MPI delivers advanced portfolio analytics to help fund buyers make smarter, more informed decisions, while offering fund sellers deeper insight into the style, performance and risk characteristics of their product sets.
What Drives the Performance of the World’s Largest Active Fixed Income Fund?
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.
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How have risk parity funds actually acted (or reacted) during the current crisis? We use our Stylus Pro system to estimate changes in allocations and leverage levels.
We use our tools and proprietary dynamic factor model to analyze Renaissance RIEF to gain insight into the results in the first quarter of 2020.
We use our Stylus Pro system’s patented Dynamic Style Analysis (DSA) with daily fund data to determine whether U.S. equity mutual funds have substantially decreased market exposure in the highly volatile period from early-February to mid-March
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.
“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