Combine factors the right way

By: Mark Stacey & Bill DeRoche • October 10, 2018

Multi-factor portfolios that are built starting at the individual stock level can help target desired exposures more precisely and lead to better outcomes.

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, quality and low volatility have been fairly consistent factor leaders over the past several years, while value and size 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 2015, it gained more than quality, size and value, but in 2016, it trailed the performance of all three of these factors. Value, meanwhile, did just the opposite – underperforming in 2015, while outperforming in 2016.

Although factors are anticipated to outperform over the longer term, there will be periods when they move in or out of favour.

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 2008

Differential of average 12-month return of stocks in the top and bottom quintiles of MSCI ACWI ordered by the respective factor values at the beginning of each year.

Source: AGFiQ, FactSetFactors used (respective factor group’s shown above): Price to Book Ratio (Value), Market Capitalization (Size), 300 Day Volatility (Volatility), Return on Equity (Quality), 12-month Price Change (Momentum)

A better multi-factor approach is to build a portfolio using quantitative analysis that starts at the individual security level.

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.

(1) Fundamentals of Efficient Factor Investing by Roger Clarke, Harinda de Silva, CFA, and Steven Thorley, CFA. Financial Analysts Journal, Volume 72 – Number 6; 2016 CFA Institute.

AGFiQ ETFs are ETFs offered by AGF Investments Inc. and managed by Highstreet Asset Management. AGFiQ ETFs are listed on the Toronto Stock Exchange and may only be bought and sold through licensed dealers.

Commentaries contained herein are provided as a general source of information based on information available as of September 25 2018 and should not be considered as personal investment advice or an offer or solicitation 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. Market conditions may change and the manager accepts no responsibility for individual investment decisions arising from the use of or reliance on the information contained herein. Investors are expected to obtain professional investment advice.

AGFiQ Asset Management (AGFiQ) is a collaboration of investment professionals from Highstreet Asset Management Inc. (HSAM), a Canadian registered portfolio manager, and of FFCM, LLC (FFCM), a U.S. registered adviser. This collaboration makes up the quantitative investment team.

Publication date: October 10, 2018