Rally Back, Still Going Nowhere

April 21st, 2014
in contributors

X-factor Report 20 April 2014

by Lance Roberts, Streetalk Live

Despite the fact that we remain on a "sell" signal, and technically should be carrying a partially underweight position in equities, the markets have done nothing "wrong" at this point. As shown above, while the markets broke down last week raising some concerns it was quickly reversed as market participants bid stocks back up.

Follow up:

A large inflow of liquidity from the Federal Reserve, as shown in the chart below, was responsible for the sizable reversal last week.

If the markets can breakout above 1880 to new highs, and reverse the current sell signal in the next week, then the bull market trend will remain intact and we will allocate portfolios accordingly. However, as shown in the chart above, support for the Federal Reserve will fall rather sharply over the next couple of weeks creating a bit of void for the markets. Therefore, we will remain cautious for the moment and watch to see what unfolds.

A Correction Is Coming

Now, just because I am currently suggesting no change in allocations at the moment, does not mean that I am in the camp of "perma-bulls" whom never see the dangers of a correction. A correction is coming - I just don't know when and what will cause it.

However, as I stated this past week in our daily blog:

Every major market peak, and subsequent devastating mean reverting correction, has ever been the result of the exact ingredients seen previously. Only the ignorance of its existence has been a common theme.

As I discussed yesterday, the reason that investors ALWAYS fail to recognize the major turning points in the markets is because they allow emotional "greed" to keep them looking backward rather than forward.

Of course, the media foster's much of this "willful" blindness by dismissing, and chastising, opposing views generally until it is too late for their acknowledgement to be of any real use.

The next chart shows every major bubble and bust in the U.S. financial markets since 1871 (Source: Robert Shiller)

At the peak of each one of these markets, there was no one claiming that a crash was imminent. It was always the contrary with market pundits waging war against those nagging naysayers of the bullish mantra. Yet, in the end, it was something that was unexpected, unknown or simply dismissed that yanked the proverbial rug from beneath investors.

What will spark the next mean reverting event? No one knows for sure but the catalysts are present from:

  • Excess leverage,
  • IPO's of negligible companies,
  • Companies using cheap debt to complete stock buybacks and pay dividends, or
  • High levels of investor complacency.

Either individually, or in combination, these issues are all inert. Much like pouring gasoline on a pile of wood, the fire will not start without a proper catalyst. What we do know is that an event WILL occur, it is only a function of "when."

The discussion of why "this time is not like the last time" is largely irrelevant. Whatever gains that investors garner in the between now and the next correction by chasing the "bullish thesis" will be wiped away in a swift and brutal downdraft. Of course, this is the sad history of individual investors in the financial markets as they are always "told to buy" but never "when to sell."

For now, the "bullish case" remains alive and well. The media will go on berating those heretics who dare to point out the risks that prevail. However, the one simple truth is "this time is indeed different." When the crash ultimately comes the reasons will be different than they were in the past - only the outcome will remain same.

The Iron Law Of Valuation by John Hussman

The following is an excellent read to think about during your Easter holiday in regards to what future returns from stocks are likely to bring. Investor's expectations are extremely "out of whack" with what is very likely going to be a very disappointing decade ahead. John's analysis is extremely important in the understanding of this problem.

"The Iron Law of Valuation is that every security is a claim on an expected stream of future cash flows, and given that expected stream of future cash flows, the current price of the security moves opposite to theexpected future return on that security. Particularly at market peaks, investors seem to believe that regardless of the extent of the preceding advance, future returns remain entirely unaffected. The repeated eagerness of investors to extrapolate returns and ignore the Iron Law of Valuation has been the source of the deepest losses in history.

A corollary to the Iron Law of Valuation is that one can only reliably use a "price/X" multiple to value stocks if "X" is a sufficient statistic for the very long-term stream of cash flows that stocks are likely to deliver into the hands of investors for decades to come. Not just next year, not just 10 years from now, but as long as the security is likely to exist. Now, X doesn't have to be equal to those long-term cash flows - only proportional to them over time (every constant-growth rate valuation model relies on that quality). If X is a sufficient statistic for the stream of future cash flows, then the price/X ratio becomes informative about future returns. A good way to test a valuation measure is to check whether variations in the price/X multiple are closely related to actual subsequent returns in the security over a horizon of 7-10 years.

The Iron Law of Valuation is equally important in the stock market, as is the need for representative measures of future cash flows when investors consider questions about valuation.

It's striking how eager Wall Street analysts become - particularly in already elevated markets - to use current earnings as a sufficient statistic for long-term cash flows. They fall all over themselves to ignore the level of profit margins (which have always reverted in a cyclical fashion over the course of every economic cycle, including the two cycles in the past decade). They fall all over themselves to focus on price/earnings multiples alone, without considering whether those earnings are representative.

Yet they seem completely surprised when the market cycle is completed by a bear market that wipes out more than half of the preceding bull market gain (which is the standard, run-of-the-mill outcome). The latest iteration of this effort is the argument that stock market returns are not closely correlated with profit margins, so concerns about margins can be safely ignored. As it happens, it's true that margins aren't closely correlated with market returns. But to use this as an argument to ignore profit margins is to demonstrate that one has not thought clearly about the problem of valuation. To see this, suppose that someone tells you that the length of a rectangle is only weakly correlated with the area of a rectangle. A moment's thought should prompt you to respond, "of course not - you have to know the height as well." The fact is that length is not a good sufficient statistic, nor is height, but the product of the two is identical to the area in every case.

Similarly, suppose someone tells you that the size of a tire is only weakly correlated with the number of molecules of air inside. A moment's thought should make it clear that this statement is correct, but incomplete. Once you know both the size of the tire and the pressure, you know that the amount of air inside is proportional to the product of the two (Boyle's Law, and yes, we need to assume constant temperature and an ideal gas).

