Lower the Risk in Your ETF Portfolio

In the fourth part of our series on managing risk in your portfolio we look at how alternative strategies solve inherent flaws in market-cap-weighted indices

Gordon Rose, CIIA, CAIA, 7 March, 2014 | 12:27AM
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In part three of our risk management strategies series, we discussed the target-volatility approach; a strategy aiming for constant volatility. Today, we turn our attention to low beta strategies.

What is Beta?

Beta is a measure of volatility based on the degree to which a fund moves relative to a benchmark. A fund with a high beta experiences higher highs and lower lows and is considered riskier than a fund with low beta.

What is Smart Beta?

ETF providers love to call strategic beta strategies “smart beta“. Personally, I dislike this marketing term, as it implies that some strategies are smarter than the market. They are not; they just define the market’s beta slightly different.

The discussion about strategic beta in the wider active versus passive asset management debate is almost philosophical in nature. A market participant actively decides where the assumed “golden mean“ is and then uses a passive, quantitative strategy – i.e. an alternative beta – to express it. These strategies tend to be transparent, rule based approaches, where the index weighting usually differs from pure market capitalisation.

Strategies re-defining market beta - in particular those claiming to reduce risk - are becoming increasingly en vogue. But they are not a new concept. For example, the Guggenheim S&P 500® Equal Weight ETF (RSP) was launched in the US over ten years ago, while Research Affiliates has been offering fundamentally weighted indices since 2004.

The key selling point of alternative strategies is that they are able to solve some inherent flaws in market-cap-weighted indices. Equally weighted indices, for instance, are better diversified, as the weighting methodology prevents concentration risk in certain stocks and/or sectors. This helps to overcome one of the main criticisms of market-cap-weighted indices; namely that they tend to overweigh overvalued stocks; sometimes with very undesirable consequences. The aftermath of the TMT-bubble at the turn of the century is a perfect example of this flaw.

However, alternative strategies are not a flawless panacea. Indeed, many of these strategies are underpinned on statistical models feeding from historical data carefully selected to prime stocks that have performed well in the past. And therein lies the problem; for just because a stock outperformed in the past, it doesn’t mean it will outperform in the future. In fact, studies have shown that the back-tested performance of indices drops dramatically once they go live.

Other potential issues with alternative strategies include liquidity constraints; an increase in the overall portfolio risk courtesy of a higher allocation to small caps; and increased trading costs, and hence reduce real net returns, due to above-average turnover.

Does Low Beta Mean a High Return?

Low-beta strategies – a sub-group of alternative beta strategies - are a very simple approach to hedge a portfolio against tail-risks by including defensive (i.e. low beta stocks) stocks. Examples of low-beta stocks include those which tend to generate steady income irrespective of the current market cycle (e.g. healthcare and utilities companies).

By definition, the market beta is 1. To calculate the beta of a stock or index relative to a benchmark, the returns are regressed against each other. A stock with a beta of 0.5 participates 50% of the market move, both on the up and downside. Or put it differently, if the market moves by 10%, the stock would move by 5%. From that it intuitively follows that, stocks with a beta above 1 should be the most attractive option for yield-chasers and risk-takers alike. And yet, low-beta stocks can outperform high-beta ones.

One might get the impression that leverage would be needed to achieve outperformance with low-beta stocks. However, that is not necessarily true. Indeed, since high-beta stocks are usually the preferred choice for hunting outperformance, they usually trade at a premium. By contrast, due to comparatively lower demand, low-beta stocks usually trade at a discount. This generates pricing inefficiencies which investors could exploit.

The following table shows performance metrics for a selected group of stocks during the period between 1987 and 2011. It comes as little surprise that high-beta stocks experienced higher volatility than low-beta ones. However, contrary to the general perception, low-beta stocks actually outperformed high-beta ones. This goes to show that investors can reduce equity-risk without sacrificing the performance.

The outperformance of low-beta stocks was, however, not explained by better performance in bull markets. A quick look to the maximum drawdown figures reveals that outperformance was generated by avoiding the downside. Let’s look at a hypothetical example where we have two portfolios, each worth £1,000. Portfolio A invests only in global low-beta stocks while portfolio B allocates all the money into high-beta stocks. Taking the maximum drawdown during the period, the value of portfolio A would drop to £558, while that for portfolio B falls to £198. From that point, just to get level with the low-beta portfolio A, the high-beta portfolio B would have to increase by 280%. Followers of this article series might recall that we already discussed this phenomenon in the context of the risk-parity approach.

Consequently, it might make sense to invest in low-beta stocks or indices to reduce risk over the long-term. The key term to remember here is “long-term”, as this approach might underperform in bull markets over the short-term. In fact, we’d argue that investors should follow this strategy over the course of several market cycles in order to unlock its full potential. 

In the last part of our series, we will discuss the stop-loss strategy and analyse how alternative asset classes can be used to reduce overall portfolio risk.

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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About Author

Gordon Rose, CIIA, CAIA,

Gordon Rose, CIIA, CAIA,  is an ETF analyst with Morningstar Europe.

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