Stock Exchange: How to Use Backtests Effectively


Everyone interested in managing their own money ought to keep an old idiom in mind: if it seems too good to be true, it probably is. Unfortunately, greed is a powerful motivator. It’s tempting to see a new model with an incredible backtest and think this could be the answer.

Experienced investors know that there’s often a drastic change between a model’s backtest and its first live run. You can usually find that point by checking for where the 45-degree angle increase in value drops off into sideways movement (and generally underperforms the market).

This week, we’ll take a deeper dive into how you can minimize these problems using professional techniques.


Our last Stock Exchange revisited a common theme: making stock picks according to a set time frame. Our models suggested finance and software stocks in the short-term, and energy for the long-term.

Let’s turn to this week’s ideas.

This Week— *crickets*

We usually arrive to find the gang happily enjoying their weekly poker night. Instead, all we’ve got are Felix and Oscar’s weekly rankings with a “gone fishin’” note on the counter. Strange behavior.

We decided to give Vince Castelli a call to investigate. Vince is our modeling guru, a brilliant scientist who spent the bulk of his career as a civilian employee for the U.S. Navy. During his time there, he’s had hands-on experience with modeling techniques vital to national security – not something you can find in the classroom. He knows these models better than anyone; after all, he designed them.

Jeff: Vince! What is this about giving everyone the week off?

V: I didn’t give them the week off. There were new no new fresh signals.

J: Is there something wrong with the gang? They encompass five different methods. How can there be no fresh ideas?

V: A key feature of all models is recognizing the best times to trade. When volatility increases trades become less predictable.

J: What do you mean? The VIX is lower this week. Volatility is down.

V: That measure is for amateurs. Trading volatility includes both upside and downside. That bogus fear gauge emphasizes only the downside. Predictions are affected by extreme movements in either direction.

J: Since we do not have current picks to feature, maybe we could discuss how you developed these models.  There was an excellent recent article from Ben Carlson about what you cannot learn from a backtest. It reminded me of the TV ads suggesting that anyone can discover a system and trade their way to a fortune.

V:  If only it were that easy.

J:  Ben’s description made me think of some suburbanites wandering into the woods with massive chain saws.  The power of the tools far exceeds their skill in using them.

V: I see it all of the time.

J:  I would like to take up a few of Ben’s points and get your reaction.  How about this:  How many bad backtests came before the good ones?

V:  This is a great question.  Most people do not know the right questions to ask the model developer.  That one is crucial.

J:  How would you answer?

V:  Our method preserves multiple out-of-sample periods.   We develop models on our development data, saving pristine time periods for the test.  We verify that the strength of results continues.  You cannot just look at backtest results; you must know the developer’s method.

J:  Here is another good point — Data availability at the time.   Isn’t it easy to “peek ahead” or to exclude data from failing company?

V:  It certainly is.  You need to have data that includes the failed and merged companies.  The average person at home will not pay up to get this.  It introduces a deceptive, positive bias.

J: Ben also raises an interesting point about friction.  He writes:

It’s almost impossible in a backtest to completely account for costs and frictions such as taxes, commissions, market impact from trading, market liquidity, etc. Sure, you can estimate these frictions, but you never truly understand how these things will affect your bottom line until you actually have to execute buy and sell orders.

V:  This is the first point where I really disagree with him.  Why is it almost impossible?  You should definitely include commissions and a slippage factor.  If your trades are a small percentage of the market volume, the impact from trading is negligible.  Taxes vary by the type of account and the investor.

J:  Interesting point!  “Almost impossible” is strong language.  For someone who knows the ropes, this kind of test might represent real edge.

V:  That is what I do with each of my creations!

J:  Some of Ben’s other points relate to psychological factors.  The trader bailing out of the system in the face of losses.  Or concern about real money.

V:  That is strictly a matter of confidence in the system.  If it has been developed properly, you should not do a lot of fretting.

J: Thanks for joining us, Vince. I’m sure your comments will help readers make more sense of our series.

V: Any time!


One important point was not mentioned in Ben’s article – simplicity.  The temptation for the untrained modeler is to introduce as many variables as possible, hoping to find correlations that others have missed.  What they find is misleading. Computers are powerful enough to discover apparent links between variables when there is actually no relationship. A great model uses as few variables as possible.  The backtest may not seem as good, but the real-time trading will be much better.

Quantitative modeling is an extraordinarily complicated field. In some ways, the way to find success here is similar to finding success in the investment world as a whole. Find the right experts, learn their methods, and try to make sense of the data for yourself. Backtesting can be effective or dangerous – it depends on the skill of the developer.

Background on the Stock Exchange

Each week Felix and Oscar host a poker game for some of their friends. Since they are all traders they love to discuss their best current ideas before the game starts. They like to call this their “Stock Exchange.” (Check it out for more background). Their methods are excellent, as you know if you have been following the series. Since the time frames and risk profiles differ, so do the stock ideas. You get to be a fly on the wall from my report. I am the only human present, and the only one using any fundamental analysis.

The result? Several expert ideas each week from traders, and a brief comment on the fundamentals from the human investor. The models are named to make it easy to remember their trading personalities.


If you want an opinion about a specific stock or sector, even those we did not mention, just ask! Put questions in the comments. Address them to a specific expert if you wish. Each has a specialty. Who is your favorite? (You can choose me, although my feelings will not be hurt very much if you prefer one of the models).

Getting Updates

We have a new (free) service to subscribers to our Felix/Oscar update list. You can suggest three favorite stocks and sectors. Sign up with email to “etf at newarc dot com”. We keep a running list of all securities our readers recommend. The “favorite fifteen” are top ranking positions according to each respective model. Within that list, green is a “buy,” yellow a “hold,” and red a “sell.”  Suggestions and comments are welcome. Please remember that these are responses to reader requests, not necessarily stocks and sectors that we own. Sign up now to vote your favorite stock or sector onto the list!

Headline Spin — Recession Forecasting is Back!

Investors have learned from both data and personal experience that business cycle peaks (popularly known as recessions) are associated with the most important stock declines. It is natural that any news about a possible recession gets extra attention. There are so many sentiment measures – surveys of different populations, including non-investors – that it is easy to find one that supports any viewpoint.

Since I have recently spoken with several intelligent, but worried investors, my own conclusion is that market worries and Trump angst are at a high point. Consider some evidence. Here is the headline page from a reputable source for professional managers.


The array of front page stories has nothing positive about U.S. equities. Here is a front-page story running yesterday on a social media page.

When you actually read the article, you cannot even find the “R” word! Economist Adam Posen, President of the Peterson Institute, is actually writing about an excessive boom (not mentioned in the headline) which would lead to the inevitable bust when the Fed over-reacts. Briefly put, he expects greater amplitude in business cycle, mostly because of deficits which his organization opposes. Posen has no record of successfully predicting recession. More importantly, his near-term prediction is for a boom.

