Expensive Misconception: Economic Growth was Fueled by Debt

Individual investors must watch out for the latest piece of nonsense from those preaching doom and gloom.

The statement is that the U.S. economic growth, particularly that of the last five years, has been artificially induced by debt.  The implication is that the economy will collapse like a house of cards when the debt must be repaid.  Those making these statements call this "incontrovertible fact", culminating with an issue of Time Magazine that will be the most expensive copy you every buy, if you read and believe this article.

At "A Dash" we have a key mission of helping individual investors.  Part of this work involves trying to develop some guidelines about how and where to find the right information.  We look for various sources on a topic and try to find the real expert.  Let us see how an astute individual investor might analyze this current proposition.

  • Look at people’s credentials!  When everyone is on one of those televised "debates" it may seem like they are all equal.  Sometimes those in the know are a bit less eloquent or glib than those who lack the relevant expertise.  This is especially true when the format emphasizes sound bites.  Our review of those focusing on debt-based growth is that they are usually non-economists–often journalists, bloggers, traders, or "global strategists".  They usually have a special agenda — promoting a book, or a web site, or their own trading positions.  Since they never did the formal work required to understand economics, they disparage those who have real expertise, claiming that it is irrelevant, or even a disadvantage!
  • See if the author knows the basics about the topic. With respect to debt, these writers choose to look at only half of the balance sheet.  They ignore assets!  Many of my smartest and wealthiest friends have elected to increase debt because of the attractiveness of various investments.  Corporate CFO’s learn to compare financing from debt and equity.  Is it surprising that in an era of low interest rates, many astute people have chosen to buy homes and to consolidate high-interest consumer debt into low-interest home equity loans?
  • Do a reality check.  Does the argument make sense?  Do we really believe that three years of double-digit growth in corporate earnings was achieved through stupid decisions by all of the leading corporate CFO’s?  Are the journalists and bloggers smarter and more knowledgeable than those running these businesses?
  • Compare the types of evidence.  Those making the debt argument paint a world where consumers are "spent up" and debt-laden.  They make anecdotal arguments about people who are the marginal borrowers, and act as if this is evidence of the mainstream.  They lack accurate quantitative analysis, often making outrageous projections using "black or white" estimates instead of using economic basics about supply and demand.

Considering the Facts

The household balance sheet is excellent, and has never been better.  David Malpass, an excellent economist with a great record, wrote as follows in December:

The multi-decade accumulation in U.S. household assets, not
reflected in the personal savings rate which excludes gains, is a key factor in the economy’s sturdiness and strong long-term prospects.
The U.S. household sector is showing rapid growth in most types of savings. At $27.5 trillion,  U.S. households have more net
financial assets than the rest of the world combined. By this measure, IMF data shows
Japan with $9.5 trillion, the UK 
$4.3 trillion, Germany $3.2
trillion, and   France
$2.6 trillion. Having added $1.5 trillion over the last four quarters,  U.S.   households probably also added
more to financial savings than the rest of the world combined.  This measure includes mortgages and credit cards in debt but
excludes houses in assets, so broader definitions would be even more favorable to the U.S. In the third quarter, household
net worth rose $776 billion to $54.1 trillion. Financial net worth increased
$479 billion to $27.5 trillion. Household liabilities rose $268 billion to $13.0
trillion.

Briefly put, household balance sheets are very strong and getting stronger.  If one were to add gains in home values for the last several years, the picture would be even better.  Please note that the gains in household net worth dwarf the alleged impacts from housing declines and sub-prime mortgages.  Do yourself a favor and bookmark this page.  The next time you see one of the doom and gloom articles, please check back here and compare the (exaggerated) numbers from anecdotes with the overall household strength.

Malpass concludes, both in this piece and in various others, that household net worth or home equity withdrawals are not key drivers of consumption.  He cites the low unemployment rate and the "rapidly rising personal income."

Anyone who has been paying attention to how personal savings and debt are measured understands the flaws in the highly-publicized reports.  The government clarified this years ago, pointing out the shortcomings.  Readers of James Altucher on theStreet.com’s RealMoney site learned this through his excellent analysis of these measures.

(Part of the "debt fuel" argument is about the U.S. national debt.  More on that in our next post.)

