Progress of the secular bear market: position as of May 31, 2015

10000 point decline in the Dow in the cards over the next three years

I have been tracking the progress of the secular bear market since forecasting it in Stock Cycles in 2000. The valuation tool I employ is P/R, which I outlined in my first article at Safehaven in 2001. R stands business Resources. It refers to the non-labor resources businesses employ to earn a profit. R can be thought of as a constant-dollar book value. R in year t is the sum of retained earnings from 1871 to year t plus the value of R in 1871. I assume that R in 1871 is equal to the index value in 1871 and proceed from there. Values for the index price, earnings and dividends were obtained from Professor Shiller’s website. The figure at the top of this article shows plots of P/R for previous secular bear markets. Until about a year ago the current secular bear market had been behaving in a very conventional way–even the disruption of the crisis in 2008. But over the last year the behavior of the market has been unprecedented, assuming that we remain in a secular bear market.

I believe the recent rise in the market reflects a bout of irrational exuberance. Consider, in January 1999, P/R reached a level equal to its preceding record value, set in 1901. I had sold half my portfolio the previous month and would sell the rest by the end of the summer. Yet the S&P reached its highest value (on a monthly average basis) in August of 2000, 17 months later. The story told by the NASDAQ is even more interesting. In January 1999, it stood at 2500 and P/R predicted serious declines in the next few years. Indeed, the NASDAQ averaged about 1240 in October 2002, half its value in January 1999. What is interesting is the path taken by the “decline” from 2500 in January 1999 to 1240 in October 2002. On the way “down” it (briefly) was over 5000. Fed Chairman Alan Greenspan had called the late 1990’s market “irrational exuberance” and that is what it was.

The figure at the top of this article shows that the stock market reached an all-time high P/R for our current position in the stock cycle in May of 2014 and since then has moved much higher. But this assessment assumes that we are still in a secular bear market, and that stock market cycles are meaningful. How does the market compare to history if we ignore stock market cycles? The current value of P/R of 1.04 is well below the value of 1.47 seen in 2000. It is even below the absolute P/R of 1.06 in 1966, the lowest of all the secular bull market peaks. (Note: the 1966-1982 bear is scaled in the top figure so as to fit in with the other secular bear markets in order to show relative levels). So is the current level really all that high?

Why the market level today is problematic

The stock market is essentially a capital market; it serves the function of putting a price on the basket of capital associated with a specific firm. A broad-based stock index, like the S&P 500, provides a price for the capital collectively possessed by the companies in the index. R represents the cumulative investments responsible for that capital and can be thought of as an independent measure of the capital in the index.

It follows that the index earnings (E) divided by R gives the return on capital (ROC) for the index. The quotient of ROC and P/R gives the return on price (ROP) which should be indicative of the typical return on investment (ROI) from a purchase of a diversified portfolio of stocks in the index. Since capital is a real thing, ROC is a real return and so is ROP. ROC declined after WW I and never recovered. Table 1 shows ROC for the period before and after 1916. ROC was much lower after 1916 than before. The stock market responded by pricing capital lower, the average price for R was 24% lower after 1916 than before. As a result ROP did not drop nearly as much as ROC. Actual observed total return was only modestly lower.

Table 1. Estimation of stock market total real return using ROC and P/R

So far we have seen that around 1916 the way the stock market works changed in ways that reduced the average price of capital. There is an old Wall Street saying that the market is driven by fear and greed. Before 1916, the balance between fear and greed maintained P/R at about 1, and investors reaped a real return of 7.0% on a ROC of 7.3%. After 1916, the average level of fear increased so as to reduce average P/R, enabling an ROC of 4.5% to give a 6.2% real return. To do this required large swings in market levels (i.e. the secular bull and bear markets) to generate the fear necessary to produce low average prices. The figure at the top of the page shows that secular bear markets after WW I ended at much lower levels than those before WW I. Presumably, the current secular bear market should be no different than the other three post-WW I ones.