Why the negative headline, with a worried trader looking at a declining chart?

Here is the next case, sent to me by a reader.

Fed rate hikes + low growth = recession, says stock-market strategist


This article reproduces an almost indecipherable chart that references three recessions in all of history that began after a Fed rate increase when economic growth was low. Of course, the article does not explain it that way. It seems inevitable. The author, a non-economist with no proven record of recession forecasting, does not even make these claims in his original post.

If it has historically taken 11 quarters to go fall from an economic growth rate of 3% into recession, then it will take just 2/3rds of that time at a rate of 2%, or 6 to 8 quarters at best. This is historically consistent with previous economic cycles, as shown in the table to the left, that suggests there is much less wiggle room between the first rate hike and the next recession than currently believed.

I hope the error in this pseudo-math is obvious to my astute readers.

And here is the conclusion, after explaining that all Fed rate-rising periods eventually lead to bear markets:

For now, the bullish trend is still in place and should be “consciously” honored. However, while it may seem that nothing can stop the markets current rise, it is crucial to remember that it is “only like this, until it is like that.” For those “asleep at the wheel,”there will be a heavy price to pay when the taillights turn red.

So to be clear, the author is bullish for the moment, but giving a warning. I guess he will be right either way.

And meanwhile, how does this recommendation compare to the headline in the original article – the one predicting a recession?

Is there another side to this?

If so, it must be infrequent and obscure. I invite readers to send examples. This cannot just be a bullish story with evidence, since that is not spinning. You need to find a bullish headline that is not supported by the underlying facts.


Why the disparity? The truth about recession chances – that we are almost certainly OK for the next year or so – is not an exciting story. Journalists never ask about the record or credentials of sources on technical stories.

Investor Protection

There are two ways investors can protect themselves:

  1. Plow through the entire story, the supporting links, and the bio for the original source. (That is what I do, of course). It helps to know how to spot real experts.
  2. Just ignore these stories – especially when the interview subject is not presented as holding specific and relevant skills and experience. This method will save a lot of time – and also plenty of money!

Actionable Investment Advice

The main educational theme is more significant and potentially profitable than any specific stock recommendation. For those needing a little help in following it through, late stage cyclicals, financials, and technology are all good choices. Bonds and utilities are not.

The Quest for Investing Excellence and the Lesson of Dow 20K

The new movement to passive investments is a sharp break from the historical quest for excellence. Many articles claim that no one can do better than the market average. If that is true, you should just throw out your investment library and skip the popular lists of “best investment books.”

This post will suggest a short list of books that would have needed quite different titles. They also would not have become best-sellers! In the conclusion, I will provide some ideas about why this is important for your investment decisions. Here are the hypothetical titles followed by a cover shot of the real book. Suggestions for more examples are quite welcome!


In Search of Mediocrity

Market Sheep

The Average IQ Investor

The Little Book that Equals the Market

Common Stocks and Average Profits

Buffett: The Making of a Lucky Investor

Stay Even with Wall Street


In this series on investment expertise I have (so far) covered the following:

  • There are indeed experts. Sometimes it is obvious, and sometimes they are difficult to find. Consider the case of Phil Mickelson.
  • Forecasting is not always folly. I provide specific examples of expertise, and a checklist for finding the best modeling experts.
  • Dow 20K. The round-number milestone has finally been achieved – at least for today! There are many who are stepping up to claim some credit for their prediction on this front. Some were way too early, and others made the call as we got much closer. Each prognosticator had a method.

My own Dow 20K forecast came when the Dow was at 10,000 and many prominent pundits were calling for Dow 5000! My opinion was controversial at the time. Check out the history of the forecast to remind yourself of how bad things were (unemployment over 10%, and I was ridiculed for suggesting it might fall to 8%).

While it is nice to get some recognition (like this spot from CNBC when we got close to the milestone last month), I see it more as a validation of my methodology. I seek out the best experts. I am constantly looking for excellence. I know that I do not have all of the answers, but my background taught me how to search and to learn. Following superior methods helped to keep my readers and clients on the right side of the market through a long rally hated by most of the punditry and many traders.

There are many paths to trading and investment success. Mine was not the only way, but it was a good way. Having strong evidence and indicators is crucial for confidence.

What Now?

Most of the key factors I see as important are still in place. I summarize them each week. The list of worries has changed a lot but it is still there. The time will come to pull back – but it is not here yet.


Finding Investment Excellence

There is a lot of recent buzz about active management – basically showing that excellence is difficult to achieve. The conclusion is popular, especially among those who have no aspiration to beat average.

I cannot do this in a single post, but I must start somewhere. As I often do, let me start with something far away from financial markets as the original illustration. As the TV lawyers say when wandering off course, “Your honor, just give me a few questions and I’ll connect it all up.”

Experts Exist

Let us suppose we have a difficult situation, not unlike a complex market. In this case, you are golfing. Your ball is in the rough, and there is a danger of going over the green on your approach shot.

If you are a golfer, you will get a laugh out of Golf Digest’s 26 most difficult shots. I have experienced all of them. The “shot over water” was especially intimidating at Butler National, where I asked my caddy about the drop zone. He wisely told me, “You need a better swing thought.” That was great advice!

Here is an example of Phil Mickelson hitting a 64-degree wedge. It is not a cherry-picked result. A google search will show many other similar shots.

The commentator observes that Lefty might be the only one who could hit that shot.

Finding the Expert

I hope everyone is convinced that there are experts in golf. In fact, there are experts in any field. In most cases there is a problem of “Untangling Skill and Luck” as Michael Mauboussin astutely poses it. In the case of Mickelson’s flop shot, the skill is evident. Many important cases are more challenging. What about someone with a model that provides a 10% improvement in forecasting hurricanes? Or earthquakes? The social gain from such expertise is important, but it might be difficult to identify.

If you are an investor in search of excellence, this is the challenge. For over ten years I have taken pride not in my own expertise, but in the ability to spot the best experts in various fields. That is now more important than ever for those who want more than mediocrity.

2016 Silver Bullet Awards Part Two

Each week I try to give special attention to those who do important work, even though it is probably unpopular. These contributors are so important, and their work is so helpful, that we recommend taking another look at the end of the year. (Part One is here).



In a WTWA first, CNBC anchor Sara Eisen earned a Silver Bullet Award for her excellent interview with Fed Vice-Chairman Stanley Fischer (Transcript and video via CNBC). As we wrote at the time:

One-by-one she asked all of the key questions in the current debate over Fed policy – potential for negative rates, Brexit impact, does the Fed make decisions based the economic impact abroad, the state of the economy, recession potential, employment, George Soros, and the strong bond market. Whether or not you agree with Vice-Chairman Fischer, it is important to know what he thinks.

Sara Eisen displayed first-rate journalism, as expected from a Medill School graduate. Unlike so many other financial interviewers she did not argue with her subject nor push her own agenda. She did raise all of the current Fed misperceptions common in the trading community. Her preparation and poise helped us all learn important information. It was well worth turning off my mute button and dialing back the TIVO.


