MPI Research

Leveraging our patented analytical models to examine and explore some of the most pressing issues in the investment community.

Risk

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

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.

Opaque Investments

Better understanding complex and opaque products through more dynamic analytical models.

We use Allianz Structured Alpha hedge fund as an illustration to demonstrate how investors could apply quantitative techniques to assess potential risks of complex volatility strategies.

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.

Smart Beta

Analyzing the opportunities and challenges tied to one of the fastest growing fund segments.

Investors have a tendency to downplay interest rate sensitivity as a factor influencing equity products, with the assumption being that its effect must be negligible at most. One of a handful of exceptions to that assumption, however, is concern over the rate sensitivity of low volatility “smart beta” funds.

Continuing our exploration into the smart beta segment (Part 1, Part 2), in this third post we introduce a simple “IQ Test” that can help investors and managers measure the “smartness” of the increasing number of non-cap-weight rules-based products on the market.

Target-Date Funds

A quantitative analytical series looking at one of the most popular retirement investing fund segments in the market.

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.

Morningstar’s 2017 Target Date Landscape Report indicates that approximately one quarter of TDF series shifted the target equity allocation of at least one vintage by 15% or more over the last 5 years and nearly half by at least 5%.

Endowments

A deeper look inside the investment returns of some of the most prestigious endowments in the world.

Lessons (not) learned: our analysis shows Ivies are at pre-GFC levels of risk

For the second straight year, Brown outperformed all other Ivy endowments by a large margin. Our research team, using MPI Stylus Pro to dissect the endowment annual returns, provides a plausible explanation of the endowment’s spectacular results.

Fund Research

Our library of individual fund and peer group analysis. Looking for a specific fund or peer group that you don't see? Let us know.

We use Allianz Structured Alpha hedge fund as an illustration to demonstrate how investors could apply quantitative techniques to assess potential risks of complex volatility strategies.

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

The quantitative research and approach demonstrated in this white paper, helps to provide a useful and pragmatic framework for investment practitioners to screen for liquidity risks when selecting new fixed-income products, as well as when conducting ongoing monitoring of their current bond funds.

This white paper looks at the period of the increased volatility in the financial markets leading up to and on November 8th and provides valuable insights into internal workings of risk parity strategies during periods of heightened volatility.