Fund flow data show a shifting trend toward multifactor indexes, which have already seen flows increase by 75% through the third quarter of 2016. Index funds are an efficient and transparent mechanism to access factors at a low cost, but buyer beware: Investors must be cautious not to fall into the trap of thinking all index funds are created equal.
Many investors associate passive indexing as a commodity product with the lowest cost index fund winning out, but investors must look closely at the construction and methodology of these indexes to ensure they align with the desired outcome. The object is not to make the case for active management, but to approach the selection of these indexes with the equivalent rigorous due diligence that traditionally is completed for active management.
Interest in single-factor indexes, such as value, can be credited to their historical outperformance relative to market-cap-weighted indexes. However, these factors go through distinctive cycles of out- and underperformance. Diversifying factor exposure, by combining multiple compensated factors together, can reduce the longevity and severity of drawdowns. For example, most value indexes have suffered multiyear drawdowns, underperforming market-capitalization-weighted benchmarks over the past decade, while most low-volatility indexes have outperformed. By merely combining value and low volatility factors, investors could have improved risk-adjusted returns.
This could very well be the basis for fund flow trends. Investors might be combining factors and strategies such as low volatility and quality with their existing value exposure or simply moving toward multifactor strategies in an attempt to improve risk-adjusted returns.
Although the benefits of combining factors in a transparent and low-cost index fund appear relatively straightforward and simple, the plethora of index choices can produce widely different outcomes. Whether you're picking a single-factor or multifactor index, you actually have a very active decision to make. Investors must understand the construction and methodologies in order to maximize the probability of achieving their objectives. Many of the indexes appear to be similar from afar, but after looking at the underlying details of these indexes, numerous differences emerge.
Looking across four commonly followed U.S. equity indexes in the multifactor category, we observe that the difference between the worst- and best-performing index is on average 6% over the last 10 years. For example, if your multifactor index didn't include the low-volatility factor, you experienced a much different result during both the financial crisis in 2008 and the subsequent reversion in 2009. Some index providers focus solely on combining factors to achieve the largest factor loadings, while others focus on both diversifying factors and weighting schemes to reduce stock-specific risks. Index providers also use different methodologies to combine factors. Certain providers use a top-down approach to combining factors, meaning they take single factor portfolios and simply add them together, while others employ bottom-up approaches in an attempt to find the few stocks that rank well across multiple factors. These methods can produce extremely different outcomes in terms of factor exposures and factor diversification; resulting in different risk profiles and returns.
Not only do index providers use different combinations of factors, but also they use different definitions for the same factors being targeted. While single-factor indexes often have similar names, they once again produce widely different results demonstrating that even the definitions of your factors matter. For example, there is wide consensus in value being a compensated factor exposure; however, there isn't broad consensus around the construction and methodology of value indexes. When looking at 16 different U.S. value indexes over the last 10 years, they appear to be very similar with a 97% correlation to each other. However, these indexes have a 15% difference between the top and bottom performing index, on average, in any given year. This is a wide margin with the highest performing value indexes actually outperforming market-cap-weighted indexes over the last 10 years. The different results over this time period are explained by additional portfolio biases that stem from the index methodology. Some more concentrated value indexes have larger sector biases and larger indirect factor exposures, such as a small size bias. By comparison, more diversified value indexes can perform better than more concentrated value indexes when value is out of favor, but can underperform concentrated value indexes when returns to value are strong. Not only should investors ensure that the index methodology aligns with their objectives, they also should scrutinize how these definitions have changed over time and if there is potential for them to change in the future.
The factors an investor uses, the definitions of the factors, weighting schemes, constraints and how the factors are combined are all critical elements for review. The construction and methodology of factor indexes have evolved fairly rapidly, creating an issue for analyzing the reliability of historical results. Many index providers have launched new factor indexes or changed their methodology, changing how they define the factors and how they combine them. The newest factor indexes tend to have the best hypothetical results bringing into question the reliability of the back tests. Investors should prudently evaluate the significance of the back-test and measure the reliability of the results to escape the trap of data-mining. Furthermore, investors need to consider how these strategies will perform in the “real world” and compare both in- and out-of-sample performance results. These indexes may also come with higher turnover and less liquidity relative to cap-weighted portfolios. Transaction cost constraints can be added to the index with little degradation of the risk and return profile of the index.
Lastly, it is also important to understand the index manager's knowledge of the methodology and experience implementing factor indexes to make sure they can successfully navigate any implementation challenges to ensure they do not erode expected returns.
Greg Behar is head of index strategy at Legal & General Investment Management America in Chicago. This content represents the views of the author. It was submitted and edited under P&I guidelines, but is not a product of P&I’s editorial team.