Good old safe and reliable consumer staples—the sector that was down a stinking 10% for the rolling year ending May 15, 2018.
The same sector that has super boring companies that produce food, toilet paper, beverages, household cleaning products, etc.—the stuff that we “always need” and that is marketed with exorbitant advertising budgets.
What can a money manager possibly do to find value in such a lackluster, lagging sector in the current market? The answer is in the trailing returns and/or spread analysis of the consumer staples sector compared to the S&P 500 (used in this example as a broad-based representation for the overall stock market).
So, let’s go back in history almost 20 years. The S&P 500 was on an upward rocket trajectory from 1993 through 1998 but started to show signs of wearing down in 1999 and into 2000. From 1998 through part of 2000, the out-of-favor sector was consumer staples—denigrated as “brick and mortar,” “boring,” “it’s not tech,” and so on.
At the end of 1999, the trailing 52-week return for the consumer staples sector ETF, XLP, was -13.9% versus a 16.6% return for SPY. That is over a 30% gap between the broad index and the sector! As of May 15, 2018, the gap is more than 24%.
Many of us remember the giddiness of the markets (especially the NASDAQ) in the latter parts of 1999 and early 2000. The latter part of 2017 and early part of 2018 felt similar. The spread ratio of SPY/XLP has shown a bullish nod to SPY since February 2016 and currently has a value of 5.48 (calculated as the price of SPY divided by the price of XLP).
Historically (1999–2009), when the spread value fell below and/or whipsawed near a value of 5.0, the overall market was going to be very volatile and/or very sick. The all-time end-of-week high for the indicator is 8.03—ironically, at the all-time former S&P 500 high on March 24, 2000. The spread fell consistently to below 5.0 by Dec. 29, 2000, and erratically bounced abound between 5.0 and 5.5 until Aug. 17, 2001. It remained below 5.0 for almost the entirety of the period from Aug. 17, 2001, to April 11, 2003.
Between April 11, 2003, and Oct. 12, 2007, the spread crested above or near 6.0 three times before starting its descent to below 5.0 on July 25, 2008. All of these dates are important, as it gave a macro warning to overall market behavior and direction. In the current bull market, “4.0” has become “the new 5.0.” Since, April 3, 2009, cresting above 4.0 or below still warrants attention as a value-added addition to other indicators.
However, here is the other part of the SPY and XLP story that is very relevant through all market conditions since 1999: When the trailing 52-week return of the S&P 500 (SPY) has been greater than the XLP, it has indicated a strong overall market. When the opposite has occurred, it has been a very opportune time to retreat from the markets and sit in a money-market fund or the ETF SHY (iShares 1-3 Year Treasury Bond ETF).
With that simple formula, if one had bought and sold SPY since Dec. 31, 1999, using the trailing return indicator, one would have returned 206% versus the SPY buy-and-hold return of 159% (see Figure 1).
FIGURE 1: EQUITY CURVE OF SPY STRATEGY USING XLP INDICATOR VS. “BUY AND HOLD”
Source: Market data, kensingtonanalytics.com
But here is the kicker. The maximum drawdown in the total period using that indicator is -15.7% during a span of time when the S&P 500 fell -49.5% in the 2000–2002 bear market and -56.5% in the 2007–2009 bear market. Having similar returns to a buy-and-hold S&P 500 strategy with far lower drawdowns sounds pretty good to me. The standard deviation of the total period of 969 weeks (measured weekly) is 1.39% using the indicator, versus 2.42% for a buy-and-hold S&P 500 strategy.
The consumer staples sector is not only something that provides products essential to our modern daily lives, but it can also be our friend in market analysis.
The opinions expressed in this article are those of the author and do not necessarily represent the views of Proactive Advisor Magazine. These opinions are presented for educational purposes only.
Ian Naismith works in research and development for Kensington Analytics. Kensington Analytics specializes in powerful, data-driven, quantitative decision models that apply to the equity and fixed-income markets. Mr. Naismith has been analyzing and trading the markets since the early 1990s. He is a member of the National Association of Active Investment Managers (NAAIM) and has also served as board member and president. kensingtonanalytics.com
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