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!

Why You Never See the Best Employment Data

On the first Friday of each month the Bureau of Labor Statistics releases the Employment Situation Report. The data – especially the payroll employment change – is the subject of much speculation, forecasting, and spinning once it is announced. Most sophisticated analysts (like me) regularly report that the sampling error is +/- 120K jobs or so. And that is after the second revision. Few realize that the revisions mostly “top off” the sample responses. There is also non-sampling error, of course, if the current universe of employers is not representative.

The BLS method involves attempting a “count” of the total number of jobs, via a survey, in one month and subtracting it from the prior month. It is not a direct count of change in the number of jobs. ADP attempts a similar estimate using payroll data from their private clients. Today they reported a gain of 246K private jobs. Both are estimates – and only estimates!

The most accurate employment report comes from a source you never hear about, the quarterly Business Dynamics Report. It is based upon the Quarterly Census of Employment and Wages (QCEW), the authoritative final count of all things labor. The QCEW is the basis for the final benchmarking of all the major BLS reports. Why? The data is drawn from local employment offices, not surveys. Businesses are legally required to report all workers. It is the basis for employment insurance, and there is obviously no incentive to overstate employment.

Why Don’t We Hear About This?

No one reports the results of the Business Dynamics Report or the QCEW because we do not have this great and accurate data until eight months later. From the Wall Street perspective, it is “old news.” Here is an important table from the last report.

For our current purposes, the key number is the net employment change of 307,000. I am going to compare that to the estimates made at the time of the original releases.

We should also observe that overall job creation in the quarter was almost 7.5 million jobs. This is very important, but no one seems to know it. Jobs destroyed were over seven million, leaving the net of 307 thousand. This is around 100K per month, and that is all you will hear about.

Please also note that the new jobs come from both additions at current establishments and opening establishments. New jobs from new businesses were 1.4 million for the quarter. The data from this series proves that those complaining about the BLS birth/death adjustment are wrong now, and always have been.

The Estimates

If we fire up the Wayback machine, we can look at the reported employment data from this period. To understand the data, we must realize that the BLS, ADP, (and others) are all making an estimate of the “true job growth.” Their estimates represent different methods, all with pluses and minuses. Let’s see how the two estimates did against what we now know to be “the truth.”

We do not have monthly data for the BED series, but we can see how the two sources did for the entire three-month period. “Truth” was a gain of 307K. Both estimating sources were a bit too high, with the BLS doing better for this round. I have occasionally done this comparison, concluding that the ADP method should also be considered. It would be useful to do this analysis over a longer period. It takes a lot of careful work. (Perhaps if I get a good summer intern, this will be one of the projects. Applications welcome).

Implications for Investors

I understand that investors generally tune out educational posts, especially when a “deep dive” is involved. This is discouraging, since one of my missions is to help people “navigate the noise.” In the case of employment data, it is nearly all noise!

Here are conclusions I have reached, and which you might consider:

  • BLS and ADP both provide useful estimates of employment change. It is a mistake to regard (as most do) the BLS as the “official” result.
  • We should expect variation in the monthly BLS numbers. The survey has a confidence interval of 120K! If the data are real, then the reports should fluctuate around truth.
  • Traders focus on the BLS. They must, since that will be the trading flow. If you are a trader and want to game that announcement, you are on your own. If you are an investor, you should include both reports in your thinking.
  • Do not be bamboozled by those who claim that seasonal adjustments or estimates of new jobs are misleading. I have studied dozens of these claims. None of the writers show any real expertise in data analysis or a proven track record. They are all men on a mission or women on the warpath.
  • The overall path of employment growth remains solid. That will be true even if we get a “weak” payroll employment number on Friday.

And Finally

This topic is (yet another) example of how difficult it is to find real experts. It takes real skill and knowledge. You cannot just read the newspaper.

Other Reading

Your Employment Report IQ – No one knows even 25% of these answers, despite the importance. My favorite prof and greatest teacher introduced me to labor economics. He “approved this message” and said that everyone should read it. While I appreciate the encouragement from a great mentor, the viewership was about 10% of my WTWA pieces – and far less than other pseudo-experts. Trying to help people is an uphill battle!

My best single piece on the monthly employment report. Guessing beans in a jar?

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.


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.

2016 in Review: Best of the Silver Bullet Awards Part One

Since the earliest days of A Dash of Insight, Jeff has brought attention to journalists and bloggers who dispel myths in financial media. We congratulate these writers with the Silver Bullet Award – named in honor of the Lone Ranger, who lived by a strict code: “…that all things change but truth, and that truth alone, lives on forever.”

In a year rife with misinformation and disinformation, it is fitting that we gave out a record 23 Silver Bullet Awards in 2016. For that reason, we’ll be doing this year in two parts; our winners for the first half of the year are summarized below. Readers may also want to check into our 20132014, and 2015 compilations, as many of the same issues persist to this day.

Have any thoughts or predictions on what will dominate news cycles in 2017? Know of a great analyst flying below our radar? Feel free to post in the comments with any suggestions or nominations.


It didn’t take long to find our first Silver Bullet winner of 2016. Matt Busigin took on US Recession Callers ahead of the ISM data release:

Through a combination of quackery, charlatanism, and inadequate utilisation of mathematics, callers for US recession in 2016 are embarrassing themselves. Again.