We gave the Silver Bullet to Justin Fox for his writing on one of the most persistent myths – the manipulation of government statistics. His whole post is available here, but we particularly liked this bit:

First, because I know a little bit about the people who put together our nation’s economic statistics. The Bureau of Labor Statistics, Bureau of Economic Analysis and Census Bureau are run on a day-to-day basis by career employees, not political appointees. Even the appointees are often career staffers who get promoted, and many have served under multiple administrations. When top statistics-agency officials do leave government, it’s often for jobs in academia. Credibility with peers is generally of far more value (economic and otherwise) to these people than anything a politician could do for them.

To those with even basic experience in civil service, the political manipulation theory makes little sense.


Ben Carlson won a Silver Bullet for investigating the apparent link between Fed meetings and stock performance. While many (including at least one WSJ writer) took the rumor at face value, Ben asked a clever question: What happens if you change the starting date of the analysis?

As it turns out, any relationship between the two is likely a result of 2008.


Menzie Chinn was a big winner this year. Professor Chinn, a Wisconsin economist, debunked many annoying data conspiracies in one fell swoop. In so doing, he also illustrated how an inappropriate use of log scales can mislead readers.

We called his piece the most profitable thing for investors to read that week – if you missed it, be sure and catch up!


By late in the year, it was increasingly apparent that individual investors were misreading the VIX as a “fear indicator” rather than a measure of expected volatility. Chris Ciovacco did an excellent job in making that distinction. His image here is particularly persuasive.

Runner up awards to Jeff Macke and Adam H. Grimes for their similar conclusions on the same subject.


Shiller’s CAPE method has often caused some eyebrow-raising on A Dash, most notably since he doesn’t use it himselfJustin Lahart of the Wall Street Journal thought to analyze just how this method (and others like it) would work in practice:

For New York University finance professor Aswath Damodaran, this is the real sticking point. He set up a spreadsheet to see if there was a way that using the CAPE could boost returns. When the CAPE was high, it put more money into Treasuries and cash, and when it was low it put more into stocks.

He fiddled with it, allowing for different overvaluation and undervaluation thresholds, changing target allocations. And over the past 50-odd years, he couldn’t find a single way he could make CAPE beat a simple buy-and-hold strategy. In the end, he doesn’t think it represents an improvement over using conventional PEs to value stocks.

“This is one of the most oversold, overhyped metrics I’ve ever seen,” says Mr. Damodaran.

Mr. Shiller agrees that the CAPE can’t be used as a market-timing tool, per se. Rather, he thinks that investors should tilt their portfolios away from individual stocks that have high CAPEs. But he says he isn’t ready to modify his CAPE for judging the overall market.


With the blogosphere in full election season fever, some started to worry that the 2016 stock market gains were a precursor to something much worse. We gave the Silver Bullet to Ryan Detrick of LPL Research for discrediting this argument with two easy charts:


We make a special effort to recognize writers trying to debunk the endless onslaught of recession predictions. Bill McBride of Calculated Risk did this very effectively, with a few key points:

Note: I’ve made one recession call since starting this blog.  One of my predictions for 2007 was a recession would start as a result of the housing bust (made it by one month – the recession started in December 2007).  That prediction was out of the consensus for 2007 and, at the time, ECRI was saying a “recession is no longer a serious concern”.  Ouch.

For the last 6+ years [now 7+ years], there have been an endless parade of incorrect recession calls. The most reported was probably the multiple recession calls from ECRI in 2011 and 2012.

In May of [2015], ECRI finally acknowledged their incorrect call, and here is their admission : The Greater Moderation

In line with the adage, “never say never,” [ECRI’s] September 2011 U.S. recession forecast did turn out to be a false alarm.

I disagreed with that call in 2011; I wasn’t even on recession watch!

And here is another call [last December] via CNBC: US economy recession odds ’65 percent’: Investor

Raoul Pal, the publisher of The Global Macro Investor, reiterated his bearishness … “The economic situation is deteriorating fast.” … [The ISM report] “is showing that the U.S. economy is almost at stall speed now,” Pal said. “It gives us a 65 percent chance of a recession in the U.S.

The manufacturing sector has been weak, and contracted in the US in November due to a combination of weakness in the oil sector, the strong dollar and some global weakness.  But this doesn’t mean the US will enter a recession.

The last time the index contracted was in 2012 (no recession), and has shown contraction several times outside of a recession.

We strongly recommend reading the original post in its entirety.


Jon Krinsky of MKM and Downtown Josh Brown both earned the Silver Bullet award in late 2016, for taking on myths about currency strength and stock performance. In sum: there is zero evidence of a long-term correlation between stocks and the dollar.


Our final Silver Bullet award of the year, given on New Year’s Eve, went to Robert Huebscher of Advisor Perspectives. His full article is definitely worth a read, but choice excerpts follow below. Good financial products are bought, not sold!

But I caution anyone against buying precious metals from Lear Capital. It is not an SEC-registered investment advisor and its web site states that there is no fiduciary relationship between it and its customers.

And also…

For example, Lear will sell you a $10 circulated Liberty gold coin (1/2 ounce) for $753.00 (plus $24 shipping). I did a quick search on eBay and found a circulated Liberty coin selling for as low as $666 (with free shipping).

Buying silver is no different. Lear will sell you a pre-1921 circulated Morgan silver dollar for $30 (plus $10 shipping). On eBay, I quickly found one of these for $22.00 (plus $2.62 shipping).


As always, you can feel free to contact us with recommendations for future Silver Bullet prize winners at any time. Whenever someone takes interest in defending a thankless but essential cause, we hope you’ll find them here.  Have a Happy New Year and a profitable 2017.

Is Forecasting Always A Folly?

Forecasting season is upon us. Anyone who gets to be quoted in print or speak to a reporter is asked an opinion. Expertise not required! It is paradise for pundits.

Many have decried the “folly of forecasting.” People love to laugh at supposed experts, looking back at old forecasts. Since most forecasts are based upon a model, modelers are thrown under the bus as well.

Barry Ritholtz wrote on this topic in his excellent Apprenticed Investor series. There are now over 200,000 blog hits on this phrase.


But please consider this: Most models and forecasts are bad – very bad – but not all. The trick is to figure out which is which. Barry notes the possible exceptions:

There are only two kinds of predictions that have some value to investors: One is probability-based, and the other is risk-based. If you apply the same rules — no one knows the future, they are subject to revision and should not be taken as gospel — then these are sometimes worth considering.

Here are a few examples.

  • Millions of people attempt to paint, but only a handful are successful. Could you pick the winners?
  • Millions attempt to write, but there are few best-sellers. Could you guess them in advance?
  • Worldwide wine consumption is over 30 billion bottles. How many are really good?
  • In the U.S., 11 million people are playing baseball in a given year. Fewer than 900 are in the major leagues. There is so little difference that only an expert could identify the best players by watching them bat.

