Fund Ratings Get Volatile as Financial Crisis Fades From the 10-Year Window.
Now providing advanced stress-testing features that deliver insight into fund performance across various regimes and hypothetical scenarios.
The leading TDF analysis and reporting solution for DC Advisors is now available to support the unique needs of TDF product and sales teams.
Submit it here, and we will respond shortly.
In this post, our research team examines why investors should proceed with caution when selecting top-ranked funds.
While the health of the bull market, the raging fee wars and the ongoing active vs. passive debate continue to capture the money management industry’s attention, something fascinating has quietly taken place on fund analysts’ radars.
The endowment model, and active management in general, has come under increased scrutiny, while indexed, or passive, products have grown in popularity and number. Regardless of where you stand on that debate, it’s hard to deny that the Ivies approach to asset allocation has been very good.
Similar to 2017 performance, this past fiscal year was a strong one for most Ivy League endowments. Fiscal year 2018 is noteworthy, however, for being the first year that long horizon (10-year) returns from all Ivy endowments lagged behind the 60-40 portfolio.
“The smart beta label still represents a small, new, heterogeneous, and most likely misunderstood, group of exchange-traded funds in the fixed income space,” says MPI’s Megan Woods in this article on Smart Beta bond funds by Institutional Investor‘s Julie Segal.
“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