Investment Product Review


In this series we examine investment products and strategies, from the mundane to the highly complex, explaining how they work and why we do or do not use these particular products or strategies in our portfolios.

Evaluating Low Volatility Funds

A recent trend in the growing category of low cost index fund investing is the creation of “low volatility” funds. These, as you might guess from their title, are funds that are intended to track a sector or asset class while exhibiting lower volatility than the standard indices in that asset class.  These funds, generally available in the ETF space, have been extremely popular among investors understandably wearied by the market swings of the past decade. However, are these funds really as advertised?  This investment product review will examine low volatility index funds and assess the costs and benefits including this type of fund in a diversified portfolio.

Low Volatility Funds

Before evaluating low volatility funds, it is important to understand how the indices they track are constructed.  Generally, the strategy is to take a broad index (e.g., the S&P 500) and select a set of stocks (perhaps 100 or 250) that have exhibited the lowest price volatility over the previous twelve months1.  This smaller set of equities would be assumed to represent the least volatile assets in the index, and could be called the S&P 100 Low Volatility index.  This method may have lower volatility than the S&P 500 as a whole, but it is no guarantee, and there are several flaws inherent in this approach.

1. Past volatility is not a perfect measure of future volatility

Most investors are familiar with the disclosure “Past performance is no guarantee of future results,” and the same is true for asset volatility.  Just because an asset exhibited relatively stable pricing over the previous year does not mean that this must hold going forward.  This is especially true if the reduced volatility had more to do with the sector of the equity than the specific underlying company itself. The next potential flaw expands on the relevance of the sector in evaluating future volatility.

2. Picking stocks based on past volatility can lead to a reduction of diversification

A reason that a particular group of stocks had relatively low trailing volatility could be due to a period of stability in a certain sector of the economy, making all companies in that sector appear to be less risky.  This would not be a problem if there were a guarantee going forward that particular sectors would remain approximately as stable or as risky as they have been recently. Clearly there is no such guarantee, and as a result of recent sector stability, these funds may suffer from higher levels of sector concentration.  For example, consider two iShares funds; the Core MSCI Emerging Markets ETF (IEMG) and the MSCI Emerging Markets Minimum Volatility ETF (EEMV).  Both funds are intended to provide the same asset class exposure (large capitalization emerging market equity), with EEMV experiencing less volatility.  However, looking into the sector breakdown reveals that EEMV has a higher weight to financial stocks (27.41% versus 24.43% for IEMG).  While this weighting might have resulted in lower price movement in the past year, and may continue to do so in the future, it is important to consider how these funds would each perform during a shock to the financial sector, such as the Financial Crisis of 2007-2009.  It is likely that the fund most exposed to financial stocks (EEMV) would end up being the more risky option of the two.

3. Not all volatility is bad

Volatility is a measure of price movement of an asset, but it is critical to remember that it is a two-sided metric.  This means that a stock that rapidly increases in price will exhibit a large amount of volatility, but one assumes that most investors would like that type of volatility in their portfolio.  By using a simple screen, these funds may very well exclude stocks of improving companies with strong future prospects as well as struggling companies.  As market price tends to steadily improve in the long run, it is more likely that rising stock prices will be the greater portion of an index than falling prices.  Also, equity prices tend to fall quickly and rise more gradually, so a simple volatility filter could include a firm with stable prices that will experience a steep drop in price, while the opposite is less likely (because sharp increases in stock prices are fairly uncommon).

4. Risk is the source of expected returns

Finally, investors must keep in mind the most basic principal of investing; investment returns are compensation for taking risk.  When you invest money, you are exposed to several types of risk, depending on the nature of the investment.  There is the risk that you will not be repaid (default risk, or possibly fraud), the risk that your asset will decrease in value (price risk), and the risk that you will not have access to the money at the moment you need it (liquidity risk) among others.  The riskier an investment, the higher its expected return.  In the context of low volatility funds, by removing the most volatile stocks you have also likely removed the stocks with the highest expected return.

Despite the four reasons listed above as to why these funds may not be optimal, they are by no means necessarily inferior investments.  They provide asset class exposure in a low cost indexed form, and will likely perform in a similar manner to the broad indices of which they are a subset.  In normal market conditions, they are likely to have slightly lower volatility than similar broad index funds, though at the same time they should be expected to have a somewhat lower return as well.  For investors who want asset class exposure and are willing to trade off some expected return for lower volatility, these funds might be a good alternative, as long as it is understood that the lower level of risk is a goal of the fund, not a guarantee.

1. It should be noted that not every fund uses this exact strategy, and each index provider will claim to have an optimal weighting procedure.

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About Erik Lehr

Erik graduated from the University of Oregon with a Bachelor of Economics and Mathematics degree. His background includes master’s degree in economics and a Master of Science in Computational Finance and Risk Management from the University of Washington. Erik also holds the Chartered Alternative Investment Analyst (CAIA®) designation.

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