Finding the best in any large field is a real challenge!

The issue is especially important for financial analysis. I have been pondering this question for weeks. How can I best explain an important but unpopular viewpoint? I recently began this theme with by citing a bogus analysis in the New York Times. In simple fashion, I showed that if you only had the long-term average – that the market returned a positive result 2/3 of the time – you would do much better to predict “Up” every year rather than guessing 2/3 up and 1/3 down. This counter-intuitive result should be cause for thought, since it is an expensive and common investor mistake.

Ben Carlson inspired another approach. He publishes consistently strong work at his blog, A Wealth of Common Sense, which I always read and frequently cite. He discusses the difficulty of selecting the best stocks and sectors. This is the updated sector asset quilt he created, followed by his principal conclusion.

Like any asset quilt, there’s no rhyme or reason from one year to the next. I’m sure you could torture the data here using a momentum or value-based strategy to improve upon the results of the S&P 500, but unless you’re using a rules-based approach, you’re really just guessing when attempting to figure out which sectors will perform best over any given time frame.

That conclusion seems persuasive to a very intelligent observer using annual ranking changes. Can a first-rate forecaster add any value?


Finding the Real Experts

Ben is quite correct in noting that most contrived explanations will torture the data. Is this true of every approach? Here are some things I look for in evaluating a model:

  • It does not use too many variables compared to the available data
  • It has a good record using “out of sample” data as well as in real time
  • The underlying method is logical, proceeding from a theory
  • The modeler has both experience and expertise

Two sharply contrasting success stories reflect the two most common model types, trend following and mean reversion.

Dr. Robert Shiller is a leading economist at a top university, a Nobel Laureate, author of many papers and books of value to investors, and a popular media guest. Among investors, he is probably best known for his Cyclically Adjusted Price to Earnings ratio (CAPE) method. One of the methods that he endorses is the Barclays ETN, CAPE. Barclays implements CAPE in a mean reversion method. They look at the historical CAPE for each sector choosing the sectors most under-valued by this comparison (throwing out the bottom one). This is a mean-reversion method based upon fundamental data. At the introduction over four years ago, Barclays had promising backtest data. This did not attract many investors, most of whom cite CAPE as a method for timing the overall market – which Dr. Shiller himself does not do. After four years, the fund remains very small (under $34 million).

How has it done in real time?

Probably riskier than buy and hold the market, but much stronger returns. Those choosing to use CAPE as a reason to exit the market (not Dr. Shiller’s recommendation) would have done better to buy the ETN.

Dr. Vincent Castelli is not a professor at a top university, but he could have been. He will not win a Nobel prize, because his best work was top secret. He spent a career making U.S. armed forces safer and more effective, heading a group of other scientists from various disciplines. His modeling is known in quant circles, where he demonstrates, advises, and coaches. He is probably not going to become famous on CNBC.

His approach to sector analysis begins with the time-tested method of trend following. The tricks are in separating signal from noise, recognizing trends in a timely fashion, and exiting while you can protect profits. As an expert in modeling, Vince touches all the bases for sound work — ruthlessly pruning variables, a generous out-of-sample test, and real-time comparisons.

These two brilliant men took quite different approaches to life and later to analyzing stock sectors. Each found a profitable approach where most of us would see nothing.


There are many paths to successful investing. Remain open to profit opportunities by giving open-minded consideration to other approaches. Finding the best experts is just as important as finding the best stocks or sectors.

The Evolution of the “Hussman Chart”

Hardly a week goes by without an article like this one by the influential Henry Blodget — One smart stock market analyst thinks this is where we’re headed…(gulp). Mr. Blodget writes as follows:

But anyone who’s feeling comfortable after a strong week in the markets should at least understand that: 1. The macro environment most conducive to crashes is still in place (overvaluation + increasing risk aversion) and 2. The way the market is behaving now is exactly the way it behaved before the biggest crashes in history.

So, neither Hussman, nor I, nor you should be surprised if the market keeps on dropping and doesn’t bottom until it’s down 50% or more from the peak.

As Hussman noted last week in his usual depressing note, a 50% crash would not even be the worst-case scenario. It would just be a normal correction from valuations we reached in 2015.

Featured in the valuation articles is a chart purporting to show very low expected annualized returns for a multiple-year period. The implication for stock investors is clear: Little upside combined with huge risk. It has had a big impact both with individual investors and also my investment advisor colleagues.


Last week, among several other illustrations of popular investment misconceptions, I included a version of what I will call the “Hussman Chart.” I suggested that if you did not understand the chart, you shouldn’t be using it for your investment decisions. My main point was that people blindly accept conclusions from intelligent sources who use sophisticated methods. Of the are dozens of possible illustrations, I included the Hussman Chart. I know that many people sold their stocks some time ago when their investment advisors warned them, producing one of the charts I discuss below.

My worst fears were confirmed! Out of the thousands reading the post, only two or three explained anything about the chart – how it was constructed, what it implied, how to think about it. Quite a few people repeated the author’s conclusion. Wow! They understood and accepted the conclusion without any evaluation of the reasoning. Others did not want to be challenged. They wanted me to explain what I thought was wrong with the chart.

Readers promptly ignored everything else in the article. Some even concluded (amazingly) that I was stating that I personally did not understand the chart. Jesse Felder, a fellow investment advisor and blogger stated this viewpoint explicitly. His conclusion (without any explanation of the chart):

Furthermore, this negative correlation between valuations and forward returns is statistically very high (greater than -90%) and backed by 65 years worth of data. The Buffett Yardstick, as Hussman demonstrates, has been nearly as good as his own version at forecasting forward returns and is backed by roughly 90 years worth of data. Both charts, and the data and reasoning behind them, clearly demonstrate and validate the concept that, “the price you pay determines your rate of return.”


Apparently I need to elaborate on the original theme. I will do so by providing examples of “the chart” over the years. The variables, adjustments and time periods change, but the conclusions are generally the same. Each chart has a documented method and stands on its own. Together one gets a different picture. While the method is continually “improved” and the time period changed, there is never a date with destiny. We do not know whether the early versions worked or not. There is no distinction between the time period used to create the method and the “out of sample” period that follows.

Here is a summary of the charts below.

Date Independent variable Starting point Length of Forecast Adjustments
Nov, 2008 Terminal multiple 1950 7 years
Oct, 2010 Terminal yield 1944 7 years
Aug, 2010 Adjusted forward earnings 1963 10 years Reducing margins
Jan, 2011 Normalized earnings 1928 10 years “Normalizing” earnings
Dec, 2013 CAPE 1932 10 years Mean-reverting margins
Feb, 2016 Non-financial Gross Value Added 1950 12 years World effect, excludes financials

The rest of this report will show the evolution of the approach and raise some specific concerns and points that you might wish to consider.