The most prominent reason for recession calling may well be the Institute of Supply Management’s Manufacturing Purchasing Manager Index. The problem with this recession forecasting methodology is that it doesn’t work.

As we now know, the US economy did not slip into a recession in 2016 – lending further credence to Busigin’s critique of these methods.


Paul Hickey of Bespoke Investment earned the second Silver Bullet award of 2016. While others were content to see doom and gloom in the level of margin debt on the NYSE, Hickey dismissed this as a minor concern.

Although declining margin levels are often cited as a bearish signal for the market, Hickey believes that it is a small concern given the indicator’s coincidental nature. On the other hand, the prospect of rising rates spooks investors much more, and holds them back from buying stocks.

“Margin debt rises when the market rises and falls when the market falls,” Hickey said. “If you look at the S&P 500’s average returns after periods when margin debt falls 10 percent from a record high, the forward returns aren’t much different than the overall returns for all periods.”


The causation-correlation fallacy is a favorite of ours on A Dash. Robert Novy-Marx distinguished himself with an excellent paper titled “Predicting anomaly performance with politics, the weather, global warming, sunspots, and the stars.”

“This paper shows that several interesting variables appear to have power predicting the performance of some of the best known anomalies. Standard predictive regressions fail to reject the hypothesis that the party of the US President, the weather in Manhattan, global warming, El Niño, sunspots, or the conjunctions of the planets are significantly related to anomaly performance. These results are striking and surprising. In fact, some readers might be inclined to reject some of this paper’s conclusions solely on the grounds of plausibility.”

We often note how bloggers and media search back to find tedious explanations and tie a day together. For more reading, we recommend our old post “The Costly Craving for Explanations.”


“Davidson,” by way of Todd Sullivan, was recognized for writing on the confusion of nominal and real data on Retain and Food Service Sales. His key takeaway:

Retail and Food Service Sales are at the highest levels ever measured and trending higher. Would you believe that today’s pace is more than 35% higher than our last recovery. Comments in the media would lead you to believe otherwise. Perhaps you have heard a number of recession forecasts. I have heard at least a dozen well known investors say a recession will occur before this year is out. My view differs considerably and remains very positive.


Jacob Wolinsky found it suspicious that Harry Dent was predicting the next big crash – and happened to have just the product to help investors cope. This “Rounded Top” chart had started to make its way across the panicky world of financial media:

The whole of Wolinsky’s article is still worth a read (especially given its twist ending).


The economic impact of lower oil prices in early 2016 was surprising to many observers. We recognized Professor Tim Duy for his research on the economic impact of lower oil prices.

This problem, however, just scratches the surface. Look at either of the first two charts above and two red flags should leap off the screen. The first is the different scales, often used to overemphasize the strength of a correlation. The second is the short time span, often used to disguise the lack of any real long term relationship (I hope I remember these two points the next time I am inclined to post such a chart).

Consider a time span that encompassed the entirety of the 5-year, 5-year forward inflation expectations:


If we spent a little time looking for the newest conspiracy theory about the Federal Reserve, we could probably give out the Silver Bullet every week. Ethan Harris of Bank of America Merril Lynch (via Business Insider) got this week’s award for shutting down a new “theory” about central banks and the dollar.

“There is a much simpler explanation for all of this. Central banks have turned more dovish because they are being hurt by common shocks: slower global growth and a risk-off trade in global capital markets,” he argued.

“Hence it is in the individual interest of the ECB to stimulate credit and bank lending, the BOJ to push interest rates into negative territory and the Fed to move more cautiously in hiking rates,” he continued.

Some may also point out that there’s a gap between Yellen’s recent messages and some of the recent speeches from FOMC members.

But Harris has thoughts on this, too:

  1. Yellen has consistently leaned more dovish than others.
  2. Most of those more hawkish speeches were from nonvoting members.


The mythology surrounding the Fed bled over into the next week as well. We gave Steven Saville a Silver Bullet award for targeting ZeroHedge with this very thorough rebuttal:

A post at ZeroHedge (ZH) on 8th April discusses an 11th April Fed meeting as if it were an important and unusual event. According to the ZH post:

With everyone’s focus sharply attuned on anything to do with the Fed’s rate hike policy, many will probably wonder why yesterday the Fed announced that this coming Monday, April 11, the Fed will hold a closed meeting “under expedited procedures” during which the Board of Governors will review and determine advance and discount rates charged by the Fed banks.

As a reminder, the last time the Fed held such a meeting was on November 21, less than a month before it launched its first rate hike in years.

As explained at the TSI Blog last November in response to a similar ZH post, these “expedited, closed” Fed meetings happen with monotonous regularity. For example, there were 5 in March, 4 in February and 5 in January. Furthermore, ZH’s statement that 21 November was the last time the Fed held such a meeting to “review and determine advance and discount rates charged by the Fed banks” is an outright falsehood. The fact is that a meeting for this purpose happens at least once per month. For example, there were 2 such meetings in March and 1 in February.


