Category: Earnings & Dividends

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The Blue and Yellow Can | Eric Cinnamond

This excellent post from Eric Cinnamond at Palm Valley Capital sums up the challenges facing value investors in our post-QE world:

Last week my son and I went for a bike ride. Before departing, I noticed the chain on my bike was a little rusty, so I sprayed it with WD-40. My instinctive response can be traced back to my childhood and growing up in a WD-40 family. We put it on everything. In addition to our bikes, we sprayed it on window tracks, saws, locks, nuts and bolts, lawnmowers, and anything else that squeaked, rusted, or was stuck. If it was edible, we’d probably have put it on our pancakes!

When I became a small cap analyst in 1996, I was thrilled to learn WD-40 (symbol: WDFC) was a publicly traded company. In fact, it was one of the first stocks I followed and recommended. WD-40 is a classic high-quality small cap that possesses many of the attributes we seek…..

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Price-Earnings versus Growth

A comment at lunch today about high price-earnings multiples got me started on one of my favorite topics: investment returns.

Most of us use the basic price-earnings ratio (PE or P/E) as a rough measure of how highly priced a stock is. The higher the P/E, the higher the risk.

But P/E only focuses on current earnings and ignores future growth which can make a huge difference to the return on your investment.

The PEG ratio, popularized by Peter Lynch in One Up On Wall Street, attempts to address this deficiency by dividing the price-earnings ratio by expected long-term growth rate of earnings.

  • more than 1.0 is poor;
  • less than 1.0 is good;
  • less than 0.5 is excellent.

Comparing P/E to long-term growth is a step in the right direction but the PEG ratio has two notable deficiencies:

  • It ignores dividends; and
  • It assumes that the relationship between P/E and growth is linear.

Dividends

It is fairly obvious that two stocks trading on the same P/E, and with the same expected long-term growth rate, do not present the same value if one pays regular dividends and the other does not. PEG can be adjusted to compensate for this deficiency, by adding the dividend yield to the expected growth rate. If we assume Computershare (ASX:CPU), for example, has a long-term growth rate of 10%, this should be adjusted to 12% to include the expected 2% dividend yield.

P/E versus Growth

The relationship is not linear. Take a look at the graph below which compares P/E ratios on the vertical axis to Growth (including dividend yield) on the horizontal axis.

PE versus Growth

The gray line plots stock prices at a PEG ratio of 1. A P/E of 10 intersects with growth at 10%, a P/E of 20 with growth at 20%, etc.

The green line plots an internal rate of return at 12.5% p.a. on investment. Here is a brief explanation of my calculation:

I project earnings of $1 at varying growth rates for a period of 20 years. Then I discount this at 12.5% p.a. to arrive at a present value which equates to the P/E ratio (PV/$1 earnings in Year 1). I assume an exit value of zero for two reasons: (a) to simplify the model; and (b) to compensate for declining growth rates over time. I can give you ten different alternatives but this seems the most effective treatment (and I am trying to avoid this reading like a PhD thesis).

The relationship between P/E and expected growth rate is clearly exponential. If we require an annual return on investment (ROI) of 12.5% :

  • A growth rate of 15% would justify a P/E of 22; while
  • A growth rate of 30% would justify a P/E of 97.

What is clear is that price may be dictated more by high expected earnings growth than by current earnings.

How do we estimate long-term earnings growth? With difficulty.

But this is the most important factor in determining a stock’s value so we need to make our best effort. Factors to consider include:

  • Past revenue growth (earnings growth without corresponding revenue growth is difficult to sustain);
  • Cash flow to fund future growth
  • Market position
    • Market growth or market saturation
    • Market share
    • Ability to withstand competition (rising profit margins are often a good pointer)

Conclusion

The next time you look at a PE ratio, remember that earnings growth may be more important than current earnings.

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PEmax and why you should be wary of Robert Shiller’s CAPE

Robert Shiller’s groundbreaking works, Irrational Exuberance and Animal Spirits, led to a Nobel prize in 2013 but we need to be careful of placing too much reliance on his CAPE as an indicator of stock market value.

What is CAPE?

