The real return driver behind Brown University’s FY20

As Alternatives Watch reported earlier this month, the Ivy League endowment funds on average have underperformed a conservative portfolio of 60% stocks and 40% bonds for the second year in a row. The outlier though was Brown University, according to the analysis compiled by Markov Processes International (MPI), which reported Brown’s gains of 12% for the twelve-month period ending June 30, 2020. Those in the industry, according to MPI, have chalked up the endowment’s success to the university’s private market exposure. MPI rightly points out that it is only part of the story in that Yale has a 41% allocation to private markets, and underperformed Brown, which has a 31.2% combined allocation to private equity and venture capital. Others have credited Brown’s hedge fund portfolio, which makes up 35% of the overall endowment. The program reportedly has holdings in niche offerings from Atreides Management LP, Melvin Capital Management and Skye Global Management. By comparison Yale and other Ivy League endowments have similar although smaller allocations in the neighborhood of 20-25%. MPI decided to dive deeper into Brown’s numbers. The firm relied on its own patented analysis technique -- Dynamic Style Analysis. It is a model the company sells to institutional investors that boasts a 25-year history. Built on the backbone of the returns-based technique developed by William F. Sharpe in the early 90s, the model is designed to provide a more precise and transparent view of complex or opaque investment product performance such as hedge funds, private equity, structured and fixed-income products. MPI estimated that over the past two years that private equity, venture capital and technology holdings have dominated Brown’s portfolio exposure and grown. While last year was the year of private assets for Brown, this last year was really the "year of tech." “Whether known or unbeknownst to the investment team, they seem to have accumulated a significant overexposure to tech stocks which, regardless of the skills of their managers, could be valuable information for their risk team,” MPI concluded in its analysis. While the team at MPI didn’t have full access to every portion of Brown’s portfolio, the analysis showed that the investment team’s hunt for the best talent may have created a significant over-exposure to the technology sector that to date has worked to their advantage. They say though that significant "alpha" can often signal the deficiency of the model of a missing factor -- rather than a proverbial "skill." For MPI the precision from annual data on portfolio exposures could be telling, yet officials added that more interesting results may be gleaned from quarterly data for the private asset portfolio and monthly or daily data within the public markets portfolio being analyzed together.

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