During the economic recovery following the Great Recession, critics often argued that net job creation emphasized part-time and low-paying jobs. Jeffry Bartash of MarketWatch thought to look at the data, and concluded the US economy is still creating well-paid jobs. The key takeaway is in the following chart:


Breaking down mean averages can produce some strange results, and you can never be sure how financial bloggers might spin that data. We gave a Silver Bullet award to Jeff Reeves for breaking down this baffling valuation of Tesla.

$620,000 for every car it delivered last year, or $63,000 for every car it hopes to produce in 2020.

By comparison, General Motors Co’s (GM.N) $48 billion market value is equivalent to about $4,800 for every vehicle it sold last year.

Reeves’ full article, still available on MarketWatch, is still very smart and very readable.


The “flattening” yield curve had become the newest scare issue by late May. Barron’s Gene Epstein and Bonddad’s New Deal Democrat both took this to task, with satisfying results. In particular, the latter’s article had a solid mix of compelling charts with snappy writing:

In the last week or so there have been a spate of articles – from the usual Doomer sources but also from some semi-respectable sites like Business Insider vans an investment adviser or two ,see here (… ) – to the effect that the yield curve is flattening and OMG RECESSION!!! Here’s a typical Doomer graph – that draws a trend line that ignores the 1970s and neglects to mention that 2 of the 4 inversions even within the time specified don’t fit:


We gave this week’s award to the former President of the Minneapolis Fed, Narayana Kocherlakota. As conspiracy theories persisted, he explained the nature of Fed meetings and their timing:

Timing alone, though, hardly merits so much attention. To understand why, consider two possible scenarios. In one, the Fed starts raising rates in June and then adds another quarter percentage point at every second policy-making meeting (once every three months) for the next three years. In the other, the Fed waits until the second half of 2017 and then adds a quarter percentage point at each of the next 12 meetings. The second path represents slightly easier monetary policy, but most economic models would suggest that there would be almost no difference in the effect on employment or inflation.


New Deal Democrat earned a second Silver Bullet award for his work debunking a notoriously deceptive chart:

“The problem with this graph is that includes two slightly to significantly lagging indicators.  Your employer doesn’t start paying withholding taxes until after you are hired.  State tax receipts aren’t paid until a month or a quarter after the spending or other taxable event has occurred.  Worse, since both have seasonality, both have to be measured on a YoY basis, which means the turn in the data will come after the actual turn in the economy.”

Conclusion – Part One

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. Expect to see Part Two of our Silver Bullet review later on in the week. Happy New Year!

Stock Exchange: Model Picks Teach Us to Manage Risk

Individual investors are intensely focused on the concept of risk. And why shouldn’t they be? Finding an appropriate level of downside risk is paramount. However, too few give equal weight to the potential upside risk in their decisions. Permabears and doom-and-gloomers often watch from the sidelines as the market rallies beyond the fear of the day.

We’ve been able to enjoy such a rally in the wake of the election. As the uncertainty surrounding future government policy dissipates, investors have a broad range of new opportunities.This week, our models’ picks give us an opportunity to explore both upside and downside risk.

To help us cut through the fog, we are joined by Blue Harbinger (AKA Mark Hines).

What level of risk is right for you?

The Stock Exchange provides an expert-level debate on technical and fundamental analysis. (Important background is available here). Comments, dissent, and specific stock questions are welcome!

This Week—Is Athena late to the party?

It’s an extremely common mistake for investors to chase a stock on a rally, then panic and sell at the first downturn. This buy-high, sell low strategy is an obvious loser. Athena is our answer to everyone who wants to find a trend, enjoy the ride, and hop out near the peak. Let’s see what she has on tap this week.


Athena: Drill, baby, drill! Continental Resources, Inc. (CLR) was on a roll in November – though I couldn’t say why. All I see is solid upward trend and a spike in price to cap it off.


Blue Harbinger: Continental has some competitive advantages and challenges relative to other energy exploration companies, but its price still remains highly correlated with the price of oil. For example, Continental has competitive WTI break even prices of around only $30-$35 per WTI barrel, and it was an early mover in the Bakken Shale (Williston Basin). However, it will take a long time to develop its huge acreage.

A: I hadn’t factored in time for future development, but to me that sounds like potential for future growth.

BH: Two other things I know you didn’t factor in – the incoming administration (of which you have no knowledge), and attempts by OPEC to reduce crude supply.

Regarding the incoming Administration, it seems the regulatory balance may shift slightly towards pro-business, pro-profits and pro-growth, instead of pro-environment. That may work in Continental’s favor, but the bigger factor remains oil supply/demand, something the Administration has very little control of.

Regarding the attempt of OPEC to reduce supply, would-be buyers may have already missed that boat. Oil shot up on Wednesday (11/30) as OPEC agreed to its first oil production limits in eight years. Oil, as measured by US Oil Fund (USO) was up 8.65% on Wednesday, and Continental was up 22.88%. Caution is prudent with regards to initiating any new positions, because Continental will likely be very volatile in the near-term.

A: Well that’s all very interesting, but I’m only looking to CLR for the next couple weeks. Am I wrong to see upside here?

BH: We certainly won’t see any concrete policy shifts in your time frame, but that may not matter. Sometimes the appearance of a shift to market-friendliness can move a stock just as much.