[I have never met Dr. Hussman, but I have a generally favorable impression of him. He taught for a bit at one of my schools. (Someday I might learn if he considers himself a “Michigan man.”) He is respected as a philanthropist. His approach is intended to be in the best interest of his investors. Updating his methods and conclusions is a natural part of investment management. He reports his thinking frequently and takes on issues directly. Were this not the case, a review like this one would not be possible. He has built a very successful business and earned a strong reputation. His articles are always among the most popular, especially among investment advisors].

Analysis – the Evolution of “The Chart”

First example — How Low, How Bad, How Long? November, 2008


Second example — No Margin of Safety, No Room for Error October, 2010


Third example — Valuing the S&P 500 Using Forward Operating Earnings August, 2010

This quoted explanation illustrates why some might have trouble following the methodology:

The two main failures of standard FOE analysis are that 1) analysts assume a long-term norm for the P/E ratio that properly applies to trailing net, not forward operating earnings, and; 2) analysts fail to model the variation in prospective earnings growth induced by changes in the level of profit margins, and therefore wildly over- or underestimate long-term cash flows that are relevant to proper valuation. By dealing directly with those two issues, we can obtain useful implications about market valuation.

As I have frequently noted, it is not theory, but simple algebra, that the long-term annual total return for the S&P 500 over any horizon T can be written as:

Long term total return = (1+g)(future PE / current PE)^(1/T) – 1
+ dividend yield(current PE / future PE + 1) / 2

The first term is just the annualized capital gain, while the second term reasonably approximates the average dividend yield over the holding period. For the future P/E, one can apply a variety of historically observed P/E ratios in order to obtain a range of reasonable projections, but the most likely outcome turns out to be somewhere between the historical mean and median.

You have to get two things right: the “normal” future P/E and the prospective long-term earnings growth rate g. Standard FOE analysis misses on both counts. Very simply, looking out over a 7-10 year horizon, the proper historical norm for price-to-forward operating earnings is approximately 12.7. Moreover, one cannot simply apply the long-term operating earnings growth rate of 6.3% (0.063) as an unchanging measure of g. Rather, an accurate growth rate for the model has to reflect the level of profit margins at any point in time, since the current P/E multiple may reflect either depressed or elevated earnings. For a 10-year investment horizon, the proper value of g should take into account the gradual normalization of margins. Historically, the best estimate is approximately:

g = 1.063 x (0.072 / (FOE/S&P 500 Revenues))^(1/10) – 1

[Jeff]You should at least be able to understand that the earnings are “adjusted” by a method that is deemed to be appropriate.


Fourth example — Borrowing Returns from the Future January, 2011


Fifth example — Does the CAPE Still Work? December, 2013



[Jeff] If you look at this chart and the two above, you will see that the big divergence in the late 80’s has disappeared.

Comments on the multi-year growth projections

These are points that would be discussed extensively if the research had a peer review.

  • It is necessary to explain carefully both variables, especially making clear when one can evaluate the relationship
  • There should be a sharp distinction between the portion of a chart which is a back test, or an idea fitted to past data, and the “out of sample” data that follows.
  • A multi-year projection has an eventual “date with destiny.” If you are one year away, you can calculate the return that would be needed to make the forecast correct. Think of it as a runner going for a world record in the mile. If he is five seconds off the pace with 100 yards to go, you may safely conclude that he will not break the record.
  • The concept might be extended to more years. If a very negative forecast is in place and the first year or two is strong, it might take a market crash for the forecast to come true.

Research Tests

This very brief summary is a glimpse of what a solid research design should include.


There should be a hypothesis and a test of the hypothesis.

It should be possible to disprove the conclusion.

Stated results should not consume all of the data.


It is best to share data, especially when not proprietary. This allows others to replicate the work. (One of the top economics books of the past year included a serious spreadsheet error, discovered because data were shared. It is fairly common in academic circles. Dr. Shiller shares his data, despite the great difficult in develop the historical earnings).

It is important to provide a complete description of the methodology. This should include paths not taken and variables that were rejected.

It is helpful to show the link (ideally with an update) of past research theses as more evidence emerges.

My Own Concerns about the Conclusions

Many have asked me why I have not followed this approach in my own investment management. I do not write about it very much because of the work required. Dr. Hussman has a great research budget and team. I have a small staff who are already fully-employed on stock picking and managing our programs. Going back to replicate one of the old charts would be a fair amount of work. I will share my concerns here, but only in abbreviated form.

  • We never seem to reach the point of evaluation. How did these approaches work in the past?
  • The methodology seems to include many of the classic overfitting problems. I am certainly not the first to note this. Philosophical Economics in late 2013 wrote Valuation and Stock Market Returns: Adventures in Curve Fitting.
  • There are adjustments that are not well explained. The earnings are adjusted for expected changes in profit margins, for example. What if this assumption is not accurate? Profit margins are an intense (and separate) debate.
  • The method for adjustment keeps changing – different approaches, coefficients, etc.
  • Over the years, the time frame for the forecast keeps moving, from seven, to ten, and to 12. If you go back to the original Shiller papers, he was using five years. His disciples keep experimenting with different choices.
  • The independent variables change with each new iteration. The overall model always seems to fit. Past discrepancies disappear.
  • The attribution of “bad patches” in results to market overvaluation or undervaluation. This seems backwards. Why is the market wrong and the model right?

I am especially bothered by what I see as exaggeration and distortion. What does it add to this discussion to call valuations “obscene?” I find especially distasteful the statement, “The CAPE Ratio id doing exactly what it has always done, which is to help investors anticipate the investment returns they should expect over the next decade. Those returns will very likely be in the low, single digits”.

The CAPE ratio is not some wise old friend that has been around for centuries. It was invented only recently and has not worked very well. The claim of historical validation is also completely wrong. What if I told you that the Packers always won at home after a double-digit away loss in a dome? (I made this one up, but you get the idea). It is historically accurate, but does not have any value for predicting the future. Since Dr. Shiller and Dr. Hussman made a lot of specific choices about measuring earnings, past time frames, use of inflation information, and future time frames, their conclusions should be described as a model, not some definitive historical record. It is rather easy to create a view of history that provides a vastly different conclusion. (see The Single Greatest Predictor of Future Stock Market Returns). It includes this impressive chart.


[Jeff] Similar approach, vastly different result. This is not the only such example.

Implications for Investors

My most important point is a plea, repeated from last week’s post: Be careful about investing your money using analysis you do not really understand!

Whether you share my concerns or not, I recommend a deeper look into these issues, with one of three conclusions:

  1. If this leads you to agree with Dr. Hussman, his fund offerings that provide the best balance. I have written that his stock picking is excellent. Investing with him is better than going “all out” on your own because of fear.
  2. If the deeper look leads you to disagree, you might consider funds or advisors who take a different approach.
  3. If you are not sure, then hedge your investment “bets.”

Weighing the Week Ahead: Can Markets Finally Celebrate Good News?

