Author Archive for McClellan Financial

2nd Presidential Years Are Different

Tom McClellan – McClellan Market Report

By now most who follow the stock market know that the first two years of each presidential term are basically flat, but the good times come in the 3rd year which is nearly always an up year.  What a lot of people do not know is that it matters a lot in the 2nd year whether you have a first term president or a second termer.

This week’s chart helps to make that point.  To create each plot, I took the historical data for the SP500 (or its predecessor the Cowles Index) going back to 1936 and chopped the data into 4-year chunks, starting at the beginning of November in each presidential election year.  November is when the election is, and my assumption is that the market starts reacting to the results of the election as soon as those results are known, rather than waiting until the victor is actually inaugurated.

Presidential Cycle Pattern versions for 1st or 2nd term presidents

With the data chopped up into those 4-year chunks, I then adjust each period to fit a uniform calendar.  This is necessary because up until 1952, the stock market used to trade on Saturdays.  And then in the summertime in the 1960s, the NYSE used to shut down on Wednesdays so that the clerks could get caught up on all of the paperwork for the increasing volume of trades.  Then I would reset the daily values in each 4-year chunk to reflect the percentage change since the beginning, the better to average them all together.

For this week’s chart, there is one additional step, which is to segregate the 4-year chunks of time into groups based on whether the president was in a first or second term.

Why is this necessary?  The stock market tends to behave differently depending on whether there is a new president from a different party than the last one, or a reelected incumbent.  Generally speaking, a 1st term president tends to spend a lot of time during his first two years “discovering” that conditions are even worse than he told us during the campaign, and proclaiming that the “only solution” is whatever package of tax hikes/cuts or spending boosts/reductions he is proposing.  Investors generally get discouraged upon hearing that things are worse than previously thought, and that shows up in the movements of stock prices.

An incumbent who wins reelection generally does not spend as much time blaming the guy who preceded him, and gets on with continuing what he was doing.  And the stock market responds accordingly.

By the 3rd year, those differences are gone, at least according to the historical record, and the stock market generally behaves in a similar fashion regardless of what type of new or old president is in office.  We’ll get to the 3rd year of this current presidential term in a few more months, but first we have to get through the unusual period in the summer of the 2nd year.

With a first term president in office, the market typically sees a price peak in November of the first year, and then a decline into the summer of the second year.  That summer bottom typically leads to a rally into autumn, and continuing right into the 3rd year.

But the 2nd year is almost the exact opposite with a 2nd term president in office like we have now.  The market typically reaches a peak in July (not in May, as so many believe), and then drops for the rest of the summer toward a September low.

To help see the difference, here is a chart showing both of these versions of the Presidential Cycle Pattern and comparing them to the action in the SP500 since the 2012 election.

SP500 and Presidential Cycle Patterns 1st and 2nd term presidents

It quickly becomes obvious that the current market action is behaving a whole lot more like the average pattern for 2nd term presidents, which is as one would expect.  The magnitude of the movements has been greater than average, which is also normal, and not all that remarkable.  The Presidential Cycle Pattern and its variants are much more useful for telling us about direction than about magnitude.

Here is another version, showing only the 2nd termer version, and zooming in closer on just the most recent data:

Presidential Cycle Pattern 2nd term presidents

It shows that the steep drop which began from the July 24 top is happening pretty much on schedule.  A brief pause in the decline is due over the next few days, and then a resumption of the decline should appear.  The ideal bottom equates to around Sep. 10, although the bottom to go up out of does not appear until a month later.

A few months from now, we’ll get to the bullish conditions of the 3rd year of a presidential term.  But the market has a less than bullish period to get through first.


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Chart In Focus Archive

A Scary Valuation Indicator

Tom McClellan – McClellan Market Report

If you want to get worried about long-term stock market valuations, this week’s chart should do the job.  I saw a version of this chart recently in a research report by Daniel J. Want, who is Analytics Director for Prerequisite Capital Management in Queensland, Australia.

What is unique about this indicator is that it combines two separate data series into one indicator.  When I first saw the version of this chart in Daniel Want’s report, I thought it was just wrong to put the CAPE data together with the Moody’s Baa yield, since the two are actually strongly correlated.  So combining them together just magnifies the same message.

CAPE ratio adjusted by Baa yield

This is because the P/E ratio is the inverse of the “earnings yield”, which should reasonably match up with bond yields.  If an investor can get a better return on his money in the bond market, then he will flee the stock market, or vice versa.  That is what keeps the earnings yield and bond yields in correlation.  But when investors are bidding up stock prices to a ridiculous point such that the earnings yield is way out of whack from the bond interest yield, then there can be a big problem.

But the more I thought about it, the more I saw the beauty of this approach of combining the two.  Low interest rates are usually associated with periods of high P/E ratios, but not always.  Sometimes the market’s average P/E ratio can get to a high level because earnings fall to a low level in a recession, as opposed to prices going way up above where they should be.  In 2008-09, for example, the SP500′s raw P/E ratio sky-rocketed, not because prices were too high, but because earnings were unnaturally too low.

SP500 Raw P/E Ratio

Analysts have struggled for years to make meaningful use of overall market P/E ratios because of problems like these.  Professor Robert Shiller of Yale University uses one method to deal with this, which is to calculate a “Cyclically Adjusted P/E” (CAPE) ratio.  This is the same Prof. Shiller who wrote the 2000 book “Irrational Exuberance“, and whose name is attached to the S&P Case-Shiller Home Price Indices.

Shiller’s CAPE looks at each month’s inflation-adjusted (by CPI) real price for the SP500, and compares it to the 10-year average of real earnings.  The intent is to smooth out the earnings fluctuations across one or more business cycles, which is an idea that dates back all the way to the work of Graham and Dodd in the 1930s.  CAPE does a better job than the raw P/E ratio of identifying extreme high and low valuation levels:

SP500 vs. CAPE

The extreme peaks and valleys are smoothed down somewhat, but we still are confronted with the difficult task of determining how high is “too high”.  The CAPE peak at the 2000 bubble top was well above everything else in the record, even including the 1929 stock market top which preceded the Great Depression.  But just because the CAPE level got up that high did not mean that the stock market had to roll over right away.  It stayed at a lofty CAPE ratio level for many months before the Internet bubble finally burst and caused stock prices to turn downward.

