There are many styles of pizza—New York thin crust, Chicago deep dish and even California style that incorporates non-traditional toppings. Each style offers pros and cons, and most people have a favorite (and can get vocal about it). We would argue that multi-factor investing is a little like pizza. There are different ways to construct multi-factor portfolios, and each approach has its advantages and considerations. We believe that an approach that offers adaptability to the current environment, however, can deliver distinct advantages to investors.
Taking a step back, we’ve described in earlier blogs how factor investing takes advantage of long-term risk premia that exist across the market. We've also addressed the behavioral and risk-based reasons that help explain the ability of factors to deliver enhanced risk-adjusted returns over the long term.
While all established factors tend to outperform their corresponding market-capitalization-weighted indices over the long run, their performance can be variable over shorter time periods. Fortunately, because of their performance differentials, factors exhibit low to modest correlations to each other. As a result, investors can combine them in a portfolio to harness the power of diversification to mitigate volatility. Investors concerned about short-term volatility may want to consider buying and holding more than one single-factor strategy or looking to multi-factor strategies that are designed to help mitigate the variability of returns.
Multi-factor strategies combine two or more factors in a single portfolio and typically serve as a core equity holding. They can be beneficial because the process seeks to identify stocks that are favorable across multiple factors. In principle, these strategies share many similarities with actively managed quantitative strategies, but rely entirely on a rules-based process without the discretion that an active strategy may employ.
3 Ways to Construct Multi-Factor Strategies
There is a wide variety of factor combinations available, but there tend to be two ways to construct multi-factor strategies: top-down and bottom-up (Exhibit 1). Each approach has pros and cons related to the flexibility of portfolio construction, robustness of exposures, portfolio turnover, ease of attribution and risk-adjusted performance potential. Note that both approaches can utilize optimization techniques to construct the portfolio.
Generally, a top-down approach combines single factor strategies by first ranking securities at the single factor level and then weighting the portfolio’s exposure to each factor. For example, in a two factor strategy, one might create a volatility portfolio and a value portfolio, and then weight the exposure to each portfolio equally. While this approach certainly provides exposure to both factors, it does so bluntly, without addressing whether underlying securities are exposed to multiple factors at the same time.
A bottom-up approach evaluates factor exposures at the security level. In the case of a value-volatility strategy, the bottom-up approach would look for the most attractive securities based on value and volatility at the same time. This enables the portfolio construction process to account for the interactions the rankings have with one another. While this adds complexity to factor investing, the benefits may outweigh any drawbacks. Consider a situation in which one security is leaving the volatility portfolio while, at the same time, it is being added to the value portfolio. A top-down approach would initiate trades to account for these changes, but it would be unnecessary in a bottom-up approach that takes a more holistic view of holdings.
The Missing Link: Adaptability
The majority of multi-factor strategies naively combine factors based solely on the fact that they exhibit low correlations to one another. This certainly makes sense from a diversification point of view, but it does little more than that. The FTSE OFI Dynamic Multifactor Index Series looks deeper to understand and adjust factor exposures based on the current market and economic environment. Considering that the economy and markets are not static, these indices are adaptive and emphasize certain factors depending on the regime. The series leverages models that OppenheimerFunds has developed over many years of managing global multi-asset-class portfolios. The model incorporates information derived from leading economic indicators and current market sentiment (Exhibit 2) to classify regimes into four phases: slowdown, contraction, recovery and expansion. The model’s output signals what factors will be present in the index, and at what weight (Exhibit 3).
The FTSE OFI Dynamic Multifactor Index Series also incorporates a unique bottom-up methodology pioneered by FTSE Russell to select securities for inclusion in portfolios. This approach employs a means to amplify factor exposure as opposed to simply averaging them together, which helps to ensure that factor exposure is not diluted when it is most needed.
In short, investors—like consumers of pizza—have a lot of choices when it comes to factor investing, especially with multi-factor strategies. Yet, while the perfect pizza style—New York thin crust—has existed since the early 1900s, multi-factor portfolios are still relatively new and have, until now, simply harnessed the power of factors in a diversified way. With the introduction of the FTSE OFI Dynamic Multifactor Index Series, however, we believe that investors can access a multi-factor portfolio that goes beyond diversification and adapts to the economy and markets as they evolve, which means greater peace of mind for investors.
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OppenheimerFunds is not undertaking to provide impartial investment advice or to provide advice in a fiduciary capacity.
An investment in the Fund is subject to investment risk, including the possible loss of principal amount invested. The Fund, seeks to provide exposure to investments based on the following factors: value, momentum, quality, low volatility and size, and to weight such factors based on changes in the economic cycle. There can be no assurance that doing so will enhance the Fund’s performance over time. Investing significantly in a particular region, industry, sector or issuer may increase volatility and risk. Fund returns may not match the return of its respective index, known as non-correlation risk, due to operating expenses incurred by the Fund. Because the Fund is rebalanced quarterly, portfolio turnover may exceed 100%. The greater the portfolio turnover, the greater the transaction costs, which could have an adverse effect on Fund performance.
These views represent the opinions of OppenheimerFunds, Inc. and are not intended as investment advice or to predict or depict the performance of any investment. These views are as of the publication date, and are subject to change based on subsequent developments.