The data calendar continues in something of an alternating mode. This week we have a concentration of the important economic releases. We also have daily appearances by Fed members. This provides a daily opportunity for pundits to interpret the news:

Can markets finally celebrate good news?

Prior Theme Recap

In my last WTWA I predicted special attention to housing sector issues in a week without much other data. Instead, the Brussels attacks quickly dominated the news. When there was not much additional information, the stories featured the reactions of one and all. Doug Short notes the three-day losing streak in his excellent weekly chart. (With the ever-increasing effects from foreign markets, you should also add Doug’s World Markets Weekend Update to your reading list).


Doug’s update also provides multi-year context. See his full post for more excellent charts and analysis.

We would all like to know the direction of the market in advance. Good luck with that! Second best is planning what to look for and how to react. That is the purpose of considering possible themes for the week ahead. You can make your own predictions in the comments.

This Week’s Theme

The economic calendar includes all of the most important reports. Fed participants will be out in forces. There will be plenty of fresh news to ponder.

In theory, the avalanche of news could lead to a dramatic market move. In practice, it usually works differently. The economic data are mixed. The Fed speakers disagree. Pundits are free to interpret the evidence through the prism of their predispositions. The difference in these viewpoints leads me to conclude that many will be asking:

Will good news be good for stocks?

And of course, the corollary – will bad economic news get a cushion from expectations of slower fed tightening?


The basic themes are familiar.

  • Good news about the economy is good for stocks;
  • The Fed will react to offset economic news either way – keeping the trading range; or
  • Nothing matters except oil prices.


Your conclusion about how stocks will react is a function of what you believe is driving current market action. We do not get paid for knowing yesterday’s news, but it is important to understand the sources of market reaction.

Suppose at the start of last week, people could go “back to the future” and know about the Brussels attacks. What do you suppose would have been their market forecast? In actuality, when everyone knew the answer, we heard many explanations that events like this were now accepted as normal risks. I do not like the very idea that such events are “normal.” I understand the theoretical concept that the market significance is small. With that in mind, my point is how much easier it is to make statements like this after the fact.

Let’s try next week instead. Suppose the market has a significant rally. Many will say that it was end-of-quarter window dressing. But we all know the quarter is ending. If you expect a window-dressing rally, say it now – not as some know-it-all explanation next weekend. If the market declines, I suppose it will be called “profit taking.”

As always, I have my own opinion in the conclusion. But first, let us do our regular update of the last week’s news and data. Readers, especially those new to this series, will benefit from reading the background information.

Last Week’s Data

Each week I break down events into good and bad. Often there is an “ugly” and on rare occasion something really good. My working definition of “good” has two components:

  1. The news is market-friendly. Our personal policy preferences are not relevant for this test. And especially – no politics.
  2. It is better than expectations.

The Good

There was some good news in a light week for data.

dshort GDP

  • Market liquidity is much better than people think. (Matt Turner at BI).
  • Initial jobless claims of 265K remained very low. (Scott Grannis)

Weekly Claims 4-wk avg

  • Sentiment is still not bullish, despite the recent rally. This is a positive on a contrarian basis. Bespoke has the story.


  • Trucking tonnage is strong. Dr. Ed reviews the rebound in several recent economic indicators, including trucking.

Yardeni Trucking

  • New home sales increased at a seasonally adjusted annual rate of 512K. This was slightly better than expectations, and has more economic significance than existing sales. Calculated Risk once again notes the “distressing gap” between existing and new sales. The two series tracked closely until the housing bubble and bust. Bill observes that the gap is narrowing and expects the trend to continue.


The Bad

Some of the news was negative.

  • Durable goods orders declined by 2.8%,
  • Existing home sales declined 7.1% month-over-month with a seasonally adjusted annual rate of 5.08 million. Calculated Risk cites low inventory and stress in oil patch regions as contributing factors. The chart below shows the changes in months of supply.


Truth or Fake?

We know that truth can be stranger than fiction. Many probably know the real answers to these questions, but please play along.

  1. A major company unleashes a tweeting robot. It swiftly becomes offensive and bigoted. (Does that mean that it passed or failed the Turing test?) The FT’s Izabella Kaminska has an imaginative and interesting take – a Trading Places-style bet?
  2. Petitioners demand open carry of firearms at the Republican National Convention. (Akron Beacon Journal) The fact of the petition is known. The source and motive is not – at least in theory. Readers and clients who are Second Amendment fans please not that I am raising a point about media coverage. You may decide for yourself on the merits of the petition!
  3. The research team at a major mutual fund is on a mission to create self-serving results. This is one of my occasional attempts at humor. Those who read it joined Mrs. OldProf in a laugh. Maybe you will, too. She also liked “The Rookie” who showed both knowledge and integrity. Maybe I’ll bring the character back.

The Silver Bullet

I occasionally give the Silver Bullet award to someone who takes up an unpopular or thankless cause, doing the real work to demonstrate the facts.  Think of The Lone Ranger. Often the winner has done a single refutation of a specific post. Sometimes that is not enough to make the point. No single statement has enough substance to disprove! To appreciate Jacob Wolinsky’s effort you really need to read the entire article. The subject is Harry Dent, who provides the chart below — and a product to save you from the result!


Quant Corner

Whether a trader or an investor, you need to understand risk. I monitor many quantitative reports and highlight the best methods in this weekly update. Beginning last week I made some changes in our regular table, separating three different ways of considering risk. For valuation I report the equity risk premium. This is the difference between what we expect stocks to earn in the next twelve months and the return from the ten-year Treasury note. I have found this approach to be an effective method for measuring market perception of stock risk. This is now easier to monitor because of the excellent work of Brian Gilmartin, whose analysis of the Thomson-Reuters data is our principal source for forward earnings.

Our economic risk indicators have not changed.

In our monitoring of market technical risk, I am now using our new model, “Holmes”. Holmes is a friendly watchdog in the same tradition as Oscar and Felix, but with a stronger emphasis on asset protection. We have found that the overall market indication is very helpful for those investing or trading individual stocks. The score ranges from 1 to 5, with 5 representing a high warning level. The 2-4 range is acceptable for stock trading, with various levels of caution.

The new approach improves trading results by taking some profits during good times and getting out of the market when technical risk is high. This is not market timing as we normally think of it. It is not an effort to pick tops and bottoms and it does not go short.

Interested readers can get the program description as part of our new package of free reports, including information on risk control and value investing. (Send requests to info at newarc dot com).

In my continuing effort to provide an effective investor summary of the most important economic data I have added Georg Vrba’s Business Cycle Index, which we have frequently cited in this space. In contrast to the ECRI “black box” approach, Georg provides a full description of the model and the components.

For more information on each source, check here.

Recent Expert Commentary on Recession Odds and Market Trends

Bob Dieli does a monthly update (subscription required) after the employment report and also a monthly overview analysis. He follows many concurrent indicators to supplement our featured “C Score.”