CAPE is the cyclically adjusted price-to-earnings ratio, normally applied to the S&P 500, to assess future performance of equities over the next decade. CAPE is calculated by dividing the S&P 500 index by a moving average of ten years of inflation-adjusted earnings. Higher CAPE values imply poor future returns, while low values signal strong future performance.

Economists John Y. Campbell and Robert Shiller in 1988 concluded that “a long moving average of real earnings helps to forecast future real dividends” which in turn are correlated with returns on stocks. Averaging inflation-adjusted earnings smooths out short-term volatility and medium-term business cycles in the economy and, they argued, was a better reflection of a firm’s long-term earning power.(Campbell & Shiller: Stock Prices, Earnings and Expected Dividends)

Shiller later popularized the 10-year version (CAPE) as a way to value the stock market.

S&P 500 CAPE

Strengths

CAPE correctly identifies that the S&P 500 was over-priced in the lead-up to Black Friday (October 1929) and ahead of the Dotcom bubble in 2000. It also correctly identifies that stocks were under-valued after the Depression of 1920-21, during the Great Depression of the 1930s, and during the 2008 Global Financial Crisis.

Weaknesses

Some CAPE readings are rather odd. The rally of 1936, in the midst of the Great Depression, shows stocks as overvalued. Black Monday, October 1987, which boasts the highest ever single-day percentage fall (22.6%) on the Dow, hardly features. Current CAPE values, close to 30, also appear exaggerated when compared to current earnings.

Causes

There are several reasons for these anomalies, two of which relate to the use of a simple moving average to smooth earnings.

The simple moving average (SMA) is calculated as the sum of earnings for 10 periods which is then divided by the number of periods, 10 in our case. While the SMA does a reasonably good job of smoothing it has some unfortunate tendencies.

First, the SMA tends to “bark twice. If unusually high or low data is recorded, the SMA will rise or fall accordingly, as it should. But the SMA will also flag unusual activity, in the opposite direction, 10 years later when the unusual data is dropped from the average.

Second, the SMA is fairly unresponsive. If earnings rise rapidly, the SMA will lag a long way behind current values.

The third anomaly relates to the use of a moving average of earnings to reflect future earnings potential. Companies may incur losses at the low-point in the business cycle, especially in a severe down-turn like 1929 or 2008, but the impact on future earnings capacity is marginal.

Take a simplistic example, where earnings are $1 per year for 9 years but a loss of $5 is incurred in the following year.  When the business cycle recovers, potential earnings are likely to be $1, not $0.50 (the 10-year SMA).

Examples

All of these flaws are evident in the CAPE chart above.

Problem 1

Expect a fall in CAPE next quarter (Q1 2019) when losses from Q4 2008 are dropped from the SMA period.

Problem 2

Earnings multiples in the lead-up to Black Friday (1929) and the DotCom bubble (2000) are both overstated because of the lag in the SMA caused by rapidly rising earnings.

Problem 3

Potential earnings in 1936 are understated because of the sharp fall in earnings during the Great Depression, resulting in an overstated earnings multiple. The same situation occurs 2009-2018 when losses from 2008 inflate CAPE values.

Proposed Solution

I tried a number of different moving averages in order to avoid the above anomalies but all, to some extent, presented the same problems.

Eventually, I tried dropping the moving average altogether, instead using the highest previous four consecutive quarter’s earnings to reflect future earnings potential. I call this PEmax © (price over maximum historic earnings). PEmax matches normal historic price-earnings ratio (PE) most of the time, when earnings are growing, but eliminates the distortion caused by sharp falls in earnings near the bottom of the business cycle.

S&P 500 PEmax

PEmax overcomes distortions associated with the 1936 bear market rally, Black Monday in 1987 and our current situation in 2018.

Compare how the two perform on a single chart below.

S&P 500 PEmax compared to CAPE

The spikes on Black Friday and the Dotcom bubble are more muted on PEmax but still warn that stocks are over-priced relative to future earnings potential. The 1936 bear market rally is restored to its proper perspective. As is the 1987 Black Monday spike, by removing the distortion caused by declining earnings in the early 90s. The same happens after the Dotcom bubble. And again in 2009 -2018.

