Using returns-based investment risk analytics to shine a brighter light into the dark areas of individual funds and investment portfolios.

Investors – and the Feds – need to focus less on specific stories like MicroStrategy’s Bitcoin exposure, and more on how big the systemic risk picture may be for all of us.

Using MPI’s Dynamic Style Analysis (DSA), we analyzed 600 equity hedge funds to assess their exposure to Russian equities

We argue that Sharpe Ratios could be hugely deceiving for derivative strategies – especially if they are in an outlier category as it was the case for the Allianz Structured Alpha funds.

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.

This document provides an introduction to MPI portfolio stress testing methodology as well as a step-by-step overview of how to conduct fund- and portfolio-level stress tests within the MPI Stylus Pro application.

In this post, our research team demonstrates how scenario analysis can highlight different risk sensitivities among same-vintage TDFs that could go undetected by traditional risk measures.

In this post, our research team shows how returns-based scenario analysis can be used to enhance traditional portfolio risk analysis by helping to assess potential fund performance through extreme market events.

In this post, our research team demonstrates a clever way to backtest forward-looking scenarios commonly used in portfolio risk analysis.

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.

It is generally known that endowments invest in risky assets, but quantifying such risks has remained challenging due to a lack of information about returns. We set out to address this challenge and developed a new basis for estimating endowment risks.