It is a reasonable assumption that the S&P 500 and Cowles index are sufficiently broad-based to be representative of the economy. In this case, R serves as a proxy for the amount of capital in the economy. As capital and labor are both factors of production, GDP should be correlated with both. Since the emergence of a modern industrial economy after the Civil War, GDP per capita (GDPpc) has been proportional to R.1 This means the ratio of GDPpc to R should be approximately constant if capital is being used efficiently. Indeed, from 1871 to 1907 GDPpc/R (capital productivity) showed an average value of 44±2 and over 1942-2000 it showed an average value of 42±3 (Figure 1). Following the Panic of 1907, GDPpc/R began a steady decline reaching the mid 20’s during the heights of the Depression. The ratio GDPpc/R can be thought of as a measure of sales per person (consumer) per unit of capital invested. A decline in the top line eventually falls to the bottom line, and after about a decade lag, pre-tax ROC also began to decline.

Figure 1. Declining capital productivity (GDPpc/R) led to the decline in ROC after 1916

So the fundamental problem was that capital ceased to produce as much output per person after 1907 as it had before. Less output means less pre-tax and post-tax ROC. Less ROC means more stock market and economic volatility to drive down P/R, which leads to increased risk, lower investment returns or both. Since the ethos of capitalism is the maximization of profit, this constraining of profit can be thought of as an operational crisis in capitalism, that culminated, decades later, in the general crisis of the Great Depression.

Capital that has a lower productivity than normal (i.e. between 1907 and 1942 and since 2000) does not have the same value as capital that produces normal output. We can account for changes in capital productivity by using the observation that during “normal” times GDPpc/R is approximately constant allowing us to express R as GDPpc/constant. If we use this in place of R we get:

1. P/R = constant * P / GDPpc

Figure 2 shows a plot of equation with a constant of 44 used before 1942 and 42 afterward. This shows how the market priced capital based on its performance. Three peaks stand out, 1929, 2000 and now.

Figure 2. P/R adjusted for capital productivity

That the stock market was in a bubble in 1929 was confirmed by the tremendous decline afterward. The situation in 2000 is different. Like 1929, 2000 was the end of a secular bull market during which conditions had long been favorable to investment and investors were understandably in a bullish mood. When the market began to decline, the Fed sprang into action and slashed interest rates. The real estate market, which had been in a bull mode for several years, but was not yet seriously overvalued, responded favorably and housing prices and building activity remained fairly strong during the 2001 recession, resulting in a milder downturn both economically and in the stock market than might otherwise had happened. A side effect of a strong real estate market during the recession was an even stronger real estate market after the recession, which resulted in a bubble in which real estate prices got about as overvalued as stocks had been in 2000. The aftermath of this bubble was much more severe on both the stock market and the economy. At the market bottom in 2009 P/R had fallen by two thirds from its high, and the US economy had experienced its first financial panic in 75 years.

Today the stock market is again approaching the valuations seen in 2000 and 1929. Unlike these peaks, today’s peak does not show a particularly high level in terms of P/E or other conventional measures of valuation. Stocks don’t look particularly high because the impact of the drop in capital productivity over the last decade has not yet filtered through to the bottom line. Rising profit margins since 2000 have worked to offset falling capital productivity so as to maintain ROC at pre-2000 levels (Figure 3).

Figure 3. Trends in capital productivity, profit margin and ROC since 1980

Concerns over the sustainability of current margins, have been expressed:

You have to pay close attention to Mauldin’s reasoning, which I’m obliged to disclose are based on the opinions of investor John Hussman, a closely followed investment adviser. He says “while price/earnings multiples appear only moderately elevated, those multiples themselves reflect earnings that embed record profit margins that stand about 70% above their historical norms.” Get that? Stocks are priced too high because expected record profits are too far above normal corporate earning power. By this rule of thumb, Maudlin reckons that “market valuations… are well above any point prior to the late-1990s market bubble.” Meaning that it’s 2000 all over again, as profit margins must revert to mean sooner or later.