Potential Uses

The historic average (1900 – 2018) for PEmax is 12.79. For what it’s worth, standard deviation is 5.32 but this is not a normal distribution.

S&P 500 PEmax distribution

The median (middle) value is slightly below the mean, at 12.23.

Visual inspection of the data suggests that low values are skewed towards the first half of the 20th century. The average over the last 50 years (1969-2018) is 15.85 but, again, this may be distorted by the Dotcom era.

Based on visual inspection, we suggest using a PEmax of 15.0 as the watershed:

  • PEmax greater than 15.0 indicates that stocks are over-priced; while
  • PEmax below 15.0 presents buying opportunities.

Potential Weaknesses

PEmax has one potential weakness. If S&P 500 earnings are ever exaggerated by an unusual event, to a level that is unlikely to be repeated, potential earnings will be overstated and PEmax understated. Fortunately, that is likely to be a rare occurrence, where earnings for the entire index spike above actual earnings capacity.

Conclusion

PEmax ©, an earnings multiple based on the highest previous four consecutive quarter’s earnings, is a useful comparison of price to future earnings potential. It eliminates many of the distortions traditionally associated with price-earnings multiples, including CAPE. High PEmax values (above 15) suggest poor future performance, while low PEmax values (below 15) correspond with greater investment opportunity.

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Yields rise but will stocks fall?

Yields on 10-year US Treasuries are again testing resistance at 3.0 percent. Breakout seems inevitable.

10-Year Treasury Yield

The long-term chart shows how breakout would complete a double bottom reversal, after a 3-decade-long secular bull market in bonds/down-trend in yields.

10-Year Treasury Yield - Quarterly

While most major stock market down-turns are caused by falling earnings expectations rather than revised earnings multiples, I do agree with Hamish Douglass that rising yields are likely to soften stock valuations.

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Price & Earnings: The Race to the Top

Now that 93% of S&P 500 stocks have reported first quarter earnings we can look at price-earnings valuation with a fair degree of confidence. My favorite is what I call PEMax, which compares Price to Maximum Annual Earnings for current and past years. This removes distortions caused by periods when earnings fall faster than price, by focusing on earnings potential rather than necessarily the most recent earnings performance.

PE of Maximum Earnings

Valuations are still high, but PEMax has pulled back to 22.78 from 24.16 in the last quarter. Valuations remain at their highest over the last 100 years at any time other than during the Dotcom bubble. Even during the 1929 Wall Street crash (Black Friday) and Black Monday of October 1987, PEMax was below 20.

While that warns us to be cautious, as valuations are high, it does not warn of an imminent down-turn. Markets react more to earnings than to prices as the chart below illustrates.

S&P 500 Earnings per Share Growth

The last two market down-turns were both precipitated by falling earnings — the blue columns on the above chart — rather than valuations.

While it is concerning that prices have run ahead of EPS — as they did during the late 1990s — consolidation over the past quarter should allow earnings room to catch up.

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Bob Doll: First quarter earnings continue to impress

Bob Doll

More positive news on earnings from Bob Doll’s weekly newsletter:

…..2. First quarter earnings results continue to impress, helped by tax cuts. With 85% of companies reporting, earnings are ahead of expectations by an average of 7.3%.1 Earnings-per-share growth is on track for 25%.1 Were it not for the effects of tax cuts, that number would be only 18%.1

3. Even if earnings are peaking, that does not necessarily mean the equity bull market is ending. According to one study, since the 1950s, a cyclical peak in earnings growth has tended to be followed by stock prices moving higher: From a peak in earnings-per-share growth, stock prices were still higher six months later 74% of the time and were higher 12 months later 68% of the time.2.

Fears of an earnings peak may be overblown, with inflation low, rate hikes at a measured pace, consumption strong and inflation contained despite low unemployment. Upside and downside risks appear balanced in this summary adapted by Nuveen from Morgan Stanley:

Reasons to be optimistic

1) First quarter earnings are very strong.
2) Equity valuations are reasonable.
3) Corporate America is flush with cash.
4) U.S. growth momentum may be plateauing, but is not slowing.
5) Trade restrictions have not been as severe as feared.
6) Global monetary policy remains accommodative.
7) North Korea risks have eased.

