2025年三季度私人资本指数（英）

Contents PitchBook Data, Inc. Nizar TarhuniExecutive Vice President ofResearch & Market Intelligence Daniel Cook, CFA Sr. Director, Global Head ofQuantitative Research Zane Carmean, CFA, CAIA Director, QuantitativeResearch Institutional Research Group Analysis Zane Carmean, CFA, CAIADirector, Quantitative Researchzane.carmean@pitchbook.com Miles OstroffAssociate Quantitative Research Analystmiles.ostroff@pitchbook.com pbinstitutionalresearch@pitchbook.com Published on January 15, 2026 Overview What are the PitchBook Private Capital Indexes? Additionally, the indexes unlock useful analysis on privatemarket volatility and drawdowns during difficult environments.One known limitation of private market performance and riskmeasurement is the tendency for fund returns to appear overly"smooth," with asset pricing slow to change from one period tothe next. This smoothing results in lower perceived volatilitythan what is likely realistic, which can impact diversificationdecisions and risk/reward estimations based on reportedreturns. To address 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 indexes arebuilt with PitchBook's fund cash flow and NAV data and serve asa supplement to our quarterlyPitchBook Benchmarks report. This report is organized into sections for each of the sevenstrategies, with subcategories within private equity, venturecapital, real estate, real assets, private debt, and funds of funds.We also track returns by fund quartile ranking, bucketedaccording to a fund's class and vintage year benchmark. For theoverall Private Capital Index, we include versions by globalregion. These various combinations provide an overall view ofprivate market performance by money-weighting the cash flowsand NAV changes of active funds in a respective fund category. Relatedly, we also publish Private Capital Return Barometers,which are available for our US indexes and measuremacrofinancial factors' influence on returns. On ourNews &Analysis web page, we include nowcasts implied by ourBarometers to provide a more timely estimate for US privatecapital returns. Our Benchmarks report has been providing quarterly returnssince 2018, with our data series extending back to the late 90s.By calculating the change in NAV from one quarter to the next,adjusting for cash flows coming into and out of funds via capitalcalls and distributions, we can get a sense of each asset class'sperformance in a pseudo-time-weighted manner. Linking thequarterly return figures allows us to construct an index, providinga useful alternative comparison with other portfolio holdingssuch as public markets. PitchBook clients have access to all the aggregate data in theaccompanying XLS, as well as the underlying constituent fundsin the PitchBook Platform. Please reach out with any questionsor 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 a capital-weighted basis.1They are not practically investable and are subject to change aswe continually update our datasets. Desmoothed returns Adjusting for return smoothing We also display the reported and adjusted volatility estimates foreach private fund asset class and correlations between thedesmoothed quarterly returns and the quarterly returns of selectpublic market indexes. If the ACF adjustments are not made, theprivate market asset classes will appear more attractive on a risk-adjusted basis because of the understated volatility measures. Thecorrelations between the Private Capital Indexes and publicmarkets may also be lower, potentially overstating thediversification benefits. We provide historical context on how therelationship with public equities has changed, as well as the overallcorrelation coefficients since 2000. Interpreting interim returns for private markets can be challengingdue to the inherent smoothing that takes place as a result ofinfrequent and disparate valuation adjustments to a fund's assets.This smoothing produces a potential bias in estimating volatilityand correlations, which are necessary inputs for many allocators'risk modeling in portfolio construction and monitoring. If leftunadjusted, our indexes are subject to this bias. To address the issue, we have used a common approach todesmooth private market returns. This section provides adjustedreturn series using a first-order autoregression model. In simpleterms, we have found evidence that private market returns arecorrelated from one quarter to the next by about 50%, althoughthis varies across asset classes and time. The following page also includes peak-to-trough drawdowns in theunadjusted reported returns during select time frames, includingthe dot-com crash and global financial crisis (GFC). We leave thesedrawdowns unadjusted to recognize the magnitude o