Why Moats Matter by Heather Brilliant & Elizabeth Collins

Author:Heather Brilliant & Elizabeth Collins
Language: eng
Format: epub
ISBN: 9781118760277
Publisher: Wiley
Published: 2014-06-18T00:00:00+00:00

Notes

1. For those familiar with the Morningstar Rating™ for funds, you can see that the Morningstar Rating™ for stocks differs in that our stock ratings reflect our prediction for future returns, while our fund ratings are based on historical performance compared to similar funds.

Chapter 7

Do Moat Ratings Predict Stock Returns?

Contributed by Warren Miller, head of quantitative research at Morningstar

Analyzing competitive strengths and weaknesses can undoubtedly help management teams make better strategic decisions, but can this type of research also help investors make better choices and achieve better outcomes? In other words, is it worth precious time to dive deep into the intricacies of the moat framework? In this chapter, we use some simple statistical analysis to examine what our moat ratings can tell us about stock returns. We launched these ratings in 2002, which gives us more than a decade’s worth of data to analyze. Of course, the following studies show how the moat ratings have performed in the past, and as always, there is no guarantee this performance will continue into the future.

Through our research, we’ve found that wide-moat stocks exhibit less downside risk and less upside potential. In times of market fear or distress, wide-moat stocks outperform no-moat stocks, but then underperform when risk aversion subsides. The evidence isn’t quite strong enough to claim that all wide-moat stocks generate excess risk-adjusted returns, but we do find that undervalued wide-moat stocks have done so. We think it’s safe to say, then, that the moat rating is a valuable risk-management and security-selection tool, especially when used in conjunction with valuation-based metrics.

The most direct way to look at the performance of moat ratings is to segment companies based on their moat ratings and examine the distribution of returns for each group subsequent to the date it received its moat rating.

Table 7.1 shows how stocks from each moat-rating group can be expected to perform over a one-month time horizon. Of course one month is very short to a long-term investor, but it’s useful to study returns on this horizon for two reasons. First, there is a direct mathematical relationship between short-term returns and long-term returns: Long-term returns are the geometric mean of the short-term returns that compose the same period. Here, we are averaging monthly returns over more than a decade, giving us many datapoints over varying market conditions. Second, it is reasonable to assume that even a long-term investor may revisit portfolio constitution at a monthly frequency given the fluctuations in expected returns that happen over periods as short as one month.

Table 7.1 Summary Statistics for Marginal Distributions of Future Monthly Returns by Moat Rating

Source: Morningstar.

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