I’m not looking for anything nearly as risky as Athena. Looking out a year or two down the road, I expect broad-based gains from the biotech sector (IBB).


We’re reaching the bottom of a year-long slip, and the market seems to be correcting its perception of what IBB has to offer.

BH: From a contrarian standpoint, biotechnology and pharmaceutical stocks are attractive. And ETF IBB is a decent way to play the space because it provides diversified exposure at a decent price (the expense ratio is 0.47%).

F: Who’s the contrarian here? It looks like the market is coming to terms with a drastic change in this sector. Could the recent election be having an impact here too?

BH: It makes sense to consider IBB with regards to the goals of the incoming Administration and Congress. Hillary Clinton caused several big drops in IBB over the last year simply by taking issue with the way drugs are priced. Now that her Presidency seems off the table (at least for the next four years), and the threat of the House and Senate being flipped has been removed, the prospects for biotechnology and drug-makers looks better. IBB did pop (up nearly 10%) the day after the election, but it has given back nearly half of those gains.

If you are a long-term contrarian investor, it may make sense to consider some of the individual stocks within the ETF because you don’t have to pay the 0.47% annual expense ratio. For example, the two largest holdings (Celgene and Biogen) have only underperformed the broader market (as measured by the S&P 500) slightly over the last year. However, the third largest holding, Gilead, has dramatically underperformed. We don’t own Gilead, but we wrote about its attractiveness at the end of May (Gilead: A Trump Stock Worth Considering), and it’s valuation has only become more attractive since then.


Fantasy football is going to be the death of me. I liked OBJ a few weeks back, but I didn’t like the Giants next few matchups. I left him on the bench. Naturally, he started playing his best games of the season. This on-again-off again approach isn’t working for me.

BH: Did you want to talk about stocks here or what?

O: Right – you gotta stick with what you know. I’m back on airlines & airline manufacturers. I liked ’em near the end of October and I like ’em again now. Check out BA. This one looks like a winner through the end of December, at the least.



BH: Industrials in general (as measured by the Industrials ETF, XLI) have performed well since the election, and Boeing has performed well too. Industrials (like Boeing) tend to be cyclical, and the market seems to like the incoming administration’s pro-growth message.

From a valuation standpoint, Boeing is not unreasonable considering its price-to-earnings ratio (both twelve-trailing-months and forward) is within its historical range.


O: Glad to see we agree (for once). Any reason to hold onto this one for a while longer?

BH: Boeing continues to spit off a lot of free cash flow that it has been using to reward shareholders with big share repurchases and healthy dividend payments. The dividend yield sits 2.9%, which is above average compared to the S&P 500, and may be attractive to many income-focused investors, especially considering interest rates are low and rising (i.e. bonds don’t offer a lot of yield and their prices will decline as interest rates go up).


I spy brighter days for Under Armour (UA). The recent selloff here was overdone, and some recovery is expected. Since I’m familiar with profit-taking techniques like trailing stops, some recovery is all I need.


BH: It appears the selloff was the result of management tempering long-term growth expectations. Under Armour has been growing like wild fire since 1996, but it’s a big company now, and it’s much harder for Under Armour to keep growing at the same high rate.

H: There may be some long-term concerns, but I’m not terribly concerned with that. How does this position look in the fundamentals?

BH: From a valuation standpoint, Under Armour is cheaper than it was, but it’s still very expensive, and the market still has very high expectations for future growth. For example, check out Under Armour compared to its rival, Nike.


Blue Harbinger: The market can be very fickle when it comes to brands and fashion. Under Armour enjoys a lot of brand recognition and favorability now, but that can change quickly. Plus, it already doesn’t enjoy the same profit margins as Nike.


H: Be that as it may, I’ll again say I’m really only interested in the stock’s modest recovery. Talk to me again in February, and we’ll see how this one worked out.

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. Each week features a different expert or stock.


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).


Our models’ picks for this week were uncharacteristically risky – but that’s not all they had in common. By and large, the gang picked big potential movers for their short-term potential. Fundamental analysis and broader market context raise questions, where technical pings see a big upside.

This is why it is important to consider your level of risk tolerance as a function of your objectives. For many long-term investors, these positions would have little to offer. For those with a trading mindset, there may be a tidy profit to make before the holidays.

2015 in Review: Hi-Yo, Silver!

1388287952-0For years, it’s been a staple of our Weighing the Week Ahead series to recognize analysts who go above and beyond in their coverage of the issues. We congratulate these writers with the Silver Bullet Award – named in honor of the Lone Ranger, who lived by a strict code: “…that all things change but truth, and that truth alone, lives on forever.”

In 2015, we gave out the Silver Bullet Award 21 times – the most ever in a single year. Despite the constant fearmongering from some bloggers and media personalities, more and more people are providing individual investors with the tools they need to make informed decisions. Our winners are summarized below. Readers may also want to check into our 2013 and 2014 compilations, as many of the same issues persist to this day.

Have any thoughts or predictions on what will dominate news cycles in 2016? Know of a great analyst flying below our radar? Feel free to post in the comments with any suggestions or nominations.



January 4, 2015

Our first Silver Bullet of the year went to RL at Slope of Hope for his examination of charting “techniques” in the post 2008 recovery.

