The iQ Test is a quantitative due diligence solution that allows for an easy comparison of a manager’s track record to a user-specified peer group.
The Relationship Explorer is an analytical tool that visually and quantitatively describes the relationship between any two of the available measures for a selected set of funds.
The Concentration Analysis measures the distribution of wealth for a selected set of funds using the Lorenz curve methodology. It allows users to better assess their risk profile by determining what percentage of the funds is driving performance.
Advanced features, such as the Conditional Filter, allow fine-tuned narrowing of results that depend on calculated criteria, for example selecting only the top quartile IRR – 1 Year funds within the user-defined universe. Private iQ provides the ability to compare private capital funds to a user-specified index using various public market comparison methodologies, including Gredil-Griffiths-Stucke Direct Alpha, the Kaplan-Schoar Public Market Equivalent, or the Long-Nickels Index Comparison Methodology. Preferences include the ability to calculate Pooled and Individual fund results in user-specified currencies. This functionality is currently supported in all modules with the exception of Relationship Explorer and Concentration Analysis.
The Burgiss Manager Universe is sourced exclusively from limited partners, avoiding the natural biases associated with other data sourcing models which rely on voluntary manager submissions and FOIA requests. Results are updated with every quarter end publication date. Results are always net of fees and carried interest to limited partners. Fully customizable peer groups and robust analytics enable meaningful and consistent comparisons — users can benchmark managers and portfolios, establish expectations for modeling different asset classes, and stay up-to-date about macro changes in the investment environment.