The indicator which Daniel Want featured in his report seems to solve some of those problems.  For the record, Mr. Want states that he saw it elsewhere and cannot remember the source, but he added it to his toolbox a long time ago after seeing the nice properties it displays.  I am a big fan of giving attribution to the creators of original ideas, whenever I can figure out who they are.  So I’ll give a tip of the hat to Mr. Want from whom I learned about this tool, even if I cannot yet discern the true originator.

“Baa” is a bond quality rating assigned by Moody’s, and it means that the bond instruments with that rating “are subject to moderate credit risk. They are considered medium-grade and as such may possess certain speculative characteristics.”  The monthly Baa rate used in this week’s chart comes from the St. Louis Federal Reserve’s Economic Database (FRED), and is the monthly average of daily yield data on all of the Baa-rated corporate bonds.

The magic of the composite indicator in this week’s chart is that by adjusting CAPE for the Moody’s Baa yield, the result seems to set a much more uniform ceiling for how high valuations can go.  Getting above a certain level says that the market is really getting to the edge, and is near a MAJOR price top.  And that is the message of this week’s lead chart, which shows that this CAPE/Baa ratio is now up to the sort of level which has always marked a MAJOR stock market top every time it has been reached.  That’s obviously a problem for the market, but it is not necessarily an immediate problem.  And I want to emphasize that the message is that the market is NEAR a major top, and not necessarily AT one.

Looking at past major tops, the final price top does not usually arrive while the CAPE/Baa ratio is in its steepest slope of an up move, like that which we are seeing right now.  We also see that the price peaks in 1966 and 2000 came after this indicator had already peaked and turned down.  The point is that there is considerable variability about the nature of how tops are built, and it can take a while to complete the process.  The message for now is that the rubber band is getting stretched really far, and that is a problem for the really long run for stock prices.  Today does not have to be the final moment for the long bull run, but it is the time to begin planning for the final moment.


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Chart In Focus Archive

Alarming Sign in NDX Stocks’ Drawdown

Tom McClellan – McClellan Market Report

The Nasdaq 100 Index is making new multi-year highs, levels not seen since the weeks just after the 2000 Internet Bubble top.  But it is interesting for us to see that the average component stock in that index is down 7% from its trailing 52-week high.

And that 7% drawdown number is actually smaller than it has been recently, but it is still not back to the low drawdown reading of 6.0% that we saw in early March, before the Nasdaq 100 stocks got into a patch of trouble.  And the fascinating point is that divergences like this tend to be really important for the long-run picture for stock prices.

This current divergence is not guaranteed to stay with us.  It looks like a genuine divergence now, but it is still possible that we could see a continued rally that takes the stocks in the Nasdaq 100 collectively up closer to the level of their 52-week closing highs, thereby closing the gap on this measure of average drawdown.  But for now, the message is that the average stock making up the Nasdaq 100 Index is not confirming the bullish message of the NDX’s higher price highs.

Nasdaq 100 stocks average drawdown amount

A similar message comes from a similar indicator, this time examining the 30 stocks which make up the DJIA.

DJI Oscillator Positive Index

This one looks at the 30 stocks that make up the DJIA, and checks each one to see if its Price Oscillator is above or below zero.  What we are seeing lately is a declining number of Dow components participating in the uptrend that way, and a drop of this indicator below its 15-day moving average.  This condition also comes as a divergence appears between prices and the indicator.

As with the NDX stocks’ indicator above, the divergence does not absolutely have to persist; the market could just power through it, but that is not usually the way things usually work out.

As a final aside, I appeared on CNBC this week to discuss last week’s Chart In Focus topic.  You can see a portion of that interview at http://video.cnbc.com/gallery/?video=3000288767


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Chart In Focus Archive

VIX Below 12!

Tom McClellan – McClellan Market Report

The CBOE Volatility Index (VIX) has dropped below 12.  Below 12!!!  Surely this must be one of the signs of the apocalypse.

Not so fast.  A low VIX is a sign of option trader complacency, and complacency is a problematic sign for the market which can lead to a price decline.  But when the VIX gets really REALLY low, the message changes.  Sure, it is a sign of an absence of worry, and a correction is possible.  But the really big price tops do not appear when the VIX is this low.

In 2000, the SP500 topped after the VIX had climbed up from the really low levels of a few years earlier.  The final price top came when the VIX was at 16.54.

In 2007, the SP500 again topped with the VIX above 16.  It had been much lower earlier that year, bottoming below 12 in April 2007 well in advance of the final price high.  This is a consistent theme.

VIX below 12

When a toy top spins, it is at its most stable point when the RPM are high enough to maintain stability.  Gradually the friction against the tip spinning on the floor slows the top, and the top starts to wobble.  The wobbling is a prelude to the top falling over completely.  In other words, instability increases ahead of the tipping point.  When everything is as stable as it can be, that is not yet the tipping point.  So while a VIX reading below 12 is a quite spectacular condition, history says it is not the sign of an ultimate price top.

On a shorter term time scale, the VIX can give us a hint of a brief change in trend direction.  It is normal for the VIX to make a lower low as the SP500 makes a higher high.  But when there is a disagreement, THAT is when we get useful information from the VIX.  We have a tiny little divergence right now, with the VIX making higher postings at the same time when the SP500 is also making higher highs.  On a short term basis, this is a sign of the spinning top starting to wobble, and sets up the opportunity for a countertrend price drop.

VIX SP500 with 50-1 Bollinger Bands

The divergence is a setup for potential trouble.  The real trouble for short term price movements typically comes when the VIX rises up above its 50-day moving average (50MA).  That is a topic I addressed here.

