Koenig: Low-Vol Indexes Smoother Ride

Low-volatility indexes can make a lot of sense, but the devil’s really in the details.

As investors continue to seek ways to help manage volatility within their portfolios, indexes focused on low-volatility stocks have gained increasing interest in recent years. It makes sense to the extent that investing in funds that use such indexes make for a smoother ride.

Since the first exchange-traded fund focused on low-volatility stocks was launched in 2011, ETFs based on these indexes have seen total assets grow to about $11 billion as of Jan. 31, 2014, according to ETF.com.

These strategies allow investors to maintain equity market exposure while seeking to help manage some of the volatility within the equity portion of their portfolio.

As with any index strategy, however, it’s critical that investors understand the construction methodology of the underlying index, as the approach can vary significantly from one low-volatility index to another. Those differences, in turn, can result in significant differences in exposures and performance.

Can Lower Risk Generate Higher Return?

Part of the growing interest in low-volatility strategies is increasing awareness of the wide body of academic research focused on the so-called low-volatility anomaly. This research extends back to the 1970s with a paper by Robert Haugen and James Heins titled, “Risk and the Rate of Return on Financial Assets: Some Old Wine in New Bottles,” Journal of Financial and Quantitative Analysis, 1975.

More recent research includes papers by Malcolm Baker, Brendan Bradley and Jeffrey Wurgler, “Benchmarks as Limits to Arbitrage: Understanding the Low-Volatility Anomaly,” Financial Analysts Journal, 2011; and Jason Hsu, Hideaki Kudoh and Toru Yamada, “When Sell-Side Analysts Meet High-Volatility Stocks: An Alternative Explanation for the Low-Volatility Puzzle,” Journal of Investment Management, 2013.

This research has consistently found that low-volatility portfolios have outperformed high-volatility portfolios over the long term across various time periods and geographies. This is considered an anomaly, of course, because it runs counter to traditional financial theory, in which higher expected return goes hand in hand with higher risk.

Explanations for why this anomaly exists are less conclusive and remain the subject of considerable debate and ongoing research. Among the explanations are a behavioral tendency by many investors for so-called lottery stocks, or stocks with high volatility and seemingly high potential payoffs.

Other explanations include constraints on leverage that push some investors to prefer higher-beta stocks to meet expected return objectives; and tracking error constraints that cause some investors to view low-volatility portfolios as “risky” because they tend to exhibit moderate-to-high tracking error relative to a market-capitalization-weighted benchmark.

A Potentially Smoother Ride Over Time

While the research supporting the existence of the low-volatility anomaly over the long term is robust, performance among low-volatility indexes can vary significantly in shorter time periods and in various market environments.

Three index providers—Russell, MSCI and S&P—have introduced low-volatility indexes in recent years that have been used as the basis for ETFs from State Street Global Advisors, iShares and PowerShares.

Each of these indexes consists of a long-only subset of stocks from a parent index—such as the Russell 1000, S&P 500 or MSCI USA—that have historically exhibited low volatility. As performance may vary in different market environments, it’s important to note that the primary objective of these indexes is to deliver low volatility relative to the parent index rather than excess returns.

In terms of behavior in various market environments, research has shown that low-volatility indexes have historically tended to perform strongest relative to their cap-weighted parent index in relatively volatile market environments and during deep market declines.

In this type of environment, the low-volatility indexes have historically exhibited lower standard deviation of returns over time and smaller maximum drawdowns relative to their parent indexes. (See each index provider’s website for information on historical performance characteristics.)

By contrast, in periods of strong market advances, such as 2013, low-volatility indexes have historically tended to underperform their parent indexes, as would be expected. And in periods of positive but single-digit market returns, the low-volatility indexes have generally tended to keep up with their parent indexes, slightly outperforming or slightly underperforming in any single year.

By delivering a smoother ride over time and moderating some of the volatility drag and drawdowns in negative markets, the low-volatility indexes have historically generated returns similar to their parent indexes but with significantly lower volatility. As a result, they have historically generated improved risk-adjusted returns as measured by Sharpe ratio relative to their cap-weighted parent indexes, primarily due to the lower standard deviation of returns.

Differences In Index Construction

Each low-volatility index is built differently, so it’s important for investors to understand the construction methodology. While all approaches represent a valid way to gain exposure to low-volatility stocks, these differences in methodology can lead to meaningful differences in exposures and performance, particularly in the short term. (Again, see each index provider’s website for information on construction methodology.)

Among the crucial variables investors and advisors need to remember are the following:

• Parent index: Which parent index is used as the selection universe?
• Construction approach: Does the index use a simple sorting process or an optimization process?
• Factor exposures: Are exposures to nontargeted factors limited or unconstrained?
• Sector/industry exposures: Are the index’s sector exposures concentrated or diversified?
• Rebalancing: Is the index rebalanced monthly, quarterly or semiannually?
• Turnover: Does the index include constraints on turnover?

Investors need to understand whether the index is constructed using a simple sorting process or whether it uses an optimization process around a low-volatility factor that takes into account correlations and exposure to other risk factors.

Some of the indexes include limits on turnover and on how much exposure the index can have to other nontargeted risk factors such as momentum, size, etc. Each of the indexes also uses a different rebalancing schedule: monthly, quarterly and semiannually.

Other differences include sector and industry exposures, which can vary significantly from one index to another due to their methodology differences.

Some indexes might have relatively concentrated sector exposures, while others may be more diversified. For example, one of the common misperceptions about low-volatility indexes is that they simply have concentrated exposure to sectors such as utilities.

In fact, among the three U.S. large-cap low-volatility ETFs, the utilities exposure ranged from 7.9 percent to 23.8 percent as of Jan. 31, 2014, according to ETF.com. These differences have significant implications for potential sensitivity to influences on performance such as a rising-interest-rate environment.

One Tool To Help Manage Volatility

Low-volatility strategies are not a replacement for diversification across asset classes within the context of a global multi-asset portfolio. What these long-only index strategies provide is a way for investors to maintain equity market exposure while helping to manage some of the volatility within the equity portion of their portfolio.

In selecting from among the various low-volatility strategies that have been introduced in recent years, it’s critical that investors take the time to understand not only the historical risk/return characteristics of each low-volatility index, but also the details of the index methodology. By understanding construction differences, investors can help ensure they gain intended exposures while avoiding unintended exposures and potential surprises in performance.

David A. Koenig, CFA, FRM, is an index investment strategist with Russell Investments.