RL notes:

What can we conclude from all the above? Well, first of all that making long-term trend predictions is not recommended, no-one knows what is awaiting for us in the future. Bull or Bear Market, inflation or deflation, you name it. What we can do, is to predict market trend extensions with statistical analysis, comparing past trends and current trends and that is in fact what we do with our RL models. We do not know if the market can go to 3000 in the next few years, it’s possible if all of a sudden a lot of investors, after staying on the sidelines since 2009, decide to join this 5 years long rally (how about that for a “confirmation signal”?). What we do know (based on our statistical models) is that the market is overbought right now, and it has been rising ~500 points in the last 2 years, although the strongest rise was in 2013, and in 2014 the speed of advance was a little bit slower (maybe a sign that the rally is faltering?).

In our view, this strong pace is not sustainable in the long term and some correction inevitably will come, although it does not have necessarily to be a 3-years Bear Market, it may be a 3 months correction, or a quick crash followed by a recovery, etc. What we can do is to gauge the market trend extension from a TIME and PRICE point of view with our model and this is an honest method to gauge the short and medium-term market direction

March 1, 2015

Nicholas Colas and Jessica Rabe of Convergex took on Jeff Gundlach’s assertion that equities have never risen for seven years in a row since 1871. With due respect to Mr. Gundlach, the authors primarily took issue with the dataset (courtesy of Robert Shiller) he had used to draw his conclusion. Colas and Rabe write:

“Gundlach used a well-known dataset from Robert Shiller for his findings, but it is not suitable for calculating calendar-year returns since it does not capture exact month-end levels. The S&P 500 actually rallied for eight consecutive years from 1982 to 1989 based on price returns and total returns. The index was also up for nine straight years from 1991 to 1999 using total returns. Therefore, the S&P 500 may have a few more years to run before breaking any records, but volatility will likely rise as well…Whether the stock market finishes the year in positive territory is anyone’s guess, but it wouldn’t be unprecedented.”

April 5, 2015

Barry Ritholtz dug up an old Onion article, as an analogue for what passes as analysis in the financial blogosphere. Readers may be reminded of Sidd Finch.

“Given this line’s long history of jaggedness, we really should take a wait-and-see approach,”Fortune magazine associate editor Charles Reames said. “And even if this important line continues its upward pointiness, we must remember that there are other shapes, colors, numbers, and lines to consider when judging the health of the economy.”

Reames also warned that the upward angle of the line, which most analysts agreed was approximately 80 degrees, may have been exaggerated by the way the graph was drawn.

“The stuff that’s written along the bottom of the graph is all squished together, making the line look a lot more impressive than it is,” Reames said. “Had that same stuff been spread out more, the line would have looked a lot less steep.”

April 11, 2015

Bill McBride (AKA Calculated Risk) ended 2014 by asking himself ten questions about the state of the economy. His quarterly reviews helped to measure economic progress over time, in line with his expectations. This innovative approach to interpreting data earned Bill our Silver Bullet Award.

“At the end of last year Bill made a series of ten forecasts about the economy with a full post on each. He provided a three-month update this week. While early in the year, I found it quite impressive. It is more measured than the optimistic economic predictions and much better than those always seeing the worst from any report. See for yourself, and you will understand why I emphasize this source each week. If you are interested in economic growth, housing, employment, the Fed, or oil prices there is something for you.”

April 19, 2015

Ed Dolan’s thorough deconstruction of ShadowStats is one of our favorite blog posts from 2015. From the way he picks his target, to his measurement of the data – his post reads like a step-by-step guide to winning a Silver Bullet. We found this excerpt particularly interesting:

“As mentioned above, Williams’ ShadowStats inflation series incorporates an additional 2.0 percentage point correction to reflect methodological changes that are not captured in the CPI-U-RS series. I would like to examine that number more carefully in a future post, but for the sake of discussion, we can let it stand. If so, it appears to me that, based entirely on Williams’ own data, methods, and assumptions, the adjustment for the ShadowStats inflation series should be about 2.45 percentage points below CPI-U, rather than the 7 percentage points he uses.

In my view, Williams alternative measure of inflation would be more convincing if he were to make this correction. It would also be less likely to feed the anti-government paranoia of some of his followers, who allege that the BLS is falsifies source data and manipulates reported indicators in the way that Argentina and some other countries appear to do.

It is worth noting that Williams himself makes no such claim. He is a fierce critic of BLS methodology, but he acknowledges that the agency follows its own published methods. He argues that the BLS has adopted methods that produce low inflation indicators, but not for motives of short-term partisan politics. Rather, he sees the choice of methodology as driven by a longstanding, bipartisan desire to reduce the cost of Social Security and other inflation-indexed transfer payments. It would be hard to deny that he is at least partly right about that motivation.”

April 26, 2015

The “what if?” question plagues individual investors and fantasy football fans alike. While the sports fans can afford to indulge in flights of fancy, investors probably shouldn’t. David Fabian won the Silver Bullet for writing to this effect very effectively:

Lastly, I think it’s important for investors to forget the “if/then” narrative that seems to be a psychological barrier to living in the present and investing for the future.

If the Fed had never….

If big banks had never….