Reaching the right investment conclusions often starts with figuring out where to get the evidence and knowing how to find those who are expert.  Our guidelines will help with this.

Painting the Tape

Any trader or investor must consider the use of stop loss orders.  Since circumstances may arise that suggest the original decision was wrong, one must be willing to exit the trade at some point or to face major losses.  This is an element of trading discipline.

Placing a standing order risks a situation, especially in futures trading, where locals "run the stops."  If trading is slow, active floor traders may probe for and find the stops.  Everyone is looking at the same charts, and the placement of stops in a logical fashion may make one a victim of a small run, followed by a bounce back to normal levels.

Placing a "mental stop" can work if one is always watching.  Even then there is the problem of painting the tape.  The recent controversy over Jim Cramer’s comments, well documented by Trader Mike, have called attention to the dilemma.  Cramer talked about the potential for hedge fund manipulation of individual stocks and even the entire market, through aggressive selling, put buying, and influencing key media figures.

While we have no opinion on the Cramer controversy, it is timely to take note of a broader and similar question related to exchange rules, ETF’s, and selling on downticks.

Scott Rothbort wrote an excellent piece on this topic, now available on his blog, one of our featured sources.  The article may seem long and detailed, but that is because it is carefully written and covers all of the bases.  At "A Dash" we hope that exchange rulemakers will act to protect individual investors.  The markets carry a message, but we should hope that the rules make that message clear.

We hope that Scott’s views, reflecting his broad experience and wisdom, attract attention.

Quantifying the Economic Impact of Housing Declines

Everyone wants to know about housing and the economy.  Is the sub-prime lending issue something that will extend to other mortgage classes?  How much might home prices fall?  Will the impacts lead to reduced consumer spending and an even greater economic effect?

Doug Kass, the popular hedge fund manager noted for his skill in short selling, has been one of the leading voices on this topic.  His view is that this is a major economic problem and one that will affect the home prices and portfolios of individual investors. 

Writing today in Street Insight, the valuable premium service of theStreet.com, Doug does a "back-of-the-envelope" calculation of the likely housing effects.  At "A Dash" we are big fans of such an approach.  Trying to think about quantities and actual impacts is essential.  Market participants often have knee-jerk reactions to news, mostly because they cannot estimate the real effect.

To get Doug’s entire argument, you need to be a member at theStreet.com, but they might republish it later for the general public.  Since he is such a frequent and popular TV guest, you will also see it soon on CNBC.  I am quoting just one section, the place where he quantifies the likely impact of what we all read about every day:

Quantifying the Impact of Tightening Credit
I would conservatively
estimate that about 55% of the subprime borrowers, 25% of the Alt-A borrowers
and 15% of the prime mortgage lending borrowers will no longer be able to secure
financing for new homes because of tightened conditions. (This will produce
about a 25% drop in housing demand). Speculators and investors – who were
responsible for nearly 20% of all home purchases in 2004-06 – will also find it
more difficult to secure borrowings and it is likely that this buying category
will revert back close to their historical demand role of about five percent of
all homes. (This will result in another 10%-15% drop in housing demand).
Finally, end of economic cycle conditions (lower consumer confidence, slowing
economic growth and moderating job growth) should contribute to another 10% drop
in housing demand – as it has done historically. In total (adding the above
three influences), new home demand should fall off by almost 50% (vs. the
rolling 12- month average showing a 17% drop off in 2007) – even before the
effect of a market inundated by record foreclosures is considered.

What is Wrong?

This estimate will sound frightening and persuasive to most who hear it.  For students of economics, the problem leaps out.

A statement like "a 25% drop in housing demand" has no economic meaning.

Non-economists speak in terms like Doug.  Someone is either in the housing market or he/she is not.  A home is either on the market or it is not.  Completely lost is the concept that a buyer may not qualify for a loan of one size, but will qualify for a smaller loan.  Homes for sale at one price are withdrawn from the market if the price is lower.

The century-old concept  is shown in the supply-demand curve that one sees the first day of Econ 101.

Basic_supply_demand

As price declines, the quantity demanded increases.  As price increases, the quantity supplied increases.  The actual exchange price clears the market at the  quantity where the curves intersect.

When one wishes to describe underlying changes in either supply or demand, these are characterized as "shifts" in the curve.  Reduced demand, for example, shifts the downward-sloping blue curve to the left, meaning that there are fewer sales at a lower price.  Reducing prices shifts the supply curve to the right, increasing the quantity.