But we should not confuse a short term setup for a corrective move with the signs of a more important long term top.  Seeing the VIX go this low is NOT the sort of condition consistent with the major tops of the past.


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Chart In Focus Archive

Equity Options vs. Index Options

Tom McClellan – McClellan Market Report

Most traders who look at options market data for market insights like to focus on the “Put/Call Volume Ratio”, which examines the differences between the number of trades in bullish versus bearish bets.  I use that data in my work, and even get into differences between the Put/Call Ratio for equity options versus index options.

There can also be useful information just in looking at the total volume in each category, which is what this week’s chart does.  It originated from a desire to know what it means when comparatively more of one category gets traded, and with a little bit of smoothing it makes for a nice indicator.

What we are looking at is a 10-day moving average of the daily ratio of total equity options volume versus index option volume as traded on the CBOE.  It sums together the puts and the calls in each category.  The range of values tends to wander a bit over time, and so I have also added 50-1 Bollinger Bands (50-day MA, and bands are set 1 standard deviation above and below).  When this indicator goes up above the upper 50-1 band, it can indicate a topping condition for prices, and the opposite meaning comes from dips below the lower band.

Equity versus Index option volume

The one huge caveat is that this indicator tends to work poorly around the time of quarterly options and futures expirations.  The artificial volume related to exercising options and reestablishing positions can skew the numbers for a brief period.  So that is an important factor to remember when using this indicator. 

That is not a condition we face right now, as this indicator has just dipped below the lower band.  It is an unusual condition to see the indicator this low while prices are making higher highs, but it has nevertheless happened  before.  The meaning is still bullish even at a higher price high.  Some examples are highlighted.

The implication is that the breakout move in the SP500 should be able to continue higher because of the sentiment message revealed by this indicator.


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Chart In Focus Archive

Bund Spread’s Message for the Stock Market

Tom McClellan – McClellan Market Report

The folks who watch international bond yields have been giving a lot of attention lately to the fact that the spread between the 10-year U.S Treasury Note and the equivalent government bond from Germany is now up to its widest point since 2005.  CNBC’s Rick Santelli showed a chart of it in a segment on April 2, 2014, and what caught my eye was how much that yield spread looked like the behavior of the stock market.

So I downloaded the data on German yields from the St. Louis Fed, calculated the spread versus the 10-year T-Note, and put it on a chart with the DJIA as shown above.  And sure enough there is a nice correlation there.

The German bonds are known in the bond industry as “bunds”, derived from the German prefix “Bundes” which means “federal”, as in the Bundesrepublik Deutschland, or the Federal Republic of Germany in English.

Yield spread 10-year T-Note to German bunds

As noted above, the T-Note to Bund spread was just slightly higher in 2005, and also back in 1999, and both instances were associated with toppy conditions for the U.S. stock market.  If I were to try and craft a “rule” about this relationship, then I would say it gives a pretty good top signal for the stock market when it rises up above about 100 basis points (1 percentage point), and then turns down.

That turning down part is important, because the spread can keep on rising as stock prices keep on rising.  Only after the spread starts turning down does it seem to matter for stock prices, and with some degree of lag.

Why would this work?  I confess I have been struggling with that ever since seeing Santelli’s chart of just the spread on the air.  What I have come up with is that the spread is actually a measure of investors’ risk-seeking behavior.  When investors are fearful about the stock market, then the “flight to quality” mentality sends them into Treasury bonds and notes.  In such instances, people forget about fair values and just want the perceived greater safety of having the assurance that the U.S. government will guarantee their investment. That pushes down T-Note yields.

At the other end of the sentiment extreme, when investors are confident about the stock market, they get out of Treasuries so that they can invest in stocks, and that exit from Treasuries helps push bond prices down, and yields up.

Because of the Germans’ reputation for an almost religious devotion to low inflation, their bond yields can be thought of as more of a baseline value for gauging worldwide inflation expectations.  And so to the degree that U.S. T-Note yields are varying from that baseline, there is information in this yield spread about investors’ appetites for risk, or the lack thereof.

But it is really interesting to note that the relationship has only been working this way for about the last 25 years.  Here is a longer term look at the T-Note to bund spread:

T-Note to Bund yield spread 1956-2014

The data on bund yields goes back to 1956, a period when post-war West Germany was still working to rebuild everything, including its financial markets.  During the 1950s and 1960s, the divided Germany was still more like an emerging market than the established industrial power it is today.  So bond traders back then understandably demanded a higher yield for investing in West Germany’s debt.

That relationship flipped wildly to the other side in the mid-1970s, when ultra-high inflation in the U.S. pushed Treasury yields up to a high level, taking this spread up to as high as 536 basis points in 1984.  German reunification in 1989-90, and the eventual creation of the euro currency in 1999, helped to bring this spread to a more stable relationship that we see today.

Right now, the still-rising spread means that risk-seeking (or safety-avoiding) behavior is still on the rise.  And why not, with the Fed still giving away free money at the short term end of the maturity spectrum.  But at some point in the future, the amount of this spread implies that we are going to have to see a 2001-03 or 2008-09 style bear market, just to restore equilibrium in both the international bond markets and the U.S. stock market.

 


 

On an unrelated topic, the St. Louis Fed’s web site is a great source for accessing a huge variety of historical economic data.  They even have the DJIA back to 1896, and other stock market index data series.  But an announcement on their site says that Standard & Poors is about to yank away their authority to publish S&P index data after April 25, 2014.  So if you want to have a chance to access and download that data before it goes away, now is the time to act.


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Chart In Focus Archive

A Divergence Among Nasdaq 100 Stocks

Tom McClellan – McClellan Market Report

The Nasdaq 100 Index (NDX) has been leading the way higher, making higher highs and higher lows all throughout 2013 and into 2014.  But it has been doing so with diminishing participation.