If stock buybacks had never….

Stop worrying about what the world might look like if those things had never happened, because they did and we are where we are. Focus on the present and the things that you can control in order to get the most out of your investment portfolio.

June 08, 2015

We frequently warn individual investors to keep their politics and their investments separate. Morgan Housel earned himself a Silver Bullet by illustrating this with a clear, relatable example. The market has seen significant gains since 2008. If you’ve been sitting on the sidelines, you’ve missed some big opportunities.

Take these two statements:

“11 million jobs have been created since 2009. The stock market has tripled. The unemployment rate nearly cut in half.  The U.S. economy has enjoyed a strong recovery under President Obama.”

“The recovery since 2009 has been one of the weakest on record. The national debt has ballooned. Wages are stagnant. Millions of Americans have given up looking for work. The economy has been a disappointment under President Obama.

Both of these statements are true. They are both history. Which one is right?

It’s a weird question, because history is supposed to be objective. There’s only supposed to be one “right.”

But that’s almost never the case, especially when an emotional topic like your opinion of the president is included. Everyone chooses the version of history that fits what they want to believe, which tends to be a reflection of how they were raised, which is different for everybody. We do this with the economy, the stock market, politics — everything.

It can make history dangerous. What starts as an honest attempt to objectively study the past quickly becomes a field day of confirming your existing beliefs.

June 13, 2015

Regular readers know that we like to carefully scrutinize mainstream financial media. Needless to say, we got a kick out of Cullen Roche’s colorful guidelines for financial journalists. They’re all well worth reading, but our favorites are quoted below.

I.  The Stop Scaring People Rule. Scaremongering is not to be tolerated except during the middle of a financial crisis or nuclear war. Writing scary articles for the sake of conjuring emotionally driven page views is not a legitimate business model and is generally counterproductive.

III. The Crash Call Rule. That pundit who comes on TV predicting financial Armageddon every week is not a “guru” and is directly contributing to poor financial decisions. Please refrain from interviewing him regularly. Also, see Rule I.

IX. The Bubble in Bubbles Rule. If you feel the need to use the word “bubble” please reconsider. This word is only allowed to be used by a select few financial experts (Robert Shiller, Robert Shiller & Robert Shiller).  If you are not one of the names listed in the previous sentence please do not use this terminology.

June 20, 2015

Declining profit margins are a prime target for perma bears in the blogosphere. You’d think after an “expert” calls nine of the last three recessions, this one would go away – but we’ve been fighting it for years. Pierre Lapointe received the Silver Bullet for taking on the crowd.

“It can take a long time before contracting margins begin to hurt stock prices,” Lapointe and colleagues Alex Bellefleur and Francois Boutin-Dufresne wrote in a report yesterday. They cited the 1982-1987 bull market, which took place even though earnings as a percentage of GDP were among the lowest since World War II.

“It isn’t at all clear that margins will contract further from here,” they wrote. “They could stabiglize and remain near current levels for some time. This wouldn’t be a disastrous scenario for equities.”

July 04, 2015

Beyond errors in the investment world, we like to caution our readers to think carefully about all kinds of data. Math Professor Jordan Ellenberg, of the University of Wisconsin-Madison, provided a fascinating article about the misuses of numbers. We gave him the Silver Bullet based on his conclusion:

All these mistakes have one thing in common: They don’t involve any actual falsehoods. Still, despite their literal truth, they manage to mislead. It is as if you said, “Geraldo Rivera has been married twice.” Yes—but this statistic leaves out 60% of his wives.

In the era of data journalism, truth is not enough. We need people in the newsroom who can check not only a number’s value but also its meaning. Unless we can ensure that, we’re going to be reading a lot of data-driven stories that are true in every particular—but still wrong.

July 18, 2015

Zero Hedge is one of the least credible yet oft-cited websites sucking up oxygen in the financial blogosphere. Their supporters are apparently pervasive, which is why we had to give Fabius Maximus a Silver Bullet for his thorough deconstruction. The full article is of course excellent: his commentary ranges from exposing half-truths, conspiracy-mongering, selective use of data, and outright deception.

ZH is an ugly version of Wal-Mart or Amazon. It would be sad but insignificant if ZH was exceptional. But ZH is a model of successful web publishing, probably taking mindshare from mainstream providers of economic and market insights. I see websites using its methods proliferating in other fields. For example, geopolitics has become dominated by sites that provide a continuous stream of threat inflation as ludicrous as the worst of ZH.

July 26, 2015

On a lighter note, we greatly appreciated a video done by Jimmy Atkinson at Dividend Reference. His guide to useless (but entertaining) stock market indicators comes with an important lesson attached. Below is one example particularly relevant to hockey fans in the Chicago area.

August 02, 2015

Michael Batnick won a Silver Bullet this year when he abated growing fears about market tops. His careful analysis (backed up by solid data) is a huge asset for individual investors looking for edge.

Conventional wisdom goes that prior to market tops, the major averages become more reliant on just a handful of stocks to lead the rally. When stocks are making new highs, it’s important to look at breadth indicators because indices can pull a nasty trick of masking what is actually happening to the majority of stocks. For instance, the S&P 500 is up 2.3% YTD, however, the average S&P 500 stock is down 0.7%.