Is this News for Doug Kass?

Readers should understand that Doug Kass knows everything we have written here.  He has an MBA from Wharton and he certainly studied economics.  He knows full well that one cannot describe supply and demand as a binary function — either in or out.  One of the first things you learn in economics is that shifting the curve has a much smaller price effect than one would think at first.  So why is he writing this?

Conclusion

We wish we could provide a good answer about the impact of housing and mortgages on price and quantity, but we cannot.  To do that, one would need some data about the shape of both curves, at least enough to make an estimate.

We can say with confidence, however, that the Doug Kass scenario is extremely unlikely  The relevant curves would need unusual shapes and make massive shifts to have the impact that he forecasts.

Mortgage Availability and Personal Consumption: Round Three

Background

During my vacation, Doug Kass posted again on the topic of housing and personal consumption.  His analysis can be divided into two parts.  Part one "replied" to our analysis and part two elaborated further his reasoning about the connection, the causal model, and what he expected to happen.

Here is what he wrote:

Many,
like "Mad Money’s" Jim "El Capitan" Cramer, "Kudlow & Company’s" Larry
Kudlow and others, readily dismiss the potential spending consequences of
substantially less capacity in the subprime mortgage lending market and the
emerging trend by mainstream originators and lenders to reduce lending in the
primary mortgage market and for refinancing cashouts. Indeed, Jim takes the
subprime issue one step further, noting that the mortgage house of pain will
have a salutary market and economic result, as it will hasten the Federal
Reserve’s
path toward monetary ease. Shockingly (at least to me), many
others can’t comprehend the link between mortgage availability and consumer
spending, claiming that the correlation between the two variables (seen below)
is unclear.

Those wishing to see the entire statement can look here and here, but a subscription might be required.  I have quoted the section relevant to our work.

As you can see, "A Dash" is the unnamed "many" in Doug’s statement.  Well, we have been in worse company than Kudlow and Cramer!

As purported refutation of our analysis first posted here and with more information here, Doug merely posts the same chart again, with no effort to respond to our reasoning.

Kass_chartThere is a serious flaw in Doug’s analysis, and it plays upon the perceptions of both traders and individual investors.  The concept of correlation has a measurable statistical basis.  It is not a matter of opinion. It is a fact.  We believe that the chart is an optical illusion.  Here is a familiar example, one that most readers have probably already seen:

F_1826opticalillusion1 You can either use your eyes to tell you which line is longer, or you get a ruler and find out the truth.

Readers looking at the Kass chart see with their eyes a strong correlation.  This is because the key elements of the chart have been pushed together to emphasize two key points.

To our surprise, readers at Calculated Risk commented both on our site and theirs that the areas we described as "no fit" in our chart actually showed a strong correlation.  Take a look again at our "no fit" chart.

Kass_chart_showing_fit
Readers saw what they called the "Batman" segment as quite similar.  They also were undisturbed by the periods where the two lines ratcheted along, out of phase.  This is a trick played by the human mind, the most powerful computer.  Our minds take two patterns and look for similarity.  Sometimes that leads us astray.  Correlation means that the movement in one variable corresponds in both direction and magnitude to the other variable–and at the same time.  The fact that the two lines both have "Batman" characteristics is unhelpful to the trader unless the movements directly correspond.

Since this is difficult to see visually, it is important to use statistical techniques to measure correlation.

An Aside

To put this in the proper perspective, we should remind readers of our mission at "A Dash."  We review and analyze Wall Street Research where we find interesting errors.  We have no shortage of candidates.  We do not have a mission linked to a particular market viewpoint.  We choose our market stance based upon the evidence we see.

In the Doug Kass case there is a proposition that historical data show a strong correlation suggesting that personal consumption expenditure declines are imminent.  Using traditional statistical methods, we find that the data cited do not support this conclusion.  It does not mean that Doug is wrong in his ultimate conclusion — just that his frequently-cited chart does not support his viewpoint.

In the areas of the chart that we cited as "no fit" the correlation is much lower or non-existent.  The entire strength of the chart depends upon a few data points.  If readers do not see this, then we have failed in our mission to educate about the danger of visual chart interpretation.