This week’s chart shows an indicator whose value is featured every day in our Daily Edition.  It measures the number of component stocks in the Nasdaq 100 Index which are above their 100-day simple moving averages.  As the market advances, more stocks rise in sympathy and this indicator goes to higher values.  Similarly when the market falls, the component stocks fall, and this indicator goes down.  No surprise there.

NDX stocks above 100-day MA

The real information comes when there is a difference in behavior.  Seeing the NDX make higher highs while fewer stocks are above their 100MAs is a sign of waning participation in the advance.  But divergences can unfold over a long period of time before they finally matter and turn into a meaningful market decline.

That is the issue that we face right now.  This indicator peaked all the way back in September 2013, and has been making a series of lower highs ever since even as the NDX has trended higher.  History says that eventually this type of divergence is going to matter.  But the market is inconsistent in terms of the period over which a divergence can last before the point when it “matters”.

The chart below takes a longer look at this indicator:

NDX stocks above 100-day MA  2002-09

Sometimes it can make a quick spike up to above 80 on a blowoff up move.  Other times, the market continues going higher after a quick spike, and a long divergence is needed in order to build a top.  The 2007 market top came at the end of a divergence that lasted 12 months.  Patience can be difficult in such situations.

The current divergent condition is only 6 months old.  But it carries the same attributes of other important divergences of the past, telling us that the uptrend is continuing on diminishing participation.  Eventually it is going to matter.


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Chart In Focus Archive

Housing Stocks Due for a Dip

By Tom McClellan – McClellan Market Report

The rally in housing stocks that I wrote about last November has been proceeding pretty much according to plan.  That’s the good news.  The bad news for investors is that lumber prices now say the housing related sector is due for a temporary dip.

Housing related stocks should see a recovery, for the most part, from that mid-year dip.  But by the time that the bottom arrives, history suggests that no one will be believing in any recovery.

The key insight behind this forecast is a relationship I uncovered back in 2008.  An interest in the movements of lumber prices led me to look at both the lumber market and the housing stocks sector.  Upon initial examination, it was clear to me that there was somewhat of a coincident relationship, which would only make sense since the two are closely related.  But the chart correlation was not quite right.  I unlocked the secret by shifting forward the plot of lumber futures prices by a year, to reveal how the HGX Index tends to follow the same dance steps with about a one year lag.

Lumber prices lead housing stocks by 1 year

It is really nice to get the answers ahead of time, even if they are imperfect answers.  And that imperfection is important to understand when using this relationship for insights.  The chart below zooms in closer on this same relationship, and allows us to see that at an up-close level, the correlation is not as good as it was when we looked from further away.

Lumber prices lead housing stocks by 1 year

Within this chart, we can see that back in 2011, the HGX did not feel compelled to follow the blowoff path of lumber prices a year earlier, when the April 2010 earthquake in Chile sent a tremor also through the lumber futures market.  Since that price spike was the result of an exogenous event, and not a case of a push-pull of market forces, it did not see an echo in the prices of housing related stocks.  And that reveals the key:

Lumber price movements do not “cause” the similar movements a year later in housing related stocks.  Instead, lumber just serves as an indicator of an underlying “liquidity wave” flowing through the wood market, and that same wave generally shows up again a year later in the housing stocks market.

The chart also reveals that the HGX Index does not perfectly follow every bump and wiggle in lumber prices.  And yet the overall correlation is evident. I take this to mean that it is a message worth listening to, but not one that is proper to expect perfection from.  Life just does not work that way.

Coming up, the relationship says that a top lies just ahead of us, and then a strong-looking dip to a low due in June 2014.  We saw similarly strong looking dips back in 2011 and 2012 that did not bring the same sort of magnitude response in the HGX Index, so that is worth understanding.  Still, the timing of the movements was well matched even if the magnitude was not.

After that presumptive June 2014 bottom is another rally up toward the end of 2014.  The corresponding rally in lumber prices did not make it to a higher high, but that does not necessarily mean that housing stocks cannot do so.  Remember, this model is good for timing, not for magnitude.


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Chart In Focus Archive

Yield Curve’s Message For GDP

Tom McClellan – McClellan Market Report

One of the really fun leading indication relationships involves the yield curve, the spread between interest rates on similar securities across different maturities.  The real yield curve has too many data points each day for visual modeling, and so a simplistic model of the yield curve can suffice to make for easier modeling.  In this week’s chart, the role of the entire yield curve is portrayed by the spread between the 10-year T-Note yield and the 3-month T-Bill yield.

10-year and 3-month yield spread versus relative strength

The fun thing that we get from this representation of the yield curve is a leading indication of what small cap stocks will do versus large caps.  Playing the role of each market segment are the Russell 2000 and Russell 1000 Indices.  Dividing one by the other gives us a relative strength ratio, which moves up or down as small caps outperform or underperform. 

Historically, the movements of the yield curve (as represented here by the 10-year to 3-month spread) get echoed about 15 months later in the movements of this relative strength ratio.  And that same 15-month lag period also shows up in other data.  Here is a comparison of that same yield spread versus GDP growth:

Yield spread versus GDP growth

Once again, the plot of the 10-year to 3-month spread has been shifted forward in the chart by 15 months.  This helps to reveal how periods of higher spread between long and short Treasuries gets echoed about 15 months later by stronger GDP growth.  And when the yield curve “inverts” and takes this spread down close to or even through zero, we see a corresponding dip in GDP growth about 15 months later.

We have a lot of years of history to show that this relationship works pretty well.  But the difficult question is whether it still works now that the Fed is pursuing a centrally managed interest rate market.  Economist Alexander Tabarrok had a great quote about this several years ago.  In a Forbes magazine interview, he said, “A price increase is a message about scarcity.  Price controls are like shooting the messenger.”