Mauldin’s analysis concludes that stocks are again at levels similar to 2000, which agrees with Figure 3. Using a different methodology John Hussman has also concluded that the market as of 2014 was extremely overvalued:

The upshot is that equities are likely to produce total returns close to zero over the coming decade. But they still present something of an “inventory” problem. The basic inventory problem is to accumulate inventory prior to advances in price, to hold that inventory as long as it appreciates in price, and to release that inventory when prices are elevated. What we observe at present is a market where the inventory now fetches record prices and is likely to enjoy little return for long-term holders, and suffer severe losses over the completion of the present cycle. But should short-term demand become even greater, one can’t rule out a move to even higher prices and even more dismal long-term prospective returns – something to be celebrated by those who hold out long enough to sell at that point, but tragic for those who actually buy the inventory in the hope that it will be rewarding over time.

If we accept the likelihood of a major decline in the next few years how far is the market likely to fall? If the stock market returns to the normal secular bear pattern of a downward trend in P/R, then the coming bear market bottom should see P/R below 0.49. Even if the bear market were the start today it would likely take a couple of years to reach the bottom, as was the case in 2000-2002 and 2007-2009. Let us assume a bottom in 2018. Over those three years R can be expected to gain another 10% and be at around 2200. Multiplying this by 0.49 gives about 1080, about half of current levels. This is the best case.

Worst case would be if the coming bear market/recession were associated with another financial crisis. Should this happen there is little the Fed can do, interest rates are already near zero and three rounds of quantitative easing have already been tried and shown to have little positive impact on growth. Crises are all about confidence, specifically the loss of it (which is why historically they were called panics). With the recent experience of limited Fed effectiveness, it is unlikely Fed action along will be able to significantly moderate the extent of the decline.

This leaves direct government intervention. In the last crisis the market found a bottom shortly (thirteen market days) after the passage of the stimulus bill. And this had following the TARP bill four months earlier. Serious deflation never appeared and unemployment never approached the 25% level seen in the 1932-33 crisis. So it would appear policymakers were successful in preventing a worst-case outcome in 2009. Worst case for the coming bear market would be if no legislative action is taken this time. In this case the relevant examples would be come from the period after WW I (when modern secular cycles really began) to the period after 1950 when government economic intervention became routine. This period includes bear market bottoms in 1920, 1932, 1938 1942 and 1949. The P/R values for these are 0.27, 0.21, 0.45, 0.28, and 0.31, respectively. The average of these is 0.30, which when multiplied by 2200 yields 670, about the same value as that reached in 2009. Thus a range of lows between around 650 and 1050 is projected for the coming decline.

The consensus of the chart at the top of the page suggests a P/R value around 0.4 as most typical, which translates to a bottom around 900. So 900 would be the median forecast for the bottom. In terms of the DJIA, this translates to about 8000, that is, about a ten thousand point drop in the Dow.

References:
1. Alexander, Michael A. (2000) Stock cycles: why stocks won’t beat money markets over the next twenty years, Writers Club Press, New York, p 44.

Here is a quick follow-up on yesterday’s column, along with an administrative note (at the end). Yesterday, I noted there that momentum investors will begin to lose interest in being long equities as the year-over-year price return goes towards zero. I thought of another way to illustrate the same point, which maybe gets to something more like the average investor thinks.

The average “retail” investor wants big returns, but has a very non-linear response to losses. The reason that individual investors as a whole tend to under-perform institutional investors is that the former tend to exaggerate the effect of losses while underestimating the probability of losses. So, what tends to happen is that individual investors are perennially surprised by negative equity returns (don’t feel bad – financial media is set up to reinforce this bias), and react harshly to mildly negative returns – but not harshly enough to significantly negative returns.

So, the chart below shows a simple calculation of the probability of an equity loss over the next twelve months assuming that the expected return is just the return of the last 12 months, and the standard deviation of the return is the VIX (and assuming distributions are normal…just to complete the list of improbable assumptions). This doesn’t seem unreasonable with respect to assessing a typical investor’s expectations: returns should continue, and volatility is forward-looking.

