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The MarketGrader 100 Index Journal

January 7, 2019

Carlos DiezCarlos Diez

What Will Follow the Selloff?

The MarketGrader 100 Index (MGONE) closed what appeared to be another promising year with a dud. After rising 10% through the end of August, it promptly gave up its gains by the middle of October and then some. By the time the New Year rolled in, MGONE had lost 27% from the year’s high on August 29th, clocking a yearly decline of 14%, its worst showing since it fell 46% in 20081. Few companies were spared from the selloff, with 89 of the index’s constituents closing 2018 trading below their 200-day moving average, including 42 stocks that closed the year with their stock price at least 20% below their 200-day moving average. For the year, MGONE trailed the broad market, as measured by the Russell 3000 Index, by 730 basis points, as can be seen in Figure 1.

Figure 1. Price Returns for MG100 in 2018 Relative to Select Market Benchmarks

fig1-c

Source: Bloomberg

The year-end selloff was indiscriminate, leaving most asset classes in the red in 2018, and sparing only a handful of agricultural commodities (cocoa, wheat, corn), Brazilian and Indian stocks and, among U.S. stocks, only large cap health care companies and utilities. And in a classic sign of a collective flight to safety, the WSJ Dollar Index gained 4.29% on the year while the Japanese yen rose 2.84%2. Perhaps most remarkable was the precipitous 55-basis point drop in the 10-year U.S. Treasury yield from a November high of 3.24% down to 2.68% at year-end3, a level it had reached 11 months earlier before long-term rates began their steady climb on the back of solid U.S. economic figures.

What now?

History is the best guide we know of when trying to predict what comes next in financial markets. The simple (may would argue, simplistic) answer to what happens next is that the market, and MGONE, will rise following the selloff; it always has. We cannot predict, however, when the market will hit bottom (or whether it occurred already). We do know two things, though. What MGONE has done following large selloffs such as this one and what the companies in the index are worth today based on what they earn. So, let’s start with the index’s behavior following comparable selloffs, going back to 2007, which allows us to include, of course, the mother of all selloffs between October of that year and March 2009.

Since October 2007, MGONE has had six drawdowns we would call ‘significant,’ with three declines topping 20% and three between 10% and 20%, or, in market parlance, your garden variety ‘corrections.’ The biggest drop, from top to bottom, was, of course, the 2007-2009 decline, which lobbed off 60% of MGONE’s value. It was also the longest one, lasting 17 painful months. The second biggest decline lasted 10 months, starting in the spring of 2015 as China’s epic stock market bubble began to pop, followed by the government’s bungled attempt to stem the drop, including a poorly orchestrated currency devaluation in the summer. The misery, that time, came to an end in February 2016. This brings us to the current drawdown, which, at 27% through December 24th (bottom prior to the New Year), ranks third worst in the last 11 years. Figure 2 illustrates the magnitude and length of the index’s six significant declines since 2007.

Figure 2. Six Largest Drawdowns for MGONE Since October 2007.

Start End Drawdown Duration
Drawdown 1 10/10/07 3/9/09 -60.1% 17 months
Drawdown 2 4/15/15 2/11/16 -29.8% 10 months
Drawdown 3 8/29/18 12/24/18 -26.7% 4 months
Drawdown 4 3/26/12 6/1/12 -16.2% 2 months
Drawdown 5 7/3/14 10/13/14 -10.9% 3 months
Drawdown 6 9/14/12 11/14/12 -10.3% 2 months

Source: MarketGrader Research

With the exception of the current decline, we’re thus able to calculate MGONE’s one-year performance from the day it touched bottom for five of the six drawdowns. The index’s average one-year price return across all five periods: 42.6%. We’re also able to calculate three-year returns for four out of the six drawdowns and five-year returns for three out of the six drops. The average price returns after three and five years of hitting bottom, respectively, were 83.6% and 152.6%. Figures 3, 4 and 5 illustrate how MGONE’s returns compared to those of the S&P 500 after one, three and five years of hitting bottom4.

