MPI Analyses FY 2016 Ivy League Endowment Performance

Based on a research study conducted by MPI, asset allocation remains the largest determining factor in endowment performance. Commodities and Emerging Markets, each of which suffered respective losses due to continued declining oil prices or political turmoil, were a significant drag on Ivy League funds' returns.  Despite FY 2015's stellar performance by Venture Capital and marginally positive returns by Hedge Funds, both asset classes posted negative returns in FY 2016. Real Estate, US Equities and Bonds were the highest performers in FY 2016.

Yale continued its strong performance. Posting a 3.4% FY 2016 return, Yale beat Princeton, the only other Ivy League endowment with a positive return, by 2.6%. By contrast, Yale arch-rival Harvard's near $2 billion loss elicited official calls in the press to reevaluate the University's entire investment strategy.

Yale's substantial outperformance is attributable to four themes including over-weighting private investments (Venture Capital, Hedge Funds, Private Equity and Real Estate), avoidance of Commodities and Emerging Markets and a focus on asset allocation implemented through a strong emphasis on fund manager selection. These themes reflect the "Yale Model" that encapsulates the investment philosophy of Yale's long-time chief investment officer David Swenson.

The sources of investment return of university endowments remain opaque. Using MPI Dynamic Style Analysis, we use raw information derived from publicly available data to make robust insights into the factors impacting Ivy League endowment performance.

About MPI
MPI (Markov Processes International) is a global provider of investment research, analytics and technology. Its solutions are used by leading organizations throughout the financial services industry, including: alternative research groups, hedge funds, hedge fund of funds, family offices, institutional investors, consultants, private banks, asset managers, investment advisors and private wealth professionals.  For more information, visit http://www.markovprocesses.com.  Follow us on Twitter @MarkovMPI.

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SOURCE Markov Processes International

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