Maybe it’s just me, but in these terms it seems more amazing. For much of the last few years, the trailing 12 month return was so high that it would take around a one-standard-deviation loss (16% chance) to experience a negative year – if, that is, we use prior returns to forecast future returns. In general, that’s a very bad idea. However, I can’t argue that this naïve approach has failed over the last few years!

What is the trigger that makes investors want to get out? After years of gains are investors going to act like they are “playing with house money” and wait until they get actual losses before they get jittery? Or will a 30-40% subjective chance of loss be enough for them to scale back? I think that this way of looking at the same picture we had yesterday seems much more promising for bulls. But, again, this is only true if valuation doesn’t matter. Stocks look less scary this way…but this is probably not the right way to look at it!

**Administrative Note – I have just agreed to write a book for a terrific publisher. The working title is “What’s Wrong with Money?: The Biggest Bubble of All – and How to Invest with it in Mind.” I am very excited about the project, but it is a lot of work to turn the manuscript out by late August for publication in the fall. My posts here had already been more sporadic than they used to be, but now I actually have an excuse! If you would like to be on the notification list for when the book is published, simply send an email to WWWM@enduringinvestments.com and I will put you on the list!

You can follow me @inflation_guy!

Enduring Investments is a registered investment adviser that specializes in solving inflation-related problems. Fill out the contact form at http://www.EnduringInvestments.com/contact and we will send you our latest Quarterly Inflation Outlook. And if you make sure to put your physical mailing address in the “comment” section of the contact form, we will also send you a copy of Michael Ashton’s book “Maestro, My Ass!”

Forget your typical utility companies and Oreo-peddling consumer staples — these are income plays of a completely different color

With bond yields in the gutter for almost six years now, investors have grown accustomed to looking in … shall we say….. “nonconventional” places for yield.

Whether in odd corners of the stock market or in dodgy-looking private placements, anything offering a respectable current income is bound to get at least a little attention.

It’s easy enough to understand why. The 10-year Treasury yields barely more than 2%, and traditionally high-dividend stocks like utilities and REITs yield less than 4%.

Even “high-yield” junk bonds — and yes, you have to write “high-yield” in quotation marks these days — yield less than 6%, and these come with the not-so-insignificant risk of default.

Today, we’re going to take a look at seven high-dividend stocks that fall a little outside the mainstream. Not all of these are dividend stocks that I would necessarily recommend, but all are worth at least keeping on your radar.

After all, it is their quirkiness and lack of inclusion in major benchmark indices that tends to keep them off-limits to large institutional investors … creating the very conditions that make them worth considering for us.

High-Dividend Stocks: StoneMor Partners, LP (STON)

STON Dividend Yield: 8.4%

I’ll start with a stock that is one of my personal favorites … but one that also tends to give a lot of investors the heebie jeebies: publicly traded crypt keeper StoneMor Partners, LP (STON).

StoneMor owns and operates 303 cemeteries and 98 funeral homes across the United States and Puerto Rico, and its business is anything if not predictable.

As none other than the great Benjamin Franklin noted, nothing can be said to be certain but death and taxes. And as the baby boomers — the largest generation in history — enter their golden years, end-of-life services are about to enjoy an unprecedented boom. Based on current life expectancies, the number of annual deaths in America will rise by more than 80% between 2015 and 2035. Even allowing for an increased preference for cremation over traditional burial, an incredible amount of growth is all but guaranteed to come down the pipeline.

And even better, we’re getting paid to wait: StoneMor pays an 8.4% distribution, and it has steadily raised its payout over the past 10 years.

If the unpleasant association with death wasn’t enough, StoneMor has some other quirks that make it difficult for a lot of investors to own: It’s structured as a master limited partnership (“MLP”) and can generate unrelated business taxable income (“UBTI”), which makes it all but untouchable for an IRA or Roth IRA account. Its status as an MLP also makes StoneMor problematic for a lot of institutional investors and non-U.S. persons to own.