Going Back to the Classroom

There will always be some who make up their minds first and then see everything as evidence.  We cannot reach them.  It was surprising to us how many readers insisted on the correlation, based upon this chart.  What were we seeing that they were not?  To improve on our analysis in the first two posts on this topic, let us turn back to the yellowed notes of classroom instruction from decades ago.  To see why this is not a  strong or useful correlation, one must start by understanding what that means.

The concept of correlation is based upon a linear relationship between two variables.  With modern software, it is easy for anyone with access to the underlying data to calculate the correlation and statistical significance.  But that is not enough!

The concepts are from an undergraduate introductory statistics course where correlation and regression are two of many topics.

We present here four different data sets, all showing the same statistical characteristics — averages, standard deviations, slope coefficients, etc.  The dramatic demonstration for students was that it was not enough to look at the numbers, one also had to consider a scatterplot of the data.  If the data did not fit a linear model, the entire concept of correlation was called into question.
Regression_plots

In only the first case is the regression equation a good specification of the model — a way of saying that the description and correlation really reflect the data.  In the case where the relationship is curvilinear, this tells the researcher that there is a missing independent variable.  The bottom two cases show a very strong relationship that is distorted by the presence of a single outlier, an unusual case deserving further study.  It is quite obvious that the regression equation is not a good description of the data in the bottom cases.

In real life, examples are never as clear as the pure cases from the classroom, but the Doug Kass chart comes pretty close.  We showed, in the chart repeated below, the scatterplot for the hypothesized relationship. 

Kass_chart_scatterplot_with_regress
When the optical illusion of the time series is stripped away, the reality is clear.  This is mostly a cloud of data with a few outliers that have a strong effect on the equation.  It is not really a good candidate for a linear model, and that means that the term "correlation" is meaningless.  (Those who really want to understand this should also read the prior two articles on the topic.)

The Real Conclusion

The data show that for a few quarters in the early 90’s a decline of over 15% in mortgage availability occurred at the same time as a decline of about one percent in personal consumption expenditures.  There was a recession that probably caused both effects.  The data include no other examples of big declines, and the smaller moves are all part of a data cloud.

If someone told you this in words, you would not find it very persuasive.  Somehow the chart has an overpowering visual effect.  Do not bet real money on what you think you see.

Economic Prospects: Some Strong Evidence

Economic growth and inflation prospects are always crucial for anyone interested in forecasting the stock market.  With so many market participants expecting a recession — and not just a little one — the question has special salience.  At "A Dash" we resolve such questions by finding the real experts.

Someone who shares this quest for expertise is Gary D. Smith.  He writes an excellent daily diary on theStreet.com’s professional site, StreetInsight (subscription required), a service that we find quite valuable.  Like Doug Kass, Gary manages to post daily thoughts about the market while managing his own fund.  He also writes a public investment blog, Between the Hedges (featured in our blogroll) that is one of the top resources for those actively trading the market.  Gary’s approach is top-down, looking for growth at a reasonable price.  His daily moves reflect technical considerations as well as breaking news.  His lively interchanges with Doug Kass help thoughtful readers to focus on crucial issues.

Gary reported today that the Economic Cycle Research Institute’s weekly leading economic indicators were flat, but the ten-week moving average was at a high for the cycle.  Regular readers of "A Dash" know that we are big fans of the ECRI because their methods have avoided "false positive" recession predictions in the past.  The current report is consistent with the most recent public interviews of Lakshman Achuthan on CNBC (March 15, 2007, subscription required).  Achuthan pointed out that inflation indicators like the PPI were coincident indicators, without leading power.  Their leading indicators showed a slight downtrend, without any forecast increase in inflation for the next three quarters.  On the same interview Michael Darda of MKM partners observed that recession forecasts were overblown.  His research showed that a recession had not followed a Fed tightening cycle in 45 years when the tightening stopped at low interest rate levels, like the current 5.25%.

This assessment is, not surprisingly, consistent with the statement from the Fed, relying on their staff of hundreds of PhD economists.

We find this evidence more persuasive than the arguments of those claiming to see problems in housing and subprime mortgages.  Since everyone knows about this issue, the only question is which analytical method is better at forecasting the impact.

Since few investors or traders have the individual competence to make their own forecasts, finding the real experts is crucial.  That is what we do at "A Dash."

