The projections come from MPI’s Transparency Lab, which provides unique insights into the styles, risks, and performance of traditionally opaque pensions and endowments.
Ivy League university endowments rebounded from their losses in FY2022, but their significant exposure to venture capital meant that every major endowment likely underperformed traditional 60/40 and 70/30 global equity/bond portfolios, according to projections from Markov Processes International, Inc. (“MPI”), a leading independent FinTech provider of software and services for analyzing investment performance and risk.
The projections come from MPI’s Transparency Lab, which tracks the performance of opaque pensions and endowments.
MPI Transparency Lab estimates that the University of Pennsylvania, Dartmouth University, Brown University and Columbia University endowments will have higher-than-average returns. Meanwhile, Harvard University and Princeton University are projected to be at the lower end of the Ivies.
“Large university endowments are notoriously opaque, providing little indication of what results to expect until they officially release their results, making it a regular autumn spectacle,” said Michael Markov, MPI’s co-founder and CEO. “But even then, after the annual returns are published, there’s little indication of both sources of returns and the risks that were taken to achieve them. We apply our most advanced techniques to publicly sourced data to shed light on this important segment.”
MPI utilizes proprietary technology and public data sources to peek, quantitatively, behind the curtain of a wide range of investments, providing information that is often impossible to obtain otherwise. With the Transparency Lab, all that data and analysis is contained in one place and publicly available, allowing investors, beneficiaries, regulators, researchers, journalists, and other stakeholders to garner unique insight into some of the largest and most opaque investors.
With the MPI Transparency Lab, registered users can view analytics and download “MPI-360” reports that help them uncover trends in asset exposures, explain drivers of both recent and historical results, obtain estimates of risks, drawdowns and efficiency, perform historical stress tests, and evaluate various hypothetical scenarios.
MPI uses its proprietary Dynamic Style Analysis (DSA) and public annual returns to reverse-engineer asset exposure dynamics of large investor portfolios. When endowments report only annual performance figures, a decade’s worth of performance is represented by only 10 data points. Traditional static and rolling-window methods of regression analysis struggle to find credible insights from such infrequent data. MPI’s DSA, however, is uniquely adapted to work with such limited data.