Their loss is our gain. StoneMor is a stable company that throws off a high and growing cash distribution. Buy it and plan to own it until … well, until you become one of StoneMor’s permanent residents.

.….read about the next stock HERE

EVERY single long-term market indicator has now broken down and send signals that have ONLY occurred at prior major market peaks.

However, despite the deterioration in the underlying momentum, asset prices remain near all-time highs as investors remain convinced that Central Banks will continue to “bail them out.”

Furthermore, as I discussed with Evenlyn Chang at CNBC early Friday morning:

“As we have discussed previously, the markets are starved for liquidity. The stronger than expected jobs report, which doesn’t jive with the economic data, paves the way for the Fed to hike rates in June or September.

This is a further restriction in liquidity. Remember, the markets have been rallying on BAD news because it pushes out Fed rate hikes. Good news – is technically bad for stocks at this late stage of the economic and market cycle.”

…….Read More HERE

Back in the early 1960s, then University of Chicago PHD candidate, Eugene Fama published a thesis which was later developed into a theory called the Efficient Market Hypothesis (EMH). This theory gained widespread acceptance in the finance industry (at least among academics) for several decades afterwards and is still commonly referenced to this day. Essentially what Professor Fama was postulating is that stock markets, or most markets for that matter, were efficiently priced at any point in time and that it was inherently impossible to outperform the market on a risk adjusted basis outside of the aid of pure luck, thus making individual stock selection a futile pursuit.

Around the 1990s, Fama’s theory started to lose its appeal among the mainstream finance community. Empirical evidence and research did not support the EMH’s conclusion that capital markets were perfectly efficient and select investment strategies, such as buying stocks with low price-to-earnings and cash flow multiples, did demonstrate an ability to outperform the market on a risk-adjusted basis over time. Providing an explanation of the short-comings of the Efficient Market Hypothesis was a relatively new field known as Behavioral Finance. This new field sought to study the emotional traits of investors and the impact they had on investment decisions and market activity. EMH was largely based on the assumption that humans were perfectly rationale beings and that decisions were made instantaneously with full knowledge of all potential outcomes in an unbiased and emotionless process. However, studies in both psychology and finance have demonstrated that this perfectly rationale investor was largely a myth. Human beings in fact rely on emotion to a large extent when making important decisions and are subject to a wide variety of potential biases. An objective of Behavioural Finance is to integrate these real world human biases into modern day financial theory to create a more realistic explanation of how the markets work.

Behavioral finance and psychology have defined numerous biases that can lead to poor investment decisions. We have provided a few examples below.

Bias: Bandwagon Effect

Definition: This occurs when a certain idea, investment type, or investment style starts to become more popular. As popularity increases, more and more people adopt the groupthink mentality and adopt the mentality themselves which further accelerates popularity, and in the case of investing, asset overvaluation.

Example: Alex has been looking at the market for potential investment opportunities. He has noticed that many small-cap tech companies have been doing well. A few of his friends have started to invest heavily in the sector, with good results, but Alex is worried about the high risk nature of the securities. As time passes, more of Alex’s friends have gravitated towards the sector and he is starting to see more portfolio managers and experts talk about it on the financial news. More time passes and the popularity increases. Finally, Alex has grown tired of missing out on the returns and decides to make some significant purchase of these stocks. Unfortunately, the growing popularity of the asset class has pushed valuation far beyond reasonable levels and the sector is now in serious risk of a crash.

Bias: Recallability Trap

Definition: This occurs when an individual’s opinions and decisions are overly influenced by large scale (and often dramatic) events that have taken place in the past.