Disciplined and Regular Portfolio Review: A Best Practice

A regular review of holdings is an extremely important part of investment management.  While every manager follows daily news, it is a best practice to ask whether new candidates are better than current holdings.

In our portfolios we sell stocks when our original investment thesis breaks down or when the stock appreciates so much that it no longer meets our tests for potential return.  We also maintain a watch list of potential buys — stocks that might be preferred to our existing holdings, on a risk/reward basis.  Even when following this approach, it may be difficult to sell a stock that has not fulfilled its promise in favor of one that now has better potential.

Individual investors and traders alike can learn from the process described by David Merkel in his portfolio review series.  David is a long-time contributor to theStreet.com‘s RealMoney site, and he is one of our mandatory daily reads.  David has great skill and experience for insurance stocks, including names that many find challenging to evaluate on traditional metrics.  We have learned from his writings and expect to add some of his recommendations to our holdings very soon.

David has recently begun sharing his work with a broader audience through his excellent blog site, The Aleph Blog, now added to our list of recommended sites.

In particular, we recommend that readers look at his portfolio review process.  More generally, investors should set aside some weekend time and browse the entire site, which includes many of his best articles from RealMoney.

Misusing the Most Powerful Computer

There is a perfect storm tempting many traders and investors.  The increased power of computers, the easy availability of data, and the user-friendliness of software have made it possible for nearly anyone to backtest trading systems.  The result is that people with no background or training in research methods are using the most powerful tools, but not knowing how to do it.

The sad result is the story of the system trader we covered in an earlier post, and the need for a scientific method for using the tools.  One of the comments to that post did a nice job of summarizing the best approach — saving lots of out-of-sample data, making sure the method works in different eras and markets, testing equity curves during the relevant periods, etc.

Here we introduce a new idea, one that I have never seen before.  Perhaps readers will alert me to some other mention of this notion, so that I can cite it (since this is a blog about a book).

Suppose I told you that my computer discovered a certain technical "set-up".  Let us say that it was a double bottom, followed by a five-month rally in the stock or index.  The wise system tester might ask how many such instances there were, the comparative results, and expect an out-of-sample test after discovering an apparent relationship.  Such are the methods used by system gurus like James Altucher (whose book on trading systems we recommend in our reading list) and our own Vince Castelli.

Computer systems are evaluated with scientific skepticism and rigorous demands on testing — and rightly so.  That is the world of the system trader.

Most market participants do not have the requisite skill set to evaluate systems.  They do, however, have another "skill" that is exceedingly dangerous — looking at charts.  Everyone believes in his own ability to look at a chart, see trends, see breakouts, and see correlations.

They use the most powerful computer — the human mind — to follow a process vaguely similar to the development of a trading system.  The human analyst takes the current market situation and seeks out some past situation that seems similar.  Instead of using a computer technique, the human comes up with an old chart and compares it to the new one.

There are multiple problems:

  • No one asks how many such "set-ups" there were, or what happened in all of the cases.
  • There is no question about whether there are enough cases to form a conclusion.
  • There is no out-of-sample testing.

The effect on the average reader, including market professionals, is very powerful.  The charts seem quite similar.  It is very much like the behavioral finance concept of anchoring, where a totally irrelevant fact predisposes humans to accept the fact as a base point for reality.  In the behavioral science literature a random number is often used as the base point.  Even though people know that it is random, it still has a powerful effect.

In the case of the old chart, the human parses through history to find the desired example.  Since almost no one understands how to test this, but all think they know how to read charts, the effect is powerful.  There is often little effort to compare the fundamental similarities and differences between the two time periods.

Sometimes the chartist offers several different stocks or indices from the same period.  Since the indices are all highly correlated, this actually provides no additional information, but it seems to make the argument more powerful.

While on vacation last week I read an analysis of this type at Barry Ritholtz’s site, The Big Picture.  Barry, who is more skilled than most on behavioral finance traps, thinks that this is relevant to the current market.  In fact, Barry cites similar work in Barron’s.

At "A Dash" we believe that such comparisons lack the requisite testing, the sort that we would routinely perform on technical predictions.  Barry is doing what everyone does, and he does it well.  Our objection is that the method is unsound.

Expert humans, even the most astute fund managers, are unduly influenced when someone does what we call human data dredging.

