By : Mark Stacey, Senior Vice-President, Co-CIO AGFiQ Quantitative Investing, Head of Portfolio Management, AGF Investments Inc.

A portfolio that is diversified across more than one factor can lead to better risk-adjusted returns over time, but not all methods for combining factors are equally beneficial to future performance.

While it is common to diversify holdings with a differentiated mix of single factor strategies or investment funds, a more optimal multi-factor approach begins at the individual security level and considers how various attributes of one stock should be blended with those of others.

In doing so, investors are able to strike a better balance between targeted factor exposures and fine tuning these exposures more readily in response to changing market conditions.

A single factor vs. multi-factor approach

The advantages of combining different factors has been well researched over the years. This includes the work of Clarke, de Silva and Thorley1 whose studies have shown single factor portfolios to be more volatile and less consistent over time than portfolios that blend multiple factors which demonstrate an ability to generate excess relative returns over the long term.

This stems from the difficulty of timing (and rebalancing) factor performance due to their inherent cyclicality. Although factors are anticipated to outperform over the longer term, there will be periods when they move in or out of favour. In this regard, momentum has been a fairly consistent factor leader over the past several years, while value have tended to lag. This is in contrast to the early 2000’s when, following the tech wreck, factor returns were notably marked by strong value outperformance and big losses for momentum. Moreover, a winning factor one year can quickly become a loser the next. Take momentum, for example. In 2017 it gained more than quality, size, value and low volatility, but in 2016, it trailed the performance of all four of these factors. Value, meanwhile, did just the opposite—underperforming all but low volatility in 2015 while outperforming every factor except size in 2016.

The diversification benefits of these particular style factors are also related to their unique correlations to one another, as well as the overall market. Historically, momentum and value, have proven to be negatively correlated to each other, but both have low correlations to quality. Size, meanwhile, tends to be positively correlated to the overall market, while low volatility exhibits the opposite relationship with it.

Building a multi-factor strategy at the individual stock level

To combine these factors and realize the full potential of their interplay, many investors will allocate their holdings to a number of single-factor strategies or funds. This might be as simple as buying a value fund and combining it with a momentum fund, or it could be more involved to include the purchase of several funds that each own stocks primarily defined by a particular factor.

This approach may provide some level of exposure to a predetermined set of desired factors however this may not be the case if the factors being combined have negative correlations to one another. Consider an investor who owns both value and momentum funds. They may actually find their intended factor exposures have been reduced or cancelled out.

Trading places: Factor returns since 2009

Combining factors the right way

Source: MSCI as of December 31st, 2019. MSCI index methodology resources available at MSCI World Momentum Index denoted as Momentum; MSCI World Equal Weighted denoted as Size; MSCI World Enhanced Value Index denoted as Value; MSCI World Sector Neutral Quality Index denoted as Quality; MSCI World Minimum Volatility Index denoted as Volatility. Index returns are for illustrative purposes. Index performance returns do not reflect management fees, transaction costs or expenses. For illustrative purposes only, one cannot invest directly in an index.

There is also little recognition when combining single-factor strategies to the fact that individual stocks will generally provide exposure to more than just one factor so are therefore represented in multiple single-factor strategies.

This could result in an over-concentration to a particular security, sector or geography. A stock with value characteristics, for instance, may also be a quality stock, or be characterized by its size thus resulting in exposure to this security across multiple single-factor strategies.

As well, these attributes are constantly changing over time. By not accounting for this, investors run the risk of being more exposed to one or more factors than intended and may potentially undermine the benefit of combining them in a portfolio in the first place, leading to significant unintended risks. A better multi-factor approach, therefore, is to build a portfolio using quantitative analysis that starts at the individual security level.

This provides the opportunity to select from a larger universe of stocks versus just a few single-factor portfolios and considers the combined outcome of blending individual stocks with differing attributes to ensure alignment with the desired factors while minimizing unintended exposures.

An important step in this process is the development of a forecasting model that ranks performance of each stock in a chosen universe from most attractive to least attractive on a multifactor scorecard.

Such a model can be customized to take into consideration the specific exposures being sought, incorporating various controls and constraints such as security, sector and geographic weights to target the intended sources and magnitude of risk in the portfolio.

Lastly the process needs to be implemented efficiently and constantly monitored and rebalanced as necessary to ensure the desired exposures are still being achieved regardless of the changing market environment. Building a multi-factor portfolio in this way requires a high level of expertise, resourcing and oversight, not commonly found in many of the inefficient approaches such as those that combine single factor strategies. Without proper implementation throughout the process, the expected outcomes can be reduced or even eliminated.

Done right, a multi-factor approach built from the stock level can help target desired factor exposures with far more precision, leading to greater accuracy and flexibility and better outcomes for investors.

Mark Stacey is Co-CIO AGFiQ Quantitative Investing and Head of AGFiQ Portfolio Management, AGF Investments Inc. He is a regular contributor to the Insights and a member of the Highstreet Pooled Funds Investment Team.

The views expressed in this article are those of the author(s) and do not necessarily represent the opinions of Highstreet, AGF Investments Inc, or any of its affiliated companies, products or investment strategies.

The commentaries contained herein are provided as a general source of information based on information available as of July 7, 2020 and should not be considered as investment advice or an offer or solicitations to buy and/or sell securities. Every effort has been made to ensure accuracy in these commentaries at the time of publication, however, accuracy cannot be guaranteed. Investors are expected to obtain professional investment advice.

Source: MSCI. The MSCI information may only be used for your internal use, may not be reproduced or redisseminated in any form and may not be used as a basis for, or a component, of any financial instruments or products or indices. None of the MSCI information is intended to constitute investment advice or a recommendation to make (or refrain from making) any kind of investment decision and may not be relied on as such. Historical data and analysis should not be taken as an indication or guarantee of any future performance analysis, forecast or prediction. The MSCI information is provided on an "as is" basis and the user of this information assumes the entire risk of any use made of this information. MSCI, each of its affiliates and each other person involved in or related to compiling, computing or creating any MSCI information (collectively, the "MSCI Parties") expressly disclaims all warranties (including, without limitation, any warranties of originality, accuracy, completeness, timeliness, non-infringement, merchantability and fitness for a particular purpose) with respect to this information. Without limiting any of the foregoing, in no event shall any MSCI Party have any liability for any direct, indirect, special, incidental, punitive, consequential (including, without limitation, lost profits) or any other damages. (

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