What Drives the Performance of the World’s Largest Active Fixed Income Fund?
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Fiscal year 2019 was a curious year for the Ivy League endowments. In a year with strong returns in key private market investment classes, the average Ivy underperformed a traditional domestic balanced 60-40 portfolio in FY 2019. Ivies also experienced a wider dispersion of returns and saw a shift in the historical positioning of performance leaders and laggards.
Since its launch in 2007, PIMCO Income Fund has become one of the top-performing US bond funds. However, in 2019 the fund has underperformed both the benchmark and most of its peers. Using this fund as an example, we will demonstrate how advanced returns-based analysis can be used to analyze complex fixed income products without delving into volumes of complex holdings.
The grades for all the Ivy League endowments are in – and they are rather disappointing. Save for Brown, all Ivies underperformed the 9.9% return of a domestic 60-40 portfolio in fiscal year 2019. The Ivy average in FY 2019 was 6.7%, significantly underperforming the 60-40 and reversing two years in which they outperformed the traditional domestic benchmark.
Using our analytical tools and publicly available endowment annual performance data, we project FY2019 performance of large and small endowments, as well as the Ivy League average and Yale
“The quantitative analysis firm has a method for back-solving portfolios using returns rather than squishy self-reported allocations, and produced a study for Institutional Investor,” writes Leanna Orr about MPI in her article “David Swensen Is Great for Yale. Is He Horrible for Investing?”
“Markov Processes International… uses a model to infer what returns would have been from the endowments’ asset allocations. This led to two key findings… ” John Authers cites MPI’s 2017 Ivy League Endowment returns analysis in his weekly Financial Times Smart Money column.
Chris Flood from The Financial Times talks about MPI’s technology, its ability to reverse engineer hedge fund returns and applications from fund selection to managing risk and detecting potential fraud. “MPI’s software provides valuable insights into how a hedge fund delivers returns. It can help an investor understand whether a manager is adding value. If some […]
“This method allows firms to effectively deduce strategies at other firms and avoid potential counterparty risks, without being forced to wade through information…” The article “Criminal minds and increased surveillance” highlights MPI’s technology for non-intrusive Oversight and Surveillance.
“Michael Markov, C.E.O. of MPI, a quantitative research firm, said calculations using daily prices of AXA Rosenberg’s mutual fund portfolios suggest that by early 2009, there was “an apparent aberration” in the funds.” The New York Times’ Jeff Sommer features MPI’s analysis in a story “The Tremors From a Coding Error”.
“…(MPI) was hired by a fund two years ago to look into Fairfield Sentry’s returns and found that it was “statistically impossible to replicate them.” New York Times article “In Fraud Case, Middlemen in Spotlight” discusses how MPI found warning signs in Madoff’s returns.
“To folk who want to invest in hedge funds, as well as those who want to invest like hedge funds, Markov Processes has a lot to offer…” The Economist article “In the garden of good and evil” discusses MPI’s expertise in quantitative analysis and replication of hedge funds