By manipulating the short end with its zero interest rate policy (ZIRP), and by manipulating the long end with more than $4 trillion of US Treasury bond mortgage back securities purchases, the Fed just may be killing the messenger, and ruining a great leading indication.  Ever since the Fed became more active, following the 2008-09 depression, the correlation has not been working as well.  The recent swoop upward in this yield spread should mean small cap outperformance and rising GDP growth into early 2015, but that is only if one is prepared to believe a manipulated interest rate model.


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Chart In Focus Archive

Can Earnings Get Better Than This?

Tom McClellan – McClellan Market Report

The conventional stock market analysis world revolves around earnings.  “Earnings drive the stock market,” they say.  This myopic view is akin to the belief that carbon dioxide is the driving force behind the greenhouse effect (water vapor actually accounts for 90-95% of it, but you don’t hear that).  People believe that earnings are everything because they have been told that it is so, and everyone thinks so,  therefore it must be so.  Circularity of logic and contradictory evidence do not seem to be significant impediments to the acceptance of this belief system.

This week’s chart looks at the BEA’s data on corporate profits.  To access it yourself, go to the BEA web site at this link, and then click on Section 1 – Domestic Product and Income, and then Table 1.10, and scroll down to Line  15.  Then all you have to do is divide by GDP, which can be accessed here.

Corporate profits as percentage of GDP

Why doesn’t everyone look at earnings this way?  My answer is that Wall Street has a fascination with its own forecasts of earnings, and with the reported earnings of listed companies stocks.  But those are a pair biases which excluded private company earnings, and which also accept earnings estimates which are notoriously subject to revision.  I prefer to deal in hard data.  The next BEA report on earnings is not due out until Feb. 28, so using these data means accepting the inherent reporting lag. 

What we see now is an indication that the reading for overall corporate profits as a percentage of GDP is at one of the highest levels of recent years.  And when it cannot get higher, it can only get lower.  It is true that this measure has been higher in the distant past, but that was back in the 1960s and earlier, when GDP was a bit different than it is now, and when accounting standards for measuring profits were also different.  The current high reading has only been exceeded once in the past 46 years, and that was at the real estate bubble top for earnings back in 2006.  And we all know how that ended.

Why should this matter?  When profits get up too high, certain agents decide that “excessive” corporate profits are a worthy target to go after.  So new taxes or other restrictive rules come into effect, and stimulative measures such as Federal Reserve policy which may help spur earnings to a higher level are pared back.  Those twin agents have a negative effect on stock prices, or at least they have historically.  Maybe this time will be different.

The other troubling point about this chart is that the amplitudes of the swings from highs to lows in corporate profits seem to be getting bigger over the past 20 years.  This measure formerly had much smaller magnitude movements, but the big swings we have seen during the last 3 boom-bust cycles resemble a spinning top that is starting to wobble just before it falls over and stops.  Yikes!  And at the point when profits as a percentage of GDP starts to fall, you can see in the chart what usually is happening then to stock prices.  But remember that there is a reporting lag; we don’t even have Q4 numbers yet.  So it is not as if you can wait for confirmation from the earnings data, and then decide how to invest.


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Chart In Focus Archive

Coppock Curve Turns Down

By Tom McClellan – McClellan Market Report

A classic technical indicator gave a rare bearish signal for the DJIA with the down move seen in January.  The Coppock Curve has turned down.  More importantly, it has done so after a second big top, which seems to be the important set of dance steps to mark a major market top.

Named for the late Edwin Sedgewick Coppock, his eponymous indicator was originally developed as a way to find the upturns from major stock market bottoms.  But with the right interpretation, it can also have other uses.

Coppock was a market analyst and money manager a few decades ago, and was awarded the MTA’s Lifetime Achievement Award in 1989.  The indicator that bears his name now was something he himself called his Very Long Term (VLT) Momentum indicator.  It was based on an idea which originated from a conversation Coppock had with bishops of the Episcopal church.  Coppock asked how long it takes a person to grieve, and to get over the loss of a loved one.  The answer was 11-14 months.

So Coppock incorporated that answer into his indicator, which combines 11-month and 14-month rates of change for the monthly closes of the DJIA, and then smoothes that with a 10-month weighted moving average.  Technicians who later took up the use of Coppock’s VLT Momentum indicator gradually changed the reference to “Coppock Curve”, to honor its creator.

When the Coppock Curve gets down to a very low level and then turns up, it signals an important long term entry point.  Coppock was a money manager who wanted to find the really great long term buy signals, and was not so much interested smaller swings.  The most recent such signal came in May 2009, just after the March 2009 bear market bottom, and it was indeed a great long term entry point.

After it gives such a signal, the subsequent uses of the Coppock Curve are not as clear cut, and it was not originally meant to offer other interpretations of the market action.  Tops are especially tricky, because sometimes a downturn from a high reading is a big bearish signal, and other times it does not mean that much.  This week’s chart highlights an interesting recent behavior of the market and this indicator, which is to give a two-step long term topping condition.  Or at least that has been the case in the limited number of market cycles since the late 1990s.

Now we have a downturn from a second top, as of the end of January 2014.  That completes this iteration, and arguably sets the market onto the course of a long term corrective move.  Given the math of the Coppock Curve, it will be a long time before we can get another upturn.

 

DJIA Coppock Curve

 

To help visualize this principle, the next chart compares the DJIA to the price level needed to achieve a reversal in the Coppock Curve, what I call the “Coppock Unchanged” value.

DJIA vs Coppock Unchanged level

When the DJIA crosses down through the Coppock Unchanged line, that turns down the Coppock Curve.  If such a move happens at a major top, it is a pretty unequivocal signal.  But crossings at other points can give whipsaw signals as with any other type of trend following indicator.  To get back up on top of the Coppock Unchanged line and turn up the Coppock Curve, the DJIA would need to close above 16238.07 at the end of February 2014, and that number keeps on rising.

So is this January 2014 downturn a legitimate signal, or just another whipsaw?  That’s the important question.  But consider that the DJIA has now completed the familiar 1-2 topping pattern seen at the major tops in 2000 and 2007.  And this arises at a time when the stock market still appears to be following the 1929 top’s price pattern, albeit with a much smaller overall magnitude of price movement, and the Fed is pulling away the QE punchbowl.  That adds up to a compelling case for a meaningful top and downturn.