Since the influence of this is powerful, it provides an opportunity for those who reject the approach.  Let us be completely clear.  We are not saying that the conclusion is false.  Our position is that the analysis provides no useful additional information, yet it influences many in a specific direction.

One of the major themes at "A Dash" is that astute Wall Street professionals are subject to the same behavioral finance problems as individual investors.  Knowledge of the literature does not necessarily inoculate one against the effects.

The lessons for investors and traders alike is to view such comparisons with the same skepticism they would have for computer models.  If many others are influenced by the questionable information, the contrary trade is indicated.

The Psychology of Fear

When markets become volatile (the media euphemism for declines) fear often takes hold.  In this environment investors and traders who are operating on "feel" or advice from media sources often react emotionally.  Dr. Brett Steenbarger, who writes extensively and expertly on these subjects identifies the operating elements today in his article on how to handle volatile markets.  As usual, Dr. Brett draws upon scientific literature, in this case from neuroeconomics, to describe the biases we all face.  Everyone should read his article and follow his links to get a better understanding of the problem.  Whether or not one agrees with our particular approach, it is important to proceed from reasoning and not from emotion.

Last week we addressed this problem, but it deserves further analysis.  We look today at the general issue, but will try to provides some specific stock examples in future posts.

How Fear Develops

  1. There is a background of frightening forecasts.  This goes with the territory.  Some of those writing have short positions and want to cash in.  Others are promoting their blog or their book, catering to a specific audience.  Even though the forecasts may have been incorrect for months (or even years) their audience is primed.
  2. Something happens that seems to validate the hypothesis.  Quantification and formal modeling is not necessary.  Anecdotal evidence is sufficient to gain attention.
  3. Mainstream media pick up the story.  This is a natural result of the need to "explain" any market move.
  4. Technical analysts point to the market moves as validation of a new trend, breaking of support, and deep insight into the future.  It is interpreted as a message from the market.

In short, an initial move in the market (or in specific stocks) is interpreted as a validation of a theory.  This can take place even when the theory itself has limited factual support.  (Last year we described an interesting example of this knee-jerk reaction in a specific stock, Intel, when media coverage presented an opportunity.)

The Current Issues

The current selling relates to two major issues, the sub-prime mortgage market and the yen "carry trade".  The question for a rational trader or investor is whether these are phenomena that are limited and localized, or whether the issues extend to many stocks and the market in general.

Those promoting fear suggest that the problems of a few companies that were too aggressive in lending is a harbinger of overall economic weakness.  They do not have a formal model or any quantification, but use slogans like "a fungus among us" and imply that that major financial institutions are threatened by bad loans.  When management of these firms assert that their loan portfolios are sound, the fear promoters are skeptical.  They believe that CEO’s ignore Sarbannes-Oxley requirements and risk legal sanctions to hype their businesses.  They see the worst, even when earnings records are solid.  These vocal bloggers and pundits are mired in the 2000 era — fighting the last war.

Finding some Clarity

At "A Dash" we pride ourselves in finding the real experts on any topic.  Often this means placing little reliance in bloggers who take pride in never studying economics and looking to those who have a proven record and a great feel for current conditions.

Rich Karlgaard’s column today presented a fresh piece of analysis from David Malpass.  When he gets permission to reproduce Malpass’s proprietary work (which we always read and often quote), everyone should jump at the chance to read the entire piece.  It is well worth the time.  Here is the key quotation:

We disagree with the view that
the U.S. expansion is fragile due to housing, mortgages or past rate
hikes.  Since 2003, housing-related industries have accounted for only
4% of the 7 million in net new jobs (including residential
construction, mortgage brokers and Realtors).  Mortgage equity
withdrawals have substantial correlation to net acquisitions of
financial assets but little correlation to consumption (as shown
clearly in 2006’s weak MEW and weak net acquisitions versus strong
consumption growth).  The economy grew steadily through 17 interest
rate hikes, arguing that it may turn out to be sensitive to the level
of interest rates but was not very sensitive to rate hikes from low
levels.

For anyone who chooses to look at evidence rather than to react emotionally, this means that the market is punishing stocks that are sensitive to economic growth.  (Obvious full disclosure:  We own such stocks and we are buying into the decline).