The same principle holds remarkably well for equities. What matters is both the multiple and the margin.

Wall Street - You want the truth? You can't handle the truth! The truth is that in the valuation of broad equity market indices, and in the estimation of probable future returns from those indices, revenues are a better sufficient statistic than year-to-year earnings (whether trailing, forward, or cyclically-adjusted). Don't misunderstand - what ultimately drives the value of stocks is the stream of cash that is actually delivered into the hands of investors over time, and that requires earnings. It's just that profit margins are so variable over the economic cycle, and so mean-reverting over time, that year-to-year earnings, however defined, are flawed sufficient statistics of the long-term stream of cash flows that determine the value of the stock market at the index level.

As an example of the interesting combinations that capture this truth, it can be shown that the 10-year total return of the S&P 500 can be reliably estimated by the log-values of two variables: the S&P 500 price/book ratio and the equity turnover ratio (revenue/book value). Why should these unpopular measures be reliable? Simple. Those two variables - together - capture the valuation metric that's actually relevant: price/revenue. If you hate math, just glide over any equation you see in what follows - it's helpful to show how things are derived, but it's not required to understand the key points.

  • price/revenue = (price/book)/(revenue/book)
  • Taking logarithms and rearranging a bit,
  • log(price/revenue) = log(price/book) + log(book/revenue)

If price/revenue is the relevant explanatory variable, we should find that in an unconstrained regression of S&P 500 returns on log(price/book) and log(book/revenue), the two explanatory variables will be assigned nearly the same regression coefficients, indicating that they can be joined without a loss of information. That, in fact, is exactly what we observe.

Similarly, when we look at trailing 12-month (TTM) earnings, the TTM profit margin and P/E ratio of the S&P 500 are all over the map. When profit margins contract, P/E ratios often soar. When profit margins widen, P/E ratios are suppressed. All of this introduces a terrible amount of useless noise in these indicators. As a result, TTM margins and P/E ratios are notoriously unreliable individually in explaining subsequent market returns. But use them together, and the estimated S&P 500 return has a 90% correlation with actual 10-year returns. Moreover, the two variables - again - come in with nearly identical regression coefficients. Why? Because they can be joined without a loss of information, that is, the individual components contain no additionalpredictive information on their own. Just like the area of a rectangle and Boyle's Law:

  • price/revenue = (earnings/revenue)*(price/earnings)
  • Again taking logarithms
  • log(price/revenue) = log(profit margin) + log(P/E ratio)

The chart below shows this general result across a variety of fundamentals. In each case, the fitted regression values have a greater than 90% correlation with actual subsequent 10-year S&P 500 total returns. Let's be clear here - I'm not a great fan of this sort of regression, strongly preferring models that have structure and explicit calculations (see for example the models presented in It is Informed Optimism to Wait for the Rain). The point is that one can't cry that "profit margins aren't correlated with subsequent returns" without thinking about the nature of the problem being addressed. The question is whether P/E multiples, or the Shiller cyclically-adjusted P/E, or the forward operating P/E, or price/book value, or market capitalization/corporate earnings, or a host of other possibilities can be used as sufficient statistics for stock market valuation. The answer is no.

What we find is that both margins and multiples matter, and they matter with nearly the same regression coefficients - all of which imply that revenue is a better sufficient statistic of the long-term stream of future index-level cash flows than a host of widely-followed measures. Emphatically, one should not use unadjusted valuation multiples without examining the relationship between the underlying fundamental and revenues. That is why we care so much about record profit margins here.

Note that in each of these regressions, the coefficients could place a low weight on profit margins and other measures that are connected with revenues, if doing so would improve the fit. They could place significantly different coefficients on margins and multiples, if doing so would improve the fit. They just don't, and like the area of a rectangle and Boyle's Law, this tells you that it is the product of the two measures that drives the relationship with subsequent market returns.

[Geek's Note: Gross value added (essentially revenue of U.S. corporations including domestic and foreign operations) is estimated as domestic financial and nonfinancial gross value added, plus foreign gross value added of U.S. corporations inferred by imputing a 10% profit margin to the difference between total U.S. corporate profits after tax and purely domestic profits. Varying the assumed foreign profit margin has verylittle impact on the overall results, but this exercise addresses the primary distinction (h/t Jesse Livermore) between normalizing CPATAX by GDP versus normalizing by estimated corporate revenues.]

To illustrate these relationships visually, the 3-D scatterplot below shows the TTM profit margin of the S&P 500 along one bottom axis, the TTM price/earnings ratio on the other bottom axis, and the actual subsequent 10-year annual total return of the S&P 500 on the vertical axis. This tornado of points is not distributed all over the map. Instead, you'll notice that the worst market returns are associated with points having two simultaneous features: not only above-average profit margins, but elevated price/earnings multiples as well. This combination is wicked, because it means that investors are paying a premium price per dollar of earnings, where the earnings themselves are cyclically-elevated and unrepresentative of long-term cash flows. This is the situation we observe at present. It bears repeating that the S&P 500 price/revenue multiple, the ratio of market capitalization to GDP, and margin-adjusted forward P/E and cyclically-adjusted P/E ratios remain more than double their pre-bubble historical norms.

[Geek's Note: On a 3-D chart where the Z variable is determined by the sum or product of X and Y, a quick way to visually identify the relationship is to view the scatter from either {min(X},max(Y)} or {max(X),min(Y)} as above].

The upshot is that regardless of the metrics used, S&P 500 nominal total returns in the coming decade are likely to be in the very low single digits - from current levels. But remember the Iron Law of Valuation - for a given stream of long-term expected cash flows, as valuations retreat, prospective returns increase. This should be a cause for optimism about future investment opportunities. Unfortunately, not present ones.

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