Preqin forecasts provide a complete, data-driven, and granular overview of private markets. Independent of the views of the Research Insights team, the forecasts produced by the model are intended to provide a base case for further analysis. The results are published annually in our Private Markets in report series (formerly Future of Alternatives) and made available to Preqin Insights+ subscribers in October of each year. In 2025, we made predictions for 87 private markets strategy groups in four regions.
We model private markets as a system consisting of sources of funding, aggregate cash flows, and capital accumulation. This system replicates the flow of capital through private capital markets and enables us to forecast multiple market characteristics (e.g., growth rate, performance, capital raised, and the ratio of dry powder to unrealized value) concurrently. This approach guarantees that our forecasts are internally consistent and that the model will generate plausible scenarios for the future.
The principal starting points of the model are fundraising and performance, for which we generate future values using a statistical method called ensemble forecasting. In private markets, all the data is noisy and the number of available observations is limited. Our approach collects breadcrumbs of information from up to 14,000 financial series. Next, it combines the evidence from the entire population of models, giving more prominence to those that were consistently predictive on data not used to train them. This allows us to deliver robust forecasts that are burdened with less risk.
Once we have generated expected future values of capital raised and performance, we build simple forecasts of capital called and capital distributed. We know the values of dry powder and unrealized value that were observed at the time of the forecast. This enables us to calculate dry powder and unrealized value going forward.1 The sum of the two gives us AUM – a measure of total market value. We repeat this process for each of the 87 strategy groups. Next, we aggregate all the data series to generate values for the market, regions, asset classes, region–asset class pairs, and strategy groups at the global level.
Every forecasting method is based on data characteristics that remain constant over time. The reliability of predictions generated by our approach relies on two such constants: patterns or long-term trends in each forecast data series, and the relationships between the future values of the predicted data and the observables. We test these two features jointly to ensure they are sufficiently reliable to consistently deliver useful predictions.
Our model disentangles the effects of capital raised and performance on AUM. In this sense, it is causal. While it produces effective forecasts, a limitation is that it does not fully identify the indirect impact of changes in macro variables – such as shifts in the sovereign yield curve. As a result, our model may not measure the total impact of any individual factor (e.g., monetary tightening). It also cannot answer questions that are counterfactual.
Answers to FAQs
Preqin’s forecasts are independent of BlackRock’s Capital Market Assumptions and use a different methodology and terminology
All projections are net of fees
Where performance is provided as a percentage, it always represents internal rate of return (IRR)
Our performance figures are nominal (that is, they are unadjusted for inflation)
Dry powder, unrealized value, and AUM exclude funds denominated in yuan renminbi. These funds are deemed less investable for many of our clients
We do not make assumptions about any variables (such as interest rates). When we predict the two drivers, we take historic values and third-party forecasts as inputs
Since funds do not report the breakdown of their investment by country, we cannot produce predictions at a country level