You can calculate your own Coppock Curve series with this spreadsheet.  See also Calculating The Coppock Curve.


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Gold Breaks Downtrend, Sort Of

By Tom McClellan – McClellan Market Report

Which of these statements is true:

1.  Gold is still in a downtrend.

2.  Gold has broken its downtrend.

It turns out that they are both true, but only if viewed from the proper perspective.  The price plot of gold as priced in dollars is still below the declining tops line which dates back to late August 2013.  But the same line drawn on the plot of gold priced in euros has already been broken.

Gold priced in euros

So who’s right?  The short answer is that the euro price of gold has nearly always proven to be “right” when there is a disagreement between the two plots.  Such disagreement can appear in a few different forms, but the two I pay most attention to are (1) divergences, and (2) different trendline behavior.  It is the second category which is of interest now.

Gold prices have just started the process of building a pattern of higher highs and higher lows to define an uptrend.  But we already have a broken downtrend line on the plot of gold priced in euros.  A couple of other examples of trendlines on each plot are shown in this week’s chart, and you can see that in each  case, the euro price plot broke its downtrend line ahead of the equivalent line being broken on the dollar price.  Indeed, the leftmost example did not even see the dollar price break its trendline, although there was nevertheless a pop upward after the euro price broke its downtrend.

Whether this sign of a downtrend break is going to turn into a real live uptrend, or just a brief pop and fizzle like the last two, is not something that this difference in behavior tells us.  All it says is that there is a disagreement between the dollar price of gold and the euro price.  History says that the euro price is nearly always right during such disagreements, so I expect that to be the case again this time.


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Chart In Focus Archive

Is The Presidential Cycle Inverting?

Tom McClellan – McClellan Market Report

When Dorothy went over the rainbow, she found that everything was backwards.  The world had been colorized, munchkins were grateful that it was raining houses, scarecrows could talk, a lion was a fraidy-cat.  And there was a wizard who was in charge of the whole place.

A new wizard is about to be in charge of the Fed, and that factor seems to be making the stock market turn backwards and upside down.

Our Presidential Cycle Pattern is a representation of the market’s average performance over each four-year period from presidential election to election.  It is not just a message about what the president does, but also about the whole political calendar as influenced by Congress, the federal fiscal year, and other factors.  I like to measure it from the November election rather than from January 1, since the market typically starts responding to the election results as soon as they are known.  Usually that means right away; the 2000 election was a rare exception.

SP500 versus Presidential Cycle Pattern

The Presidential Cycle Pattern often gives a good model of which direction prices should go, and when turns are likely.  But as an average pattern, some years are better and some are worse.  And sometimes, the market pays attention to other factors besides what the politicians are doing.  We appear to be in one of those exceptional situations now. 

On average, the SP500 peaks in July of the first year of a presidential term, and then spends the next 16 months chopping sideways to downward until the mid-term election.  But the current market is ignoring instructions and just continuing higher, presumably in response to the Fed continuing its money-pumping into the banking system.  What is the problem?

More than just zigging upward when it is supposed to be zagging down, the market seems to be doing precisely the opposite of what the Presidential Cycle Pattern (PCP) says it should.  Here is a closer in look:

SP500 versus Presidential Cycle Pattern

Zooming in closer allows us to see that even the minor pattern of the SP500 is doing a pretty good approximation of exactly the opposite of what the PCP says should happen.  The stock market was supposed to be bottoming at the end of December, but instead it made a top.  Now in January 2014, the market is supposed to be moving upward, but appears to be chopping downward.

What are we to infer from this?  The PCP is all about the 2/4-year political calendar in Washington, DC, which has often had a big effect on pushing the market around.  But Congress and the White House are not the big forces influencing Wall Street at the moment.  Instead, the Fed seems firmly in charge.  A different agent might perhaps mean a wholly different schedule, wholly uncorrelated to the “normal” pattern.  But instead, forces are conspiring to bring about a seemingly precise inversion of the pattern.

How long the inversion can persist is not known at this point.  And the installation of Dr. Yellen as the new Fed Chairman adds an additional unknown factor into the mix.  I have seen the market make tops and bottoms early or late by a few days compared to the PCP, but I cannot recall seeing a complete inversion like what appears to be happening.  In other words, we have a wholly irregular market right now that is not following the normal rules.  It is instead following some other set of rules, and so extra caution is in order.

The 1929 scenario discussed in a Dec. 12, 2013 Chart In Focus article still appears to be “working”, and that chart was updated in a recent issue of our twice monthly McClellan Market Report newsletter, which is available to subscribers.  I do not think that we are in for an event of the same magnitude as 1929′s crash and subsequent decline, but the imposition of “crash physics” on the market could be a possible explanation for the inversion we are seeing.  Just as compasses have been reported to swing wildly upon entry into the Bermuda Triangle, perhaps the entry into a 1929-style crash scenario is flipping the market’s polarity for a while.  Caution is clearly in order at a time when the market just is not acting normally.


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The VIX ETN is Not Right For Investors

Tom McClellan – McClellan Market Report

In the Dec. 16, 2013 issue of Forbes magazine, the editors offer their list of “365 Ways To Get Rich” with their 2014 Investment Guide.  #100 on the list is this suggestion: “Profit from stock market volatility: Buy into a VIX futures fund and use wild, seemingly irrational swings as buying opportunities.”

The most commonly known VIX futures fund is VXX, the iPath SP500 VIX Short-Term Futures ETN.  And while it might be a useful trading vehicle for someone looking to trade extremely short term moves, it is a horrible idea for “investors“.

The share price history of VXX has a terribly negative bias, and it has ever since it debuted back in 2009.  VXX ended 2013 at a price of 42.55 (unlike SPY or GLD, VXX’s numerical price is not directly related to the numerical value of the VIX).  That is down huge from its March 2, 2009 high of 7449, when we adjust for 3 separate 1 for 4 reverse splits.