Figure 3.fig3Source: Bloomberg

Figure 4.

fig4-b

Source: Bloomberg

Figure 5.

fig5

Source: Bloomberg

A better comparison, in our view, is to the Russell 3000, which represents almost the entire opportunity set in U.S. equities. Figure 6 illustrates the its one, three and five-year performance following each one of MGONE’s last five drawdowns.

Figure 6.

1-Yr. Chg. from Bottom 3-Yr. Chg. from Bottom 5-Yr. Chg. from Bottom
Date of Bottom MG 100 Russell 3000 Diff. MG 100 Russell 3000 Diff. MG 100 Russell 3000 Diff.
March 3, 2009 89.3% 72.6% 16.7% 144.0% 108.9% 35.1% 252.2% 190.5% 61.6%
Feb. 11, 2016 30.6% 29.2% 1.4%
Dec. 24, 2018
June 1, 2012 34.9% 28.5% 6.4% 94.6% 67.2% 27.4% 102.2% 90.7% 11.5%
Oct. 13, 2014 11.4% 7.4% 4.0% 40.7% 36.7% 4.0%
Nov. 14, 2012 46.9% 34.0% 12.9% 55.3% 49.7% 5.5% 103.4% 90.7% 12.7%
Average 42.6% 34.3% 8.3% 83.6% 65.6% 18.0% 152.6% 124.0% 28.6%

Source: Bloomberg

Our second point of reference, as mentioned above, is how much investors would pay today for every dollar earned by MGONE companies, following a 27% decline in the value of the index. For context, it’s useful to revisit what investors were paying a year ago, at the end of 2017. At the time, the median price to earnings ratio of MGONE constituents, based on reported, trailing 12-month earnings per share was 22.1. Today that value has fallen by almost 40% to 13.4 times trailing earnings. The decline in forward earnings, or what this group of companies is expected to earn in the year ahead and how much investors are willing to pay for them today, is similar when doing the same year-over-year analysis. At the end of 2017, the index’s median forward P/E ratio was 19.3. Today, the value is 37% lower, at 12.1.

Another way to measure what an investor’s dollar buys in MGONE today is by measuring the index’s earnings yield, which is simply the inverse of the P/E ratio. It is useful in evaluating the investment opportunity when compared to other interest-yielding classes, especially now that bonds and even cash offer a modest return. Once again, our point of reference will be the end of 2017, when MGONE constituents traded at a median earnings yield of 4.8%, a 2.5% premium over the risk-free rate of return at the time, as measured by the yield on a 10-year Treasury note. Today, by contrast, MGONE constituents sport a median earnings yield of 6.1%, or 3.4% above 10-year Treasuries.

In summary, the simple conclusion is that while plenty of uncertainty around factors such as interest rates, trade policy and political acrimony still weighs on investors’ minds, they have been given an opportunity to own U.S. equities at much lower valuations than a year ago. And while we would advise they lean in cautiously, especially as we continue to venture into unchartered waters as the Fed continues to unwind its unprecedented easy money policies of the past decade, it is clear to us that good values have been once again created among U.S. companies. Yes, companies will have to compete once again with higher returns on cash and bonds. In that case, companies with high returns on invested capital, high returns on equity and solid, defensible margins should do better than the overall market; these are precisely the types of companies found in the MarketGrader 100 Index.


1 All returns cited in this column are price-only returns.
2 Year-End Review & Outlook of Markets & Finance, The Wall Street Journal, January 2, 2019.
3 Source: Bloomberg
4 The start and end dates of the drawdowns used in our analysis are based on MGONE’s peaks and troughs. In some cases the peaks and troughs for the benchmarks cited in the analysis vary from MGONE’s by a few days or weeks. However, we use MGONE’s dates in order to measure identical periods across all indexes. All returns from the index’s low off each bottom are based on price-only returns across all indexes.

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