Reasons to be cautious

1) Margin pressures could hurt future earnings.
2) Higher rates could represent a headwind for valuations.
3) Political risks may rise as the midterm elections approach.
4) Global growth may start to slow in the coming years.
5) Trade policy remains a long-term risk.
6) Investors may be too complacent about monetary tightening.
7) President Trump’s legal issues could escalate.

But it would be foolish to ignore either upside or downside risk. Adopting a balanced strategy may be the most sensible approach.

1Source: Credit Suisse.
2Source: BMO Capital Markets

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Bob Doll: First quarter corporate earnings highly impressive

Bob Doll

Bob Doll reports positive first quarter results so far in his weekly newsletter:

First quarter corporate earnings have been highly impressive. With approximately 20% of companies reporting, 81% have exceeded expectations by an average of 6.4%2. This compares to an average beat of 4.7% over the last three years, which underlies the strength of this quarter2. Much of the strength has come from reduced tax burdens: Earnings-per-share is on track to grow 23%, but would only be 16% were it not for the effects of lower taxes2.

Prices tend to follow earnings and a solid reporting season would likely see stocks posting new highs after the recent correction.

2 Data from Credit Suisse.

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Black Monday, October 1987

Cross-posted from Goldstocksforex.com:

What caused the Black Monday crash of 1987? Analysts are often unable to identify a single trigger or cause.

Sniper points to a sharp run-up in short-term interest rates in the 3 months prior to the crash.

3 Month Treasury Bill Rates

Valuations were also at extreme readings, with PEmax (price-earnings based on the highest earnings to-date) near 20, close to its Black Friday high from the crash of 1929.

S&P 500 PEmax 1919 - 1989

Often overlooked is the fact that the S&P 500 was testing resistance at its previous highs between 700 and 750 from the 1960s and 70s (chart from macrotrends).

S&P 500 1960 - 1990

A combination of these three factors may have been sufficient to tip the market into a dramatic reversal.

Are we facing a similar threat today?

Short-term rates are rising but at 40 basis points over the last 4 months, compared to 170 bp in 1987, there is not much cause for concern.

13-week T-Bill rates

PEmax, however, is now at a precipitous 26.8, second only to the Dotcom bubble of 1999/2000 and way above its October 1987 reading.

S&P 500 PEmax 1980 - 2017

While the index is in blue sky territory, with no resistance in sight, there is an important psychological barrier ahead at 3000.

S&P 500

Conclusion: This does not look like a repetition of 1987. But investors who ignore the extreme valuation warning may be surprised at how fast the market can reverse (as in 1987) from such extremes.

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PEMAX second highest peak in 100 years

I published a chart of PEMAX for the last 30 years on Saturday. PEMAX eliminates the distortion caused by cyclical earnings fluctuations, using the highest earnings to-date rather than current earnings. The idea being that cyclical declines in earnings reflect a fall in capacity utilization rather than a long-term drop in earnings potential.

Since then I have obtained long-term data dating back to 1900 for the S&P 500 and its predecessors, from multpl.com.

PEMAX for November 2017 is 24.34, suggesting that stocks are over-valued.

S&P 500 PEMAX

Outside of the Dotcom bubble, at 32.88, the current value is higher than at any other time in the past century. PEMAX at 24.34 is higher than the peak of 20.19 prior to the 1929 Black Tuesday crash, and higher than the 19.8 peak before Black Monday in 1987.

This does not mean that a crash is imminent but it does warn that investors are paying top-dollar for stocks. And at some point values are going to fall to the point that sanity is restored.

Robert Shiller’s CAPE ratio

Here is Robert Shiller’s CAPE ratio for comparison. CAPE attempts to eliminate distortion from cyclical earnings fluctuations by comparing current index values to the 10-year average of inflation-adjusted earnings.

Shiller CAPE 10 Ratio

While this works reasonably well most of the time, average earnings may be distorted by the severity of losses in the prior 10 years.

You are neither right nor wrong because the crowd disagrees with you. You are right because your data and reasoning are right.

~ Warren Buffett

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