VXX - VIX Futures ETF


This persistent negative bias has to do with the nature of the VIX futures contracts that VXX invests in.  Most of the time, those futures contracts have a contango to their pricing, meaning that the price is higher the farther out into the future you go for a contract’s expiration.

The table at right quote table for VIX futuresshows the closing prices for VIX futures as of Dec. 31, 2013, extending out through the September 2014 contract (the furthest one currently open).  You can see that all of the contracts are priced higher than the spot VIX Index, and the further out you go, the greater that premium is.

As of this writing, VXX currently has its holdings divided between the January (F4) and February (G4) 2014 VIX futures contracts.  As the January contract nears expiration, the folks at iPath will have to replace it with the March contract (H4), and presumably at a higher price.  That price premium will then decay back down toward where the spot VIX is as the contract nears expiration.  So VXX shareholders are continuously being victimized by the “roll” to later expiration month contracts, with that ETN buying higher and then selling lower, and repeating.  That explains why the VXX’s long term “performance” has been so awful.

That does not mean VXX cannot be used for very short trading periods, when a rising VIX pushes up the prices of its futures contracts, and when the effect of the roll to the later contracts is not an important factor.  But for investors with a longer time horizon, owning VXX can be a hedge against a portfolio ever making any money.

Interestingly, just as the roll to later contract months can hurt investors in VXX, that same factor can help others.  XIV is an ETN sponsored by VelocityShares which is designed to move inversely to the VIX.  So if the stock market were to be making a short term price bottom, with the spot VIX up at a high level, then a trader could own shares of XIV to play the possibility of the VIX coming back down.  In other words, with a long position in XIV, a trader can be short the VIX.

And unlike VXX, which gets hurt by the roll to later contract months, XIV gets the benefit of that roll by shorting VIX futures at a higher price, and then harvesting the benefit of the decay as each contract’s price moves back closer to the level of the spot VIX Index.  It is for that reason that XIV has a positive bias relative to what the actual VIX does.

XIV - Inverse VIX ETN

You can see that XIV does move inversely to the VIX in the short run, and the magnitude of those movements can be quite violent.  But the longer term trend is decidedly upward, owing to the profit factor from harvesting the contango by shorting VIX futures contracts at higher prices further into the future.

Because the VIX has a reliably inverse relationship to the SP500, and because the XIV moves inversely to the VIX, many traders have figured out that they can use XIV as a leveraged proxy for the SP500.  Since January 2011, the daily percentage changes in the SP500 and XIV have a correlation coefficient of +0.82, and a “beta” (leverage factor) of 3.19.  In other words, if the SP500 were to move up or down by 1%, then the expectation would be that XIV would move by 3.19% in that same direction.  It does not always work out perfectly that way every day, but on average that is their relationship.

And in addition, XIV gets a performance enhancement by harvesting the contango as mentioned above.  Here is a chart comparing the SP500 to XIV for the past 3 years:

XIV versus SP500 2011-13

Since January 2011, the SP500 has grown 45%, but XIV has grown 178%, adding up to 33 percentage points of alpha over that 3-year period.  It has not been a very smooth advance though, as some significant drawdowns have occurred over that period.  Most notably, the big drop in 2011 took XIV down 74% from its high that year to its low.  There were not enough months of harvesting contango to make up for the negative effects on XIV from that big rise in the VIX.  So investors and traders really can get hurt.

But in a period of a rising stock market, traders who can enter and exit efficiently and who can stomach the higher beta may find the XIV a useful trading vehicle, turning the problem of the roll to higher price futures contracts to their advantage.  Please note: I am not advocating that anyone adopt such a trading scheme, and I never recommend the use of any individual securities or trading plans.  My purpose here is to help educate readers about how these products work.


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Chart In Focus Archive

A Review of Analogs

By Tom McClellan – McClellan Market Report

Have you ever lived through an earthquake?  I grew up in southern California, and lived through the 1971 San Fernando earthquake that fractured the Van Norman dam, knocked down several buildings, and generally caused turmoil.  I got to skip school for 3 days after the quake.

I now live in western Washington, and lived through the 2001 Nisqually earthquake, which knocked down some buildings in Seattle and generally caused great annoyance.

None of these compare to the magnitude of the big Tohoku earthquake in Japan, which spawned a tsunami that destroyed the Fukushima nuclear powerplant, and caused great damage to other areas of Japan.

And according to the Pacific Northwest Seismic Network, I have also lived through 201 earthquakes in just the past 14 days, although I did not even notice any of them.  An earthquake does not have to destroy a city to still be an earthquake.

This is an important principle to understand when we contemplate the topic of price pattern analogs in the stock market.  I attracted a lot of attention, and a lot of derision, when I wrote about the resemblance of the current market’s price pattern to that which occurred back in 1929.  This week’s chart updates that relationship, and we can see that the relationship has not broken correlation yet.  For as long as the correlation continues, it is interesting and potentially useful.  But anyone who endeavors to employ such an analytical tool should understand that all such pattern analog relationships break correlation eventually, so they should always be viewed with skepticism alongside the fascination we have for the pattern correlation and its (potential) message about the future.

I made that very point two weeks ago in my Chart In Focus article about the 1929 stock market pattern analog.  But some people could not get past the point that I had brought up the 1929 event, and they concluded that I was forecasting a huge crash, another Great Depression, and more.  That was not what I said, but the actual words I used and the analysis I offered seem to be secondary for some people, whose agenda is to be dismissive of others.  Why let the actual evidence and statements get in the way of a wonderfully inflammatory and critical story?

1929 DJIA versus 2013
The criticisms of that 1929 analog tend to fall into 3 general categories:

  1. The scaling is different, and so the comparison is wrong.
  2. The fundamentals are different, and so the comparison is wrong.
  3. Someone can take any 2 periods and put them on a chart to make them look the same.

