2025年二季度私人资本指数（英）2025

Q2 2025 Contents PitchBook Data, Inc. Nizar TarhuniExecutive Vice President of Research &Market Intelligence Daniel Cook, CFAGlobal Head of Quantitative Research &Market Intelligence Zane Carmean, CFA, CAIADirector of QuantitativeResearch Institutional Research Group Analysis Zane Carmean, CFA, CAIADirector of Quantitative Researchzane.carmean@pitchbook.com Miles OstroffAssociate Quantitative Research Analystmiles.ostroff@pitchbook.com pbinstitutionalresearch@pitchbook.com Published on October 31, 2025 Overview Whatare the PitchBookPrivate CapitalIndexes? Additionally, the indexes unlock useful analysis on privatemarket volatility and drawdowns during difficultenvironments. One known limitation of private marketperformance and risk measurement is the tendency forfund returns to appear overly "smooth," with asset pricingslow to change from one period to the next. Thissmoothing results in lower perceived volatility than what islikely realistic, which can impact diversification decisionsand risk/reward estimations based on reported returns. Toaddress this limitation, this report includes adjustedreturns for private market risk measurement. The PitchBook Private Capital Indexes are quarterly returnbenchmarks for the private market industry. These indexesare built with PitchBook's fund cash flow and NAV data andserve as a supplement to our quarterlyPitchBookBenchmarks report. This report is organized into sections for each of the sevenstrategies, with subcategories within private equity,venture capital, real estate, real assets, private debt, andfunds of funds. We also track returns by fund quartileranking, bucketed according to a fund's class and vintageyear benchmark. For the overall Private Capital Index, weinclude versions by global region. These variouscombinations provide an overall view of private marketperformance by money-weighting the cash flows and NAVchanges of active funds in a respective fund category. Relatedly, we also publish Private Capital ReturnBarometers, which are available for our US indexes andmeasure macrofinancial factors' influence on returns. OnourNews & Analysis web page, we include nowcastsimplied by our Barometers to provide a more timelyestimate for US private capital returns. Our Benchmarks report has been providing quarterlyreturns since 2018, with our data series extending back tothe late 90s. By calculating the change in NAV from onequarter to the next, adjusting for cash flows coming intoand out of funds via capital calls and distributions, we canget a sense of each asset class's performance in a pseudo-time-weighted manner. Linking the quarterly return figuresallows us to construct an index, providing a usefulalternative comparison with other portfolio holdings suchas public markets. PitchBook clients have access to all the aggregate data inthe accompanying XLS, as well as the underlyingconstituent funds in the PitchBook Platform. Please reachout with any questions or feedback. The indexes provided are meant to be estimates of asset class performance,hypothetically creating a return if one had access to all active funds on acapital-weighted basis.1They are not practically investable and are subject tochange as we continually update our datasets. Desmoothed returns Adjusting forreturnsmoothing We also display the reported and adjusted volatilityestimates for each private fund asset class and correlationsbetween the desmoothed quarterly returns and the quarterlyreturns of select public market indexes. If the ACFadjustments are not made, the private market asset classeswill appear more attractive on a risk-adjusted basis becauseof the understated volatility measures. The correlationsbetween the Private Capital Indexes and public markets mayalso be lower, potentially overstating the diversificationbenefits. We provide historical context on how therelationship with public equities has changed, as well as theoverall correlation coefficients since 2000. Interpreting interim returns for private markets can bechallenging due to the inherent smoothing that takes placeas a result of infrequent and disparate valuation adjustmentsto a fund's assets. This smoothing produces a potential biasin estimating volatility and correlations, which are necessaryinputs for many allocators' risk modeling in portfolioconstruction and monitoring. If left unadjusted, our indexesare subject to this bias. To address the issue, we have used a common approach todesmooth private market returns. This section providesadjusted return series using a first-order autoregressionmodel. In simple terms, we have found evidence that privatemarket returns are correlated from one quarter to the nextby about 50%, although this varies across asset classes andtime. The following page also includes peak-to-trough drawdownsin the unadjusted reported returns during select time frames,including the dot-com crash and global financial crisis (GFC).We leave these drawdowns unadjusted to recognize themagnit