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.
Using MPI’s quantitative surveillance framework we discover a slew of red flags that could have alerted investors in the Infinity Q Diversified Alpha 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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Using Norwegian pension as an example we provide a quick and easy path for US pensions to become more transparent and regain trust of their beneficiaries as well as general public
Lessons (not) learned: our analysis shows Ivies are at pre-GFC levels of risk
It’s been a wild rollercoaster ride these days for Bitcoin investors. The cryptocurrency hit an all-time high of $64k in April only to plummet nearly 50% a month later. Last year, as the entire world shut down access to mountain peaks and surfing spots, people started to look for stay-at-home ways to supply their adrenaline fix – and speculative trading fit the bill.
Following up on our most recent article, “Infinity Q: Too Much Alpha,” Infinity Q also managed a hedge fund product, Infinity Q Volatility Alpha, which exclusively employed volatility strategies. Using known sub-strategies as regression factors for a multi-strategy product can prove very useful in identifying the source of both skill and risk in a more complex product.
“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