Observers with a mission fail to note that divergences often resolve to the upside. Here is an interesting table, showing both frequency and the range of gains.

August 22, 2015

We at “A Dash” applaud anyone willing to challenge the so-called conventional wisdom. We gave Barry Ritholtz a Silver Bullet this year for taking on the Death Cross.

…yesterday’s decline triggered the dreaded Death Cross, as the index’s 50-day moving average crossed below the 200-day moving average. The other major indexes haven’t yet succumbed to the Death Cross horror, though the S&P 500 is heading in that direction.

In a research note late yesterday, Bespoke Investment Group observed that this was the first time this has happened since Dec. 30th, 2011, or in 903 trading days. They also note the modest statistical significance of the Death Cross. Looking at the past 100 years, they wrote that “the index has tended to bounce back more often than not.” Shorter term (one to three months), however, these crosses have been followed by modest declines in the index.

How modest? The average decline is 0.17 percent during the next month and 1.52 percent the next three months. By comparison, Bespoke notes, during the past 100 years the Dow averages a 0.62 percent gain during all one-month periods and a 1.82 percent rise during all three-month periods.

In an e-mail I asked Justin Walters of Bespoke to expand on the details. He wrote: “Most of the time these crosses don’t mean much of anything. This one the forward performance numbers are a little more negative than we would expect to see over the next one and three months, but it’s basically 50/50 whether we go higher or lower.”

August 30, 2015

Our final award of the year went to Michael Batnick and Todd Sullivan (citing “Davidson) for two separate articles on the same theme. Both illustrate the danger in the way the Shiller CAPE ratio is presented to investors. Batnick notes:

When Shiller says 15-16 is where CAPE has typically been, what he really means is this is what the average has been. However, what he fails to mention is that over the past 25 years, the CAPE ratio has been above its historical average 95% of the time. Stocks have been below their historical average just 16 out of the last 309 months. Since that time, the total return on the S&P 500 is over 925%.

Sullivan shows that the profit estimates in the data are flawed because of accounting changes. He shows that large and completely implausible changes in “earnings” were actually the result of the FAS 157 rules.


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 2016.

Business Cycle Forecasting: The First-Rate Results of Robert F. Dieli

This article is probably the most exhaustive and challenging piece I have written.  It was worth the effort because understanding the business cycle is crucial to making great investment decisions.  To get the full benefit, I urge readers to spend some time reading the background links and watching the videos.

I am going to follow up with another piece describing how I use this information for investment decisions.  For now, let us all focus on the method, understanding how and why it has worked so well throughout history.


In May of 2011 I embarked on a search for the best recession forecasting methods.  I had been a long-time fan of the ECRI approach.  They were still very positive on the economy at the time, and my quest was not driven by their conclusions.  I was uncomfortable with the methodology and the lack of transparency.  I had many reader suggestions, and I reviewed them all.  The criteria were stringent — "Jeff's Acid Test."  The easy winner of this competition was Robert F. Dieli's "Mr. Model."  (This article described the competition and the results).

The main conclusion from Bob's work was that there was no imminent recession.  This ran counter to some other well-publicized and popular forecasts.  Some readers complained in the comments that the history of the forecast included some imperfections.  Others disagreed with the methods.  The subject was too difficult for simple responses to these questions.  I promised to follow up in more detail, but I wanted to do so in a convincing fashion.

A Year Later

A year later, some key elements of my rationale should be even more convincing:

  1. Bob was right — once again, as so many times before.  And he did it in real time, not on a back-tested basis.
  2. Imperfections in real-time forecasting are acceptable — even desirable.  When I see a perfect forecast, it always means that the model has been tweaked and changed to fit all of the past data.
  3. Simple is good.  Methods that over-specify the number of variables and numerical trigger points also imply excessive back-fitting and poor predictability.
  4. Theory is important.  The model should make sense.

Most recession forecasting models fail because they emphasize weakness.  This is backwards.  A recession begins at a business cycle peak, something that I explain more carefully here.  A recession starts with excessive strength.  Seen any of that lately?

Dr. Dieli explains this quite clearly in this chart.


Phases of business cycle

Your intuition about the business cycle would be better if you completely forgot the "R" word and took Bob's lead:  Substitute "business cycle peak." 

The key driver of Bob's forecast is what he calls the "Aggregate Spread."  By reviewing results over decades we can see that this method actually provides a warning of about nine months.  The image below describes the composition of the spread, using example data from August.


The most recent aggregate spread is shown below. Just as it did last year, it provides strong evidence that the US economy is not nearing a recession.

Aggregate spread jan 2013

And Now — The Show

Get some popcorn and your favorite beverage and settle back to watch the show.  I recently met with Bob Dieli to discuss economic forecasting and to create some videos.  The result is an eight-part series in which we discuss each of the recessions of the latter 20th Century.  [Thanks to Derek Miller for helping in the production of the videos and producing the key summaries.]

In this first video, Bob and I discuss National Bureau of Economic Research and why their definitions of a recession are important. The nonpartisan NBER looks at both the peaks and troughs of the business cycle to conclude when past recessions have happened, effectively making "autopsies, rather than forecasts" – as Bob says. Therefore, it is important for the Mr. Model to use the same criteria when it forecasts for recessions, providing a clearer picture than other models.