Malpass wrote another piece, not reported on the Karlgaard site, showing the relatively small proportion of global liquidity linked to the yen carry trade.  While it seems obvious to us that those borrowing in yen and using eight or ten times leverage are buying bonds, not investing in Caterpillar or FedEx, the current market reflects a different viewpoint.

Forming a Plan

Mr. Market is offering investors an opportunity to buy good companies at discounted prices.  My most astute long-term investors are adding to positions.

For traders the problem is trickier.  Part of the reason for the current decline is that traders are waiting to see when these stocks — and the market — will catch a bid.  The trading problem involves guessing the psychology of others as well as being right on the fundamentals.

It is still helpful for the trader to understand the dynamics and be prepared for action. 

Housing and Recessions: A Proposed Relationship

Floyd Norris, the noted financial columnist for the New York Times, has recently begun blogging in addition to writing his regular column.  He recently posted some research he had conducted on the housing market and recessions.

Norris takes a three-month moving average of housing starts to smooth out the volatile series.  Next he notes that we are currently in the eleventh month of decline in this moving average.  Finally, he looks back at all of the other times there were eleven months of decline, going back as far as he had data (1959).  Here is what Norris found:

1. November 1973 was the 11th month. A recession began that very month.
2. April 1980 was the 11th month.  A recession began in January of that year.
3. November 1981 was the 11th month. A recession began in July of that year.
4. February 1991 was the 11th month. A recession began the previous July.

These days, almost no one thinks a recession is looming.

While he does not quite say it, the implication is that an eleven-month decline is an indicator of a recession around somewhere.

This would be a good starter problem for an undergraduate class.  Students who had the benefit of reading (my favorite professor) Neil Browne’s book, Asking the Right Questions:  A Guide to Critical Thinking, (featured on our reading list) would find this an easy problem.  Perhaps Scott Rothbort, who recently offered some great insights about the housing market, will test this question on his class at Seton Hall.

The astute readers of "A Dash" have, no doubt, immediately spotted the main issue.  The popular bearish argument is that a decline in housing will weaken the economy enough to cause a recession.  In Norris’s examples the recessions all occurred either before or (once) contemporaneously with the housing decline.

Are we surprised that during a recession, spending on housing — and many other things– is reduced?  The housing decline is associated with the recession.  Association does not show causation.  If one had to guess, the housing decline is probably a result, not a cause in Norris’s examples, both from logic and the timing.

In short, Norris’s little exercise has the look of sophisticated analysis — smoothing of data, moving averages, the same eleven-month time period, and the fatal recession.  Although he has a big audience, I was hopeful that Mildred, one of my investors who is easily influenced by this sort of argument, would not read about this "relationship".

My hopes were dashed when I saw that Norris had already gotten a boo-yah from Barry Ritholtz on The Big Picture.   I know that Mildred watches Barry on TV and also reads The Big Picture.  I can expect a phone call soon.

No one knows when the next recession will occur, nor whether it will be induced by problems in the housing market.  We can say with confidence, however, that the Floyd Norris four-case analysis does not help us in making this prediction.

The Most Expensive Investment Research of 2006

I had an interesting call this weekend from my most astute investor.  Since he wants to be anonymous, let’s call him "Bob".  Here is our conversation, with a few pointers and charts included — items that he requested I send him by email.  [Readers will benefit from taking the time to follow the links to past posts.]

Bob:  I enjoyed reading your research reviews last year, and I have a question.  What was the most expensive Wall Street research for 2006?

Jeff:  Do you mean the report that had the highest price tag?

Bob:  (chuckling) No!  I mean the one that cost people the most money.

Jeff:  Ahh.  Good question and the answer is easy.  The research on what happens when the Fed is trying to achieve what people call a "soft landing."

Bob:  That would not have been my guess.  I was thinking the election cycle or something.  What was so bad about the Fed and the soft landing.

Jeff:  It was a perfect storm for harming the individual investor and average trader.  First, the original work was a poor research design, but subtle enough that it took some skill to see the problem.  Second, it came from a big name firm so it got a major play in the media – basically accepted as gospel on CNBC.  Third, the concept was elusive, and subject to misinterpretation.  Finally, the leading blog sites gave it a big play.  The result was that anyone listening missed a big rally.

B:  You sound like a professor.  But I asked the question, so what was wrong with the research.

