Defensive ETFs: Too Good to Be True?

Defensive strategies, like those followed by low-volatility ETFs, can produce better risk-adjusted returns while smoothing out the highs and lows of the market

Alex Bryan 18 May, 2016 | 11:15AM
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Low-volatility strategies offer defensive exposure to the stock market, attempting to give investors a smoother ride with better performance during market downturns. In exchange, they tend to lag during strong rallies. That's an attractive trade-off for risk-averse investors. There are other ways to reduce risk, such as allocating a larger portion of a portfolio to cash or bonds and less to stocks. But low-volatility stocks will likely offer a better risk/reward trade-off than the broad stock market or a stock/bond portfolio of comparable volatility.

There should be a positive relationship between risk and return. Why else would investors bear the extra risk? 

Intuitively, there should be a positive relationship between risk – the type that can't be diversified away, and return. Why else would investors bear the extra risk? And in fact this relationship generally holds up across asset classes: Lower-risk assets, such as investment-grade bonds, tend to offer lower returns than higher-risk assets like stocks.

But Low Volatility Stocks Buck the Trend

But among stocks, the relationship between risk, defined by market sensitivity – beta – or volatility, and return isn't as strong as theory predicts it should be. In other words, low-risk stocks have historically offered better risk-adjusted performance than their riskier counterparts.

Much of this attractive performance can be attributed to defensive strategies' historical bias toward stocks with low valuations and high profitability, two characteristics that have been associated with higher returns. But because these strategies do not explicitly target stocks with these characteristics, their exposure to them, and thus their return profile, may change over time.

This is one of the strongest criticisms of low-volatility investing. Following this line of reasoning, Dimensional Fund Advisors and Professor Robert Novy-Marx argue that it is better to allocate a portion of a portfolio to bonds to reduce volatility and explicitly target stocks with low valuations, the focus of DFA's argument) and high profitability to boost returns.

To illustrate the impact of these style tilts on performance, consider the S&P 500 Low Volatility Index. This index targets the least-volatile 100 members of the S&P 500 and weights its holdings by the inverse of their volatilities so that the least-volatile stock receives the largest weighting in the portfolio. From its inception at the end of November 1990 through February 2016, the index's value and profitability tilts contributed about 71 and 95 basis points, respectively, to its annual return.

The index's exposure to these factors has changed over time, as the chart below illustrates. It shows the index's exposure to value and highly profitable stocks in a rolling three-year regression that includes these factors together with size, momentum, and the market risk premium. This lends some credence to the criticism that the index may not offer a consistent performance profile.

How low volatility stocks perform

Yet, during the full period, the index had a residual annualized return (or alpha) of 1.27 percentage points that the model could not explain. This result was not statistically significant, meaning that the extra return could have been attributable to chance. But it's still economically meaningful and difficult to replicate.

Why Do Low Volatility Stocks Deliver?

There is probably more to the low-volatility story than a simple bias toward value or highly profitable stocks. Andrea Frazzini and Lasse Pedersen, two principals from AQR, published a paper called "Betting Against Beta," in which they constructed a market-neutral factor that went long low-beta stocks and short high-beta stocks. This factor had a statistically significant positive return, alpha, after controlling for its value, size, profitability, and market risk exposures.

Frazzini and Pedersen persuasively argue that borrowing constraints help explain defensive stocks' attractive risk-adjusted performance. These stocks tend to lag during bull markets and may offer slightly lower expected returns than the market over the long run. Therefore, they may not be appealing to investors who are trying to beat a benchmark, like most active managers, especially because many are unwilling or unable to borrow to boost these stocks' returns (a prudent course for most.

That may push the prices of low-volatility stocks down, allowing them to offer more-attractive returns relative to their risk. Less-constrained investors, such as private equity funds, should prefer the more favourable risk/reward trade-off that less-volatile investments offer and apply leverage to boost returns. That is, in fact, the pattern Frazzini and Pedersen find.

Because many investors face borrowing constraints, there is a good chance that low-volatility stocks will continue to offer better risk-adjusted returns than the market. But investors shouldn't expect market-beating returns, even if low-volatility stocks have provided that in the recent past. These strategies will likely underperform in strong market rallies, outperform during market downturns, and offer market-like returns, or slightly less, over the long term.

 

The information contained within is for educational and informational purposes ONLY. It is not intended nor should it be considered an invitation or inducement to buy or sell a security or securities noted within nor should it be viewed as a communication intended to persuade or incite you to buy or sell security or securities noted within. Any commentary provided is the opinion of the author and should not be considered a personalised recommendation. The information contained within should not be a person's sole basis for making an investment decision. Please contact your financial professional before making an investment decision.

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Alex Bryan  is an ETF analyst with Morningstar.

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