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In this post, our research team uses regime-based investment risk analytics to present an approach to assessing the size and significance of investor blind spots during a typical manager screening process.
After years of underperformance following the financial crisis, the non-traditional bond fund segment is beginning to shine, outperforming the broader market index in the face of rising rates.
Bitcoin has had a spectacular year, with its price growing by 2,000 percent, topping out at nearly $20,000 before falling to a little over a third of that value. So, we posed the question to ourselves: how might investors have achieved Bitcoin-like returns over the last two years without needing Ambien to stomach the whipsaw swings in price?
2017 Yale endowment report rebuts Warren Buffett’s 2016 Berkshire Hathaway investor letter that “financial ‘elites’”, including endowments, are better off investing in low fee index products and not “wasting” money on active managers’ hefty fees. We did our own calculations and here’s what we found…
“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