J:  Lack of data is the main problem.  There have not been enough Fed tightening cycles to draw sound conclusions.  You have to reach too far into the past, and then you still do not have enough cases.  The researchers used all of the data they had without regard for relevance.

A technique used in Research Design 101 is to look at a time series of results.  The reported research results assumed that the Fed is no better now than it was in the Hoover Administration.  This is typical of Wall Street.  Fund managers all figure that they are smarter and better.  In any other field of study we expect that there has been great progress – nuclear power, space exploration, biotech, DNA matching, weapons development, better airplanes and cars – you name it.  Despite this, the Street thinks that decades of Nobel Prize winning research in economics and the development of computer modeling make no difference.  Criticizing the Fed is a game, like second-guessing football coaches.

Take a look at some real data on recessions.  A good question is what proportion of the time the economy has been growing versus in recession.  This chart shows that by decade.
Recessions_by_decade It is readily apparent that the economy is now more resilient.  But the chart does not tell the whole story.

Fed tightening cycles have also had less impact on stocks.  Recessions — whether or not they result from tightening cycles — have had little impact on the overall earnings prospects of the market, as measured by earnings expectations for the S&P 500.
Sp_500_earnings_timeline_1
Recessions, when they occur, are briefer and with a smaller impact.  This is the best way to look at the data — as a continuous process of economic performance.  It reflects many factors, not just the Fed.

Even if one looks at the data from the perspective of a discrete series of Fed moves — the wrong method in my view — the stock market effect is quite different from that suggested in the original research.

After_the_fed_3If one  looks at "recent" data — say from the last thirty years or so — the  result is much different  from the conclusion drawn from the  "dead ball"  era used in the original research.  If you are trying to forecast, would you think that thirty years was far enough back to go?  In running your business, would you look at the recent trend or go back to the 20’s or the 50’s?

B:  I remember hearing and reading about this repeatedly.  Everyone said a soft landing was nearly impossible.

J:  That’s right.  We pointed out these problems in mid-August, but the media was running with the story.  CNBC quoted the study repeatedly.  Major writers featured it.  The big-time bearish blogs called it a myth.  They utilized pejorative symbolism which frightened the individual investors.  I warned about this out on "A Dash" and also in individual conversations.

B:  So those who listened to the mainstream media and the blogs lost out?

J:  Big time.  Those who did not understand this Fed cycle  have missed a big rally.  Even if there finally is a correction or recession, stocks may not dip back to the August levels.  Look at the chart.
[click to enlarge]Sp_500_6_months
Investors have missed 15% in the S&P 500 and 20% in the Nasdaq while waiting for a Fed-induced correction.  (Meanwhile, Vince’s intermediate-term models gave us a buy signal on August 8th.)

Even if we eventually have a correction or a recession, the pullback may not take us down to the August levels.

B: What do you mean about "understanding this Fed cycle."  You are not suggesting that this time is different are you?  We all know that is a mistake.

J:  When the tightening starts from a level that is far below "neutral" and proceeds very gradually to a point that is slightly above neutral, it is different.  It is not like a tightening cycle where inflation was already out of control, and the Fed needed to choke the economy.  I repeat that there are not enough cases for a quantitative analysis of tightening.

B:  Personally, I have followed your advice and remained invested.  Some of my friends have not.  What would you tell them?

J:  I am not surprised that many have missed out.  The misinformation on this subject reached many — perhaps millions of investors, while "A Dash" has a loyal readership best measured in hundreds.  That is actually a good thing for those who are just now getting involved. Most still do not understand, and we will see some fund managers chasing for performance.

Despite the rally, I feel that most of the opportunity remains.  Stocks have only begun to catch up with the record run of earnings growth.  I have tried to illustrate that in my valuation stories on "A Dash".

B:  I have been reading that earnings are going down, reverting to the mean.

J:  That just means that we are returning to normal growth instead of exceptional growth.  Don’t confuse a lower rate of growth with an actual earnings decline.  Take another look at the chart of forward earnings.

Meanwhile, I’ll try to cover the subject of misleading articles on earnings.  The list of topics grows….It is more difficult when writing fresh analysis.

And our conversation reverted to the normal subjects — sports, bridge, poker, kids, and good restaurants.  It is nice to have some astute investors who ask good questions.