3 Reasons Why You Should Avoid Risky Stocks

You’ll find a wide assortment of explanations for this counterintuitive relationship, or so-called low volatility anomaly, but they all seem to fit into one of three groups: investor preferences, factors, and mathematical. The degree to which you embrace one justification over another might dictate your approach (or combination of approaches) to defensive equity allocations.

However, it’s important to keep in mind that all viewpoints are not created equal. Some views may be internally inconsistent, while others may not be useful because they are not scientific – they can’t be disproven or used to make reliable predictions.

Investor Preferences Explanations

Some explanations center on an asserted mispricing of risk: high-volatility stocks produce inferior returns because they are overpriced relative to their fundamentals. Many believe investors have an irrational preference for high-risk stocks because of their lottery-like payoffs. This preference supposedly creates mispricing by driving up high-risk stocks, making them overvalued and more likely to disappoint, while leaving low risk stocks undervalued.

Others have noted that constraints on professional managers might also contribute to mispricing. Black (1972) suggested the theory of leverage aversion. Many institutional managers have leverage constraints; therefore, buying higher-risk stocks is their only means for taking on more risk. Baker (2011) believes there is a limit to arbitraging this mispricing. Institutional investors are typically benchmarked to cap-weighted indexes, which makes them reluctant to exploit the underpricing of low-volatility stocks. Why? Benchmarking shifts the focus from the risk of losing money (standard deviation) to the risk of underperforming (tracking error). Portfolio volatility is largely ignored when taking active bets, leading to overvaluation and possible disappointment.

Factor Explanations

Another approach to understanding defensive equity performance has been to either explain it away in terms of factors, or consider it a factor in its own right. For example, Novy-Marx (2014) claimed that the poor returns for high-volatility or high-beta stocks are driven by small, unprofitable growth companies with high valuations; he further argued that defensive equity strategies avoid these stocks, concluding that size, relative valuations and profitability explain defensive equity performance. Fama and French (2016) also found that their five-factor model (2015), which added profitability and investment factors to their original three- factor model, appears to explain returns on beta-sorted portfolios.

Mathematical Explanations

Most of the mystery surrounding the performance of defensive equity disappears when it’s seen as simply trying to identify and avoid uncompensated risk. Mathematically, this can be accomplished at the security and portfolio level.

It’s well understood that stock volatility can be a drag to long-term performance: larger negative fluctuations below a stock’s average arithmetic return require higher positive fluctuations to breakeven. This effect increases dramatically with increasing volatility. A stock with a negative return of 5% requires a positive return of 5.3% to break even; a negative return of 50% requires a 100% positive return. This can explain the results in Figure 1. It implies that avoiding the highest-volatility names in a large-cap index improves long-term portfolio performance.

 

Avoiding uncompensated risk at the portfolio level is also important. We know that a portfolio’s long-term return is not simply the long-term return of its constituents. Diversification and rebalancing play a role as well. Diversification reduces portfolio variance, and one half the difference between the weighted average stock variance and the portfolio variance offers an excess return potential arising from diversification that can be captured through rebalancing. This demonstrates that when the stocks do not all have identical expected returns – generally the case in the real world – minimizing the portfolio variance is not the optimal way to improve diversification: you have to take the individual stock variance into account as well.

Whether viewed through the stock- or portfolio-level lens, the mathematical effects of compounding, and the associated added return, are critical. For any two return series that have the same arithmetic average return, the one with lower variance provides a greater compound return (geometric average) over multiple periods. Over the long term, the more reliable way of preserving and growing capital is a steady compounding of returns: win more by losing less.

Learn More

Whichever way we understand the basis for defensive equity results, we have to concede that defensive equity investing is a captivating thesis. We invite you to learn more with a fresh look at defensive equity investing: How to Make Equity Allocations More Resilient.

 

The information expressed herein is subject to change based on market and other conditions. The views presented are for general informational purposes only and are not intended as investment advice, as an offer or solicitation of an offer to sell or buy, or as an endorsement, recommendation, or sponsorship of any company, security, advisory service, or fund nor do they purport to address the financial objectives or specific investment needs of any individual reader, investor, or organization. This information should not be used as the sole basis for investment decisions. All content is presented by the date(s) published or indicated only, and may be superseded by subsequent market events or other reasons. Past performance is no guarantee of future results. Investing involves risk, including possible loss of principal and fluctuation of value. Hypothetical performance results presented are for illustrative purposes only.