Mortgage Availability and Personal Consumption: Round Three


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:

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
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.

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.

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. 

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’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‘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

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.
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.

Build your own trading system? Hmm…

Not so long ago, designing a trading system was viewed as a highly technical problem that required talented developers, special background, and great skill.  An individual investor would no sooner build a trading system than he would a refrigerator.

Advertisements for brokerage firms signal that this has all changed.  Several of the leading discount brokers now bombard television watchers with the same message:  You CAN do this at home.  One firm explains how easy it is to develop and back test strategies with their online software.  Another uses rotoscoped images to capture the indignation of some investors who are all smarter than their brokers.  A third shows investors making smart moves while taking a minute away from running the restaurant or the construction site.

At "A Dash" we have tried to show the challenges in developing systems and interpreting data.  Making powerful software simple to use and data more readily available just makes it easier for non-experts to lose a lot of money.

One graphic example is better than many admonitions from us.  Check out the story of a rookie prop trader and his foreign exchange system, as reported by Tyro.  Tyro’s friend was intelligent and methodical.  He did a lot more work than most and took what he believed to be a cautious approach.  After a month of awakening at 5 AM to test his system through paper trading, he was ready for the real show, going carefully with 2% positions.  You can guess the result.

He did many things right, but it is so easy to go wrong.  Go to Tyro’s site and read the entire well-told tale.  Thanks also to Trader Mike for highlighting  story.

Aspiring system traders should read (at least) Fooled by Randomness and the Portfolio Management Forumulas, the first book in the Ralph Vince "trilogy" (both featured on our recommended list at the right).  These books will explain many of the traps as well as some good methods for testing a system.

If you do not find these books to be real page-turners, (we did), then system trading is probably not for you.

Enhancing Trader Performance by Brett N. Steenbarger

At "A Dash" we have been reading Dr. Brett Steenbarger’s recent book, Enhancing Trader Performance, now featured on our recommended list.  (Some time spent in air travel is always good for serious reading.)  Our audience will find this book quite helpful.  In general, we feature work as we specifically cite it in our own analysis.  There are so many applications in this book, that we will be pointing to it repeatedly.

For now, let us consider a very general review, showing who will find the book helpful and why.

Greatest Strengths

The greatest strength of this work is the authoritative combination of theory and practice.  Dr. Brett draws upon a body of theoretical literature showing a logical progression from building competence, moving from competence to expertise, and using that expertise to become successful.  It is the whole package presented by a great writer who understands the theory.

Unlike many works where the strictly academic approach renders them inaccessible to most readers, this book is fun.  Each theoretical step is salted with examples from those who have achieved great success by implementing the principles.  The reader learns about how noted athletic performers like Dan Gable, Wayne Gretzky, Muhammad Ali, and Lance Armstrong employed the specific methods described.  This does not mean, of course, that these athletes had all read the relevant literature.  Instead, they learned or developed key methods on their own.  Nonetheless, their success demonstrates the power of the theories.

For traders, another great strength of the book is the application of theory to practice.  Because of his personal work in observing and helping traders with their problems and methods, Brett’s writing really comes to life.   Anyone has done some trading will recognize the characters in themselves or someone they know.  Any trader has experienced many of the same foibles as the featured characters, who are all real traders. The reality of the examples gives the lessons
and advice the ring of authenticity.

Wider Applications

While the book is aimed at a trading audience, it is quite useful for anyone engaged in competitive activity where performance is measured.  This is not just about trading.  Those competing in athletics or games of the mind will find the work most helpful.  Our own experience involves competing and coaching people in competitive activities like bridge, backgammon, chess, sports handicapping, poker, and debate.  Nearly every chapter has lessons for those striving for success in these fields.

An Important Lesson

There are also important lessons for the individual investor.  So much of today’s marketing makes it seem easy for anyone to beat the market.  Enhancing Trader Performance shows that learning the key lessons to become successful is hard work.  It requires a level of commitment that many would not have.  It is better to know this before starting, than to learn the hard way.


Briefly put, this is a must-read for traders and for system developers.  It is also recommended for those engaged in any competitive activity.  Finally, it is useful for individual investors.  Taking the time to understand the problems faced by top traders is the first step.  Those unwilling to make the time commitment to read and learn are unlikely  to achieve long-run success.  Read this book first!

Real Estate Sucker Bet

The major problem facing investment advisors is helping clients with
asset allocation.  Your client is intelligent and engaged.  The problem
is that they are focused on what worked last year, and your job is to
help them with what will work next year.

Our company has an internal ranking of pundits and advisors.  John Rutledge is one of our good sources.

Link:  Real Estate Sucker Bet

I was on CNBC’s Closing Bell with fellow guest and old friend Brian
Westbury to discuss the housing market on Monday, July 5. Brian and I
have known each other since the Reagan White House. He’s a great guy
and first class economist–one of the most …

I’ll expand on the housing theme in future posts, but we believe Dr.
Rutledge has it right on one of the major questions.  People have the
idea that real estate cannot decline in value — a dangerous notion.