The asset manager for a changing world

 

Based on the latest academic insights, MFA provides us with an efficient and precise tool to translate our views on the drivers and factors affecting the core asset classes into portfolios.

In one single step, it takes into account our active views on the core asset classes, correlations, risks and any clients’ constraints, for example, on the acceptable tracking error and the exposure to a particular asset class.

Its objective is to maximise the portfolio’s risk/return and its outcome-based targets, while linking the size of positions in the portfolio to the strength of the conviction scores on the core asset classes.

Exhibit 1: The principles underlying our proprietary MFA model

mfa 1

Source: BNPP AM, as of 11/10/2019

 

MFA works with an uncertainty term on expected returns. Accordingly, it takes into account alternative outcomes where reality deviates from the initial forecasts – i.e. when it is more negative or more positive than our investment view. We believe this helps produce robust portfolios.

The MFA algorithm finds the optimal allocation combining our multi-asset investment views, portfolio structure and the client’s risk profile.

We use six factors in our model.

Exhibit 2 shows the factor exposures of the main asset classes. What is evident is the vast difference in factor loadings from asset class to asset class.

Exhibit 2: Factor exposures of main asset classes

mfa 2

Source: BNPP AM, as of 11/10/2019

So how does MFA work in practice?

Let’s use high-yield credit as an example. It sits halfway between equities and bonds in a company’s capital structure so multiple factors are at work. So European high-yield credit is exposed to corporate spreads and market risk. If you were to overweight European HY in portfolios, they would be impacted along these factor exposures. To be complete, equities would be primarily driven by market risk, while bonds would be mainly driven by the duration factor.

Example 1: Factor exposures of EUR high-yield

mfa 3 

Source: BNPP AM, as of 10/10/2019

 

MFA’s most powerful feature is the simultaneous mapping of core views across asset classes onto a single set of factor exposures, while taking into account the constraints for each portfolio.

The optimiser will try to achieve the same factor exposures for every portfolio, using the portfolio’s tradeable assets. Of course, in practice, achieving identical factor exposures with only a limited set of assets is impossible, but as the example shows, factor exposures in real-life portfolios will largely mimic unconstrained exposures.

Example 2: Unconstrained vs. a Europe-centric multi-asset portfolio – comparing the factor exposures of our current views

mfa 4

Source: BNPP AM, as of 11/10/2019

[1] This is a shortened version of the paper entitled INTRODUCING A PROPRIETARY PORTFOLIO CONSTRUCTION SYSTEM. For the full version, click here.

[2] Watch the video on our new multi-factor allocation here


 

The views expressed are those of the Investment Committee of MAQS, as of October 2019. Individual portfolio management teams outside of MAQS may hold different views and may make different investment decisions for different clients.