 

Addressing point number 1, that the 1929 analogy is supposedly wrong because the scaling on my chart is not equivalent, and therefore the conclusions are necessarily wrong:  This stems from a prejudiced view that it is the magnitude which matters, and not the “dance steps” of the pattern.  The earthquake analogy should be sufficient to illustrate that identical magnitudes are not always the important factor.

Fred Astaire could dance the Charleston.  And a sumo wrestler could dance the Charleston.  It would admittedly look different in some ways, and it would definitely feel different from the standpoint of the dance floor.  But it would still be recognizable to an observer as the Charleston.

But to those for whom such logic is insufficient, let me offer a case history to illustrate how price magnitude is not really the important factor in governing the way that prices behave, and whether or not an analog is valid.  Most modern traders have at least heard of the big crash of 1987, but few remember the little micro-crash of 1994.  The total price damage in 1994, top to bottom, was just 9.9%, and yet the pattern itself strongly resembles what happened in 1987.  The magnitude of the 1987 event was much greater, both in terms of the volatility before the top and the severity of the actual crash.  And yet the “dance steps” look an awful lot like what happened in 1994.

analog comparing 1994 and 1987

If it was the total magnitude of the price decline which mattered, then we could have never discovered the pattern analog between 1987 and 1994, since the magnitude of the price change in each period was so very different.  But it is obvious from looking at the chart that there is indeed a genuine similarity.  And so if someone had been insightful enough to match up the pre-crash patterns between what happened in 1987 and what happened 7 years later in 1994, then that analyst could have potentially foreseen ahead of time what unfolded.

The 2nd argument, that the fundamentals are different now and thus the whole comparison is all wet, is something that I acknowledged and addressed in my article two weeks ago.  While it is true that the so-called fundamentals are different now, that factor has not stopped the current pattern from looking the same as the 1929 pattern up until now.  So why does that factor have to mean that the resemblance must stop working?  A lot of analysts think that they know which factors are the ones which matter.  But if wholly different economic and fundamental factors can still produce stock price patterns which correlate so closely (up until now), then my question is this: are those really the factors that matter?

And if those factors are not the ones that can explain the current price behavior similarity, then why are they the ones that matter for future price pattern similarity, or lack thereof?

Why do price pattern analogs ever work at all?  My answer is that human populations tend to fall into similar and repeating patterns of human emotional response, and this gets reflected in repeating patterns of price action.  This is the entire basis for classical bar chart pattern analysis.  Even though 2 different triangles might look different in some ways, or 2 different head and shoulders structures, the driving psychology behind the formation of such structures is largely the same, and tends to result in similar outcomes.

The 3rd argument is a peculiar one, asserting that a chartist can take any 2 periods, throw them together on a chart, and make them look similar.  This argument could only ever be made by someone who had not actually tried to do this.  Anyone with the least bit of experience in playing around with price data would know that this is not the case.  But such critics convert their hypotheses into assumptions, and then into “facts”, without ever checking whether they are actually true.  Prejudiced assumptions are not the same as facts.

Here is a case in point.  The 1987 crash was a lot like the 1929 crash in some respects, and different in others.

analog comparing 1987 and 2013, a comparison which does not work as well as the 1929 analog

Throwing together the current market pattern with the 1987 crash pattern results in a wholly unsatisfying comparison.  Both are in uptrends to this point, that much is true.  But there are so many points of pattern dissimilarity that I would never put this forth as representative of what is happening.  One can shift the patterns fore and aft, and it does not really get any better.

Perhaps the biggest point about analogs which their critics (and mine) do not understand is that all analogs eventually break up.  They don’t work in perpetuity if one extends backward off of the left end of the chart, and similarly at some point within the chart or off of the right end, the pattern correlation eventually breaks up.  Price patterns suddenly fall into correlation with a prior pattern, and they dance together for a while, and then they break up.  Or at least that has been the case in every single pattern analog I have ever studied.  So when we notice a similarity between now and the 1929 stock market pattern, that does not mean we can count forward 12 more years and expect the Japanese navy to bomb Pearl Harbor again at that equivalent point.  Life does not work that way.

When I find an analog that works, or seems to, it is great for a while, and then suddenly the nice relationship ends.  In my experience, the point of a loss of correlation usually arrives right at the point when I am counting on it most to continue working.  The key to not getting hurt by that breakup lies in knowing that a breakup in correlation could arrive at any time, and then to watch for and recognize the signs that it is happening.

Here is a great example, one that I have shown in past Chart In Focus articles in August 2013 and also in May 2013, and also in our McClellan Market Report and Daily Edition.  Apple’s price pattern over the past 3 years has very closely resembled that of Microsoft around the time of the 2000 Internet bubble top.

AAPL vs. MSFT pattern, showing breakup of correlation as of Dec. 2013

There was one notable misstep in the pattern leading up to the top, which is highlighted.  In April 1999, MSFT got knocked down by adverse news from its antitrust case.  AAPL’s share price did not undergo an equivalent drop at that point, because it did not suffer a similar adverse and exogenous input.  Afterward, the two patterns got back into step, and they proceeded nicely in strong correlation, that is up until just recently.

In the summer of 2013, we saw the first sign of pattern correlation breakup when AAPL made a higher low at a time when the MSFT pattern said that a lower low was on the script.  They continued to dance somewhat together for a few more months, but now in December 2013 the correlation appears to be pretty thoroughly broken.  What was a bottom at this point for MSFT’s  price pattern is decidedly not a bottom for AAPL’s price pattern.

So in summary, analysts and market participants should not expect more from such pattern analogs than they can offer.  But neither should we dismiss them as wholly without use.  The story does not have to be repeated in exactly the same way, or with the same magnitude.  We just have to be able to recognize the same dance steps being traced out to a satisfactory degree, and when we do, then we can see a model of what the future may look like, while also knowing that the correlation might break up at any time.


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