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Achieving your investment goals with factors: Reduce risk

Achieving your investment goals with factors: Reduce risk

25-04-2018 | Insight

Factor-based strategies can help reduce potential downside risk. First article of a series on how factors can help investors achieve specific goals.

Speed read

  • Risk reduction has become a major investment theme
  • One way to achieve this is to adopt a low volatility strategy
  • Some low volatility strategies are better than others

The context

In recent years, risk reduction has become a top priority for many investors. Successive market wobbles in the 2000s raised awareness about the need to preserve capital in down markets, to ensure long-term outperformance and wealth accumulation. In order to achieve such risk reduction, numerous investors have turned to low-volatility products.

Virtually unknown less than a decade ago, low-volatility investing has now become a popular approach. In fact, a FTSE Russell survey of asset owners, carried out in 2017, found that downside risk reduction ranked first among the top investment goals triggering the evaluation of factor-based strategies.

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Scientific grounding

The low-volatility factor refers to the empirical finding that securities that generate relatively stable returns compared to the broader market, have achieved higher risk-adjusted returns over the longer term (see Figure 1). As a result, investing in low-risk stocks tends to generate higher Sharpe ratios in the long term.

This effect was first documented by various academics1, who tested the capital asset pricing model (CAPM) in the early 1970s. For example, in a long-term study of the US market, Robert Haugen and James Heins demonstrated that contrary to what is expected by CAPM, low-beta stocks in the United States outperformed high-beta stocks in the period 1929-1971. However, these discoveries remained widely ignored by the investment community for decades.

Figure 1: Cumulative performance of low/high volatility stocks in the US, 1929-2014*

Further research confirmed this ‘low-beta effect’ for other equity markets and Robeco researchers2 documented a similar effect: low-volatility stocks generate higher risk-adjusted returns. Additional academic studies demonstrated that the volatility effect is growing stronger in the European, Japanese and Emerging equity markets.

Many reasons have been brought forward by academics to explain this anomaly and why it should persist in the future. Among the most frequently mentioned explanations is the fact that focusing on low-risk stocks leads to high tracking error, which is unattractive for portfolio managers of outsourced investment mandates with strict limits on the maximum deviation from a capitalization-weighted index. Another frequently mentioned explanation is the fact that retail investors often buy stocks in the same way as 'lottery tickets', preferring the sexy stocks that are getting attention in the news.

Additional considerations

Following the success of low-risk strategies launched by several active managers, many index providers and passive managers have also jumped on the bandwagon by introducing low-volatility indices and ETFs. Various terms are used to describe these products, ranging from minimum volatility to managed volatility or minimum variance. Ultimately, all of these approaches seek to exploit the low-volatility anomaly, in one way or another.

Not all low-volatility strategies look alike, though, and some have proven to harvest factors more efficiently than others. For example, many generic low-volatility strategies are based on a single backward-looking historical measure of risk, such as volatility or beta. This construction may expose the strategy to some pitfalls, such as miscalculated downside risk.

Another common pitfall of generic low volatility strategies is that they often do not take into account valuation or price momentum aspects. Indeed, buying stocks solely on the basis of their past volatility or beta can lead investors to buy securities that are overvalued or penalized by an unfavorable trend in price, which could be a drag on the performance.

1F. Black, M. Jensen and M. Scholes (1972), “The Capital Asset Pricing Model: Some Empirical Tests”, Studies in the Theory of Capital Markets. E. Fama and J. MacBeth (1973), “Risk, Return, and Equilibrium: Empirical Tests“, Journal of Political Economy. R. Haugen, and J. Heins (1975), “Risk and the Rate of Return on Financial Assets: Some Old Wine in New Bottles”, Journal of Financial and Quantitative Analysis.
2D. Blitz and P. van Vliet (2007), The Volatility Effect: Lower Risk Without Return, Journal of Portfolio Management, pp. 102-113. Winner of Citation of Excellence Award from Emerald Publishing (2008).

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