Example: John receives a call from his financial advisor informing him that he has compiled a report of several successful technology companies that offer strong investment value. All of the companies in the report are profitable, growing, maintain healthy financial positions, and are trading at attractive value. John tells his advisor that he has no interest in receiving the report as he was heavily invested in tech stocks shortly before the market crashed 2001. His opinion is that the sector is far too volatile and he has decided to stay out of it completely. Although John’s decision is understandable, he is now limiting the flexibility of his portfolio based on an irrational bias. The tech market crashed in 2001 because it was substantially overvalued – but that does not mean that current opportunities do not exist in that space.

Bias: Confirmation Bias

Definition: When people have an existing belief, such as an opinion on an individual stock or the movement of the economy, we tend to overweight evidence that supports our original view and underweight, or even disregard, evidence that that conflicts with this view.
Example: Jane recently made a purchase of Company B which is advancing a new technology. She spent a great deal of time reading the company reports and speaking to management. About a week after the initial purchase, she hears an analyst on the news reiterate what the company said about the technology. Pleased to see more people taking notice of the company, Jane increases her position that day. About a week later, she hears another analyst with a respected background in science discuss the technology and conclude that it is not as commercially viable and the company suggests. Although somewhat concerned with the statements, Jane takes no action.

Bias: Anchoring and Adjustment

Definition: Very similar to confirmation bias, anchoring and adjustment is a tendency to not fully reflect and adjust for new information when reviewing an existing opinion or forecast. This is a very common bias in the professional analyst community but can also been seen regularly with retail investors.

Example: Jim owns shares in Company C and believes that the stock price will appreciate from $5.00 to $9.00 in 12 months as a result of increased sales from a new product offered by the company. Company C releases a statement later on indicating that sales of the new product are falling significantly short of initial expectations. Disappointed, Jim decides that the stock is probably only worth $7.00 over the next 12 months and cuts his price expectation by $2.00. Considering the lack of visibility going forward, a large reduction is the price expectation is justified but Jim is still being influenced (he is anchored) to this original target.

Bias: Overconfidence

Definition: This is when investors tend to place too much confidence in their ability to pick stocks or make investment decisions. It is typically the result of a past success, or successes, which may or may not have been the result of luck. Overconfidence can be dangerous because it can cause investors to underestimate risk, under-diversify their portfolio, and even disregard relevant information.

Example: Garth has been a buyer and seller of speculative junior mining stocks for the last several years with mixed success. But recently he bought shares in Company E which made a notable discovery and appreciated in price substantially. Garth also noticed that many of his other junior mining stocks had been doing well over the past year but that his diversified portfolio had underperformed. Garth concluded that his experience in identifying opportunities in the sector had started to pay off. He was also ignoring the fact that many of his stocks were doing well as a result of a generally strong market over that period. The problem was that Garth didn’t buy enough of Company E to really boost his portfolio value. Confident in his abilities, Garth decides that he is going to search hard for another stock like Company E, only this time he plans to concentrate a large portion of this portfolio in the stock so that he can make a huge return.

Bias: Mental Accounting

Definition: This refers to the way that the people have a tendency to mentally compartmentalize their finances and separate capital to psychological accounts. 

Example: Taylor is reviewing his finances and deciding how much money he can contribute to his investment account, which is currently worth $20,000 and has been generating a 6% annual return. Taylor also noticed that his credit card balance was a hefty $10,000 on which he is paying 18% interest. Taylor understands the importance of paying down debt as well as saving for retirement so he splits his $5,000 annual contribution 50/50% to debt repayment and investment. While this may seem appropriate, it is actually highly irrational. For this to be a rational decision, Taylor would need to generate a minimum return of 18% in his investment account which is highly unrealistic. Taylor’s investment portfolio would be better long term if he were to use both his annual contribution and his investment portfolio to completely pay down the high interest debt.
Now that we are aware of a few of the common investor biases we can start to evaluate whether or not our own decisions are impacted by irrational tendencies and counterproductive habits. The first step is simply awareness. While it may be asking too much of ourselves to be perfectly rational at all times, simply being aware of the common biases and reviewing our behaviour in that context can be highly beneficial with respect to making better investment decisions in the future. 

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