Georg Vrba: provides an array of interesting systems. Check out his site for the full story. We especially like his unemployment rate recession indicator, confirming that there is no recession signal. He gets a similar result with the twenty-week forward look from the Business Cycle Indicator, updated weekly and now part of our featured indicators.

Doug Short: Provides an array of important economic updates including the best charts around. One of these is monitoring the ECRI’s business cycle analysis, as his associate Jill Mislinski does in this week’s update. His Big Four update is the single best visual update of the indicators used in official recession dating. You can see each element and the aggregate, along with a table of the data. The full article is loaded with charts and analysis.

RecessionAlert: A variety of strong quantitative indicators for both economic and market analysis. While we feature the recession analysis, Dwaine also has a number of interesting systems. These include approaches helpful in both economic and market timing. He has been very accurate in helping people to stay on the right side of the market.

The Week Ahead

We have a huge week for economic data. While I highlight the most important items, you can get an excellent comprehensive listing at You can filter for country, type of report, and other factors.

The “A List” includes the following:

  • Employment report (F). Despite wide error band and revisions, still most important.
  • ISM index (F). Good for overall economy as well – some leading quality.
  • Consumer confidence (T). Conference Board version good for employment and spending.
  • Michigan sentiment (F). Same as Conference Board, but uses the “panel” approach.
  • Auto sales (F). One of the most important elements of the recovery – private data.
  • ADP private employment (W). Strong independent measure of employment.
  • Personal income and spending (M). One of the most important indicators.
  • Initial Claims (Th). The best concurrent news on employment trends.

The “B List” includes the following:

  • PCE price (M). The Fed’s favorite inflation indicator deserves attention.
  • Construction spending (F). Volatile February data, but important.
  • Pending home sales (M). Less important than new construction, but worth watching.
  • Chicago PMI (Th). One of two regional measures worth watching.
  • Crude oil inventories (W). Attracting a lot more attention these days.

There is an abundance of FedSpeak! And just when so many think that so much transparency and multiple voices are a problem. Personally, I find it helpful to look at individual positions, just as we would with other democratic institutions that vote, but many seem to prefer less information.

How to Use the Weekly Data Updates

In the WTWA series I try to share what I am thinking as I prepare for the coming week. I write each post as if I were speaking directly to one of my clients. Each client is different, so I have six different programs ranging from very conservative bond ladders to very aggressive trading programs. It is not a “one size fits all” approach.

To get the maximum benefit from my updates you need to have a self-assessment of your objectives. Are you most interested in preserving wealth? Or like most of us, do you still need to create wealth? How much risk is right for your temperament and circumstances?

WTWA often suggests a different course of action depending upon your objectives and time frames.

Insight for Traders

We continue both the neutral market forecast, and the bearish lean. Felix is still 100% invested, catching much of the rebound. The more cautious Holmes avoided the downdraft, and has increased overall positions to 25% invested. One of these was a lucky (?) call in Pepco Holdings (POM) two days before the surprise closure of the merger. For more information about Felix, I have posted a further description — Meet Felix and Oscar. You can sign up for Felix and Oscar’s weekly ratings updates via email to etf at newarc dot com. They appear almost every day at Scutify (follow here). I am trying to figure out a method to share some additional updates from Holmes, our new portfolio watchdog. (You learn more about Holmes by writing to info at newarc dot com.

Not using Fibonacci ratios? Really?? Adam H. Grimes explains his conclusion and invites traders to join the debate.

Doug Short occasionally highlights the “best stock market indicator” from John Carlucci. The current conclusion is an untradeable market. Holmes nodded and barked when he heard this.

Insight for Investors

I review the themes here each week and refresh when needed. For investors, as we would expect, the key ideas may stay on the list longer than the updates for traders. Major market declines occur after business cycle peaks, sparked by severely declining earnings. Our methods are focused on limiting this risk. Start with our Tips for Individual Investors and follow the links.

We also have a page (recently updated) summarizing many of the current investor fears. If you read something scary, this is a good place to do some fact checking. Pick a topic and give it a try.

Many individual investors will also appreciate our two new free reports on Managing Risk and Value Investing. (Write to info at newarc dot com).

Other Advice

Here is our collection of great investor advice for this week.

If I had to pick a single most important source for investors to read, it would be this thoughtfully-researched piece from Urban Carmel. He begins with this quotation and comment:

The US economy is stuck in one of the most sluggish recoveries in history. Growth is just 2% and it will remain slow as consumers and companies work off vast amounts of debt. The country has gotten off track and neither political party has any answers.

These sentiments were written in Time in 1992, the year one of the biggest growth eras in American history began. But these same words are often used to describe the current economic environment.

The rest of the article is a delightful compilation of past quotes that seem to fit the current era. It is worth a careful read, and you will find it amusing.

Stock Ideas

Under Armour (UA) illustrates the power of celebrity endorsements. (Jeff Reeves) Upside potential?

The newest academic studies show that dividend growth is predictable. It takes a combination of factors – not just one.

Chuck Carnevale explains why these dividends are important. As he always does, he combines theory, data, and specific ideas.


Energy Prices

Oil rebound? Dan Dicker at Oil & Energy Insider (subscription required) has ideas about how best to play a rebound. He likes Exxon-Mobil (XOM) as a buyer of a shale player and Blackstone (BX) because of their independent power to buy key assets.

Here is an interesting chart from their free edition:



Watch out for….

Bonds. The Personal Finance Engineer analyzes different asset allocations, testing the value of bonds as a way of reducing portfolio volatility. The answer depends a lot on the Fed’s actions.

My sense is that investors can do better.


Personal Finance

Professional investors and traders have been making Abnormal Returns a daily stop for over ten years. The average investor should make time (even if not able to read AR every day as I do) for a weekly trip on Wednesday. Tadas always has first-rate links for investors in this special edition. There are several great posts, but I especially liked this WSJ article on business development companies (BDC’s). A few years ago this was a popular method for getting additional yield by lending to businesses that did not qualify for regular bank loans. Problems are starting to emerge, and people are bailing out of these funds. There is probably a lesson there.

Market Outlook

Tom Lee, one of the most successful strategists in recent years, notes signs that value stocks and small caps are showing good relative strength since the market lows in February. He believes that the prevailing conventional wisdom of dollar strengthening may be incorrect.


Brian Gilmartin has similar comments about the dollar, suggesting that Q116 may be the trough in the earnings decline.

BlackRock has also turned bullish on U.S. equities.

(Those wishing to explore this idea further can get my free report on why 2016 can be the year of the value investor. Request via info at newarc dot com. We never use your email address for any other purpose).

Final Thoughts

There is continuing tension among the various market viewpoints. It is both too simple and also unhelpful to turn it all into a game of labels.