In part two, Bob and I take a close look at the recession of 1957. In doing so, they describe exactly how Mr. Model works. The model signals 9 months ahead that the business cycle will be heading towards a peak or trough when it crosses the 200 basis points (shown as a red line on the chart). 




Bob and I illustrate the ways in which policymakers can and do impact the business cycle and how this interacts with Mr. Model. In the run up to 1960, tightening by the Federal Reserve as well as fiscal cuts by the Eisenhower Administration led to an economic downturn. In 1967, when the Fed again tightened the yield curve, the model signalled a recession. Shortly thereafter the Fed eased up, thereby avoiding a recession. At the end of the day, the NBER never called a recession in '67.




Mr. Model had nearly spotless performance in predicting the recessions of the 1970's. Contrary to popular belief, the 1973 recession had less to do with OPEC and more to do with other government policies that laid the foundation for an economic downturn. 




Mr. Model shows the result of Fed Chairman Volker's monetary policy, which inverted the yield curve and brought the Fed funds rate to 20%. The result was a short 6-month recession, then a short recovery which was stifled by other policies. Interestingly enough, the recovery never took Mr. Model past 200 basis points – meaning a new peak could not have been established for the "second" recession.




After the "double dip" recession of the 80's, the recovery brought the business cycle to record highs. This led to the third-longest period of economic expansion into the summer of 1990. A combination of tightening monetary policy and changing policies regarding the first war in Iraq were both responsible in part for the downturn. In 2000, Mr. Model signaled a recession in an election year – something that was sure to happen regardless of who was elected. However, in both instances the model predicted short and shallow recessions unlike the seriousness of the early 80s. 




In the most recent recession, Mr. Model's results were decidedly different than they had been for any previous recession. The model alerted that the 200 basis point line had been crossed in 2007 but did not decline sharply. This is in part because tightening by the Fed did not effect the yield curve as they had in past events. Quick reactions by the Bush and Obama administrations also helped to prevent a dramatic decline in Mr. Model's basis points.




In this final video, Bob and I focus heavily on the 2007-2009 recession. The model appears to show a false positive as it crosses the 200 basis point line in 2006, but continues sideways for some time before the recession was officially called. In a sense, this suggests severe instability rather than the dramatic declines of the past. In any case, we had ample warning that a recession was coming. It did not take us by surprise.





If you have studied the evidence, you will see that recessions usually involve the Fed!

You might also have noticed that business cycle peaks do not typically come from a problem of "stall speed" but one of excess stimulation.

Market observers are completely mistaken:

  • Wrong indicators;
  • Wrong interpretation (weakeness versus strength);
  • Wrong sources;
  • Wrong point of the business cycle; and finally
  • Wrong stocks.

These will be the subjects of the next installment.

A Bull Market in Bad Predictions

Why does this happen whenever I try to take a few days off?  The market for dubious predictions has geared up in earnest!

While on vacation I was watching the market (but without my customary TIVO), events developed exactly as I predicted.  I warned about signal and noise, the challenge to traders, and the opportunity for long-term investors.

I have also been reading Nate Silver's book, The Signal and the Noise, which includes a lot of wisdom on these topics.  I plan a full review when I finish.

One of Silver's points concerns predictions without any confidence interval.  Many themes will be familiar to readers of "A Dash" since I highlight pundits who claim expertise outside of their "happy zone."  Let us highlight the three worst items from the past week.

  • The fiction –  the ECRI claims that we are now in a recession.  This is ECRI 4.0 after their 2011 forecast failed, their revised 2012 forecast failed, and their complaint about seasonal adjustments being wrong has not proven out.  They are now playing out the last straw, that they are the only ones who can forecast recessions in advance and that no one else knows until after it is over.  This will obviously require a deeper look.  Let me cite the most obvious incorrect statement in their claims: The business cycle has peaked and they are the only ones who know this.

The reality.  No one knows whether the current period will eventually be defined as a recession.  A recession requires a significant decline (which you do not know until you have seen it).  At that point the NBER goes back to the last peak.   The ECRI presentation last week "assumed facts not in evidence."  They are ignoring the reduction in business spending before the election and the fiscal cliff.  They are exploiting the Super storm Sandy effects.  We can expect them to pound the drum even more during the next month, since the weak patch will take a couple of months to sort out.

I have a personal sadness about this, since I like and admire the ECRI principals.  I am going to write another piece about how and why their methods failed.  I wish that they had just been willing to accept the changing evidence — and maybe open the kimono a little bit.

  • The fiction — the decline to zero growth.  GMO's Jeremy Grantham opines that the US economy is on a zero growth path until 2050.  He focuses on the two best drivers of growth — population and productivity.  In this CNBC segment Maria Baritromo breathlessly praises Grantham:

"…He gets paid to make predictions, steve. that's what he's doing. by the way, his former predictions have been right. let's give him that."

The reality.  No one knows what will happen in 2050.  Grantham has ignored a decline in immigration (something that has helped US GDP in the past) to support his perma-bear position.  Pretending to this kind of knowledge gets headlines, but should be a warning signal to