Investors must have a fundamental method and stick with it. I track the economy (and especially recession potential) because economic growth drives stronger earnings and higher stock prices. Much of the daily news flow is simply noise, distorted further by the simple mental models used by most participants. The three biggest current mistakes are the following:

  1. Making it all about oil. This viewpoint is sufficiently prevalent that it has created excessive skepticism about economic growth and recession potential.
  2. Making it all about the Fed. It is fun for most to criticize Fed policy, but not very useful. Most of the actual predictions (hyperinflation, market collapse after the end of QE) have not occurred.
  3. Making it all about valuation. The most popular methods of market valuation help to keep the average investor scared witless (TM OldProf Euphemism).

Traders have a more difficult challenge. They must guess which of the prevailing, if erroneous, mindsets will dominate on a given day. Good luck with that!

You Do Not Get Paid for Knowing Yesterday’s News!

You do not get paid for knowing yesterday’s news… unless you work as a pundit!  In that case you just need to go on TV and repeat what you read that morning in the Wall Street Journal or the FT.  Like the “B” student in a class, you learn the conventional wisdom and repeat it.  You can sound very confident — even smug — and seem right because you are describing the past.

For traders and investors, yesterday’s news is history — already reflected in market prices.  Unlike other aspects of life, being well-informed provides you no edge. It might even be a disadvantage.  The post-hoc explanations for market moves twist theory to fit perceptions.  As humans, we crave to make sense of everything; we are very creative in finding explanations.  This may build a view of the world that is quite wrong.

Finding an investing or trading edge requires an accurate view of the future, not the past.  You can do this in several ways:

  • Better information — possession of facts not widely known;
  • Speed — getting news faster and drawing the right conclusions;
  • Interpretation of data — understanding and using an indicator or technique that is not widely followed;
  • Contrarian investing
    • Determine the conventional wisdom
    • Find important mistakes in the popular, oft-repeated viewpoints
    • Consider what sectors and stocks would benefit if there is a return to reality


If you start asking yourself the right questions, following the points listed above, you will find some fresh ideas.  Here are a few examples:

Information — There are many important facts that are not widely known.  Worldwide demand for energy has increased every year, more this year than last.  Using energy prices as a gauge for the world economy is too pessimistic.  Bank exposure to energy companies is relatively modest and reserves are much better than in 2008.

If you accept this information, you can shop economically sensitive companies and banks.  This information is hiding in plain sight.

Speed — Good luck with this approach!  You really need to have a plan in advance and jump on breaking news, beating the computer algorithms.

Indicators — The page-view payoff for pessimistic news has inflated the perceived probability of a recession.  Insider buying has been strong in several crucial sectors.  CEO’s generally express confidence about their own business, even when less optimistic about others. The relevant data is easy to find.

Contrarian Analysis — The conventional wisdom has punished biotech because of a political debate about drug prices.  Oil prices are seen as hovering at a permanently depressed level.  Banks are targets for political rhetoric and exposed to bad loans.  Apple is too big and lacks new products.  And more.

Do we really believe that an aging population will not embrace the new drug discoveries?  That China, India, and other countries will not need enough energy to close a 1% gap between supply and demand?  That banks will not escape the political noise with more profit?


I do not expect everyone to agree with the specific trade ideas in this post, but I hope readers will consider the basic approach.

If you want trading or investment profits, think for yourself and think ahead!  Reading the news only helps to know what others are doing.



Finding the Real Expert

Successful investors are modest.  Overconfidence is dangerous.

When I started writing this blog more than ten years ago, I did not think I was an expert on everything.  My investment success had more to do with my ability to recognize the expertise of others.  I have given examples of what I learned from cab drivers as well as from sophisticated model developers.  Nearly everyone has interesting information.  You can often learn just by asking, “How’s business?”

This is in sharp contrast to the behavior of most investors.  It is just human to be impressed by people who make confident predictions of extreme events.  Doing some fact-checking is difficult.  Most people spend more time choosing a refrigerator than picking a stock.

But let us turn to a really serious decision — setting your fantasy football lineup!

[I know from my teaching experience that going to a problem in a different context is a great way to put our biases aside.  Even if you are not a sports fan or fantasy enthusiast, you will understand the point].

The fantasy sports business is popular and profitable.  Players, even those risking only a few dollars, spend many hours researching choices for their weekly lineup.  There is a cottage industry of experts — people who crunch numbers, do podcasts, and sell related services.  Suppose that we wanted to choose the best source from among the following:

  • An articulate newbie who had a new system that identified top players from the past weeks or years.
  • A great-sounding source with football knowledge but no track record.
  • Someone making less spectacular claims, but with a real-time record of reasonable success.

You can probably guess who gets the business.  Let’s turn to investment information.

Eighteen months ago I reported my enthusiasm about a great investment book:

Investors can be better consumers of this information with a little help from two insiders, Josh Brown and Jeff Macke. During my vacation I finished reading their entertaining and informative book — Clash of the Financial Pundits: How the Media Influences Your Investment Decisions for Better or Worse. I plan to do a complete review, but it is especially timely right now.

As you watch or read the news next week, you should realize the pressure on pundits to be bold, dramatic, and confident – even when their forecasts are a bit shaky. The financial incentives range from selling products to building a big reputation. Their analysis of these forces is supported with some compelling evidence from both history and interviews. Reading this book is inoculation against hype, and it is also a lot of fun.

It is now time to put this great advice to use!

Think back to the bogus fantasy advice.

  • We are seeing a rash of “instant experts” on recessions.  Most of them are cherry picking a single variable.  Those with stronger methods do data mining to fit several variables. There are at least a half dozen sources currently preaching doom and gloom.
    • Many of the sources are from “credit desks” writing to their current clients.  They are selling bonds.
    • Some sources are singing an old tune, enjoying their fifteen minutes of fame.
  • None of the confident voices have any record at recession forecasting.  CNBC posts their “street cred” but never shows a track record on this key subject.
  • The most successful recession forecasts get very little visibility. I did a massive search five years ago, inviting nominations. One key source, Bob Dieli, has had the best real-time forecasts for decades.  Other top analysts have analyzed past data with great care to avoid data mining.  I have a helpful resource on recessions here, and update the key information weekly.

The Choice of Experts

A CNBC anchor was conducting a recession discussion among a number of other anchors and one trader.  She noted that most of those forecasting a recession were traders, while economists had a different conclusion.  No one said much, but it was certainly accurate.  There is a divergence between those following commodities and those following economic data.

It is a shame that the best experts on recession forecasting are not getting more publicity — right now, when it really matters for investors.  There is probably no question that is more relevant.


Stock prices for economically-sensitive sectors are, in many cases, already at recession levels.  Oil prices are viewed by many as a sound forecast for the global economy, despite increasing energy demand.  The hot money understands this oil price correlation — both HFT algorithms and human traders.  The average investor infers from the market action that the recession theory is correct.

In the short term, this is the trade.  In the long term, investors should prefer real data and a genuine track record to the bombast of newbies.

And finally, I’m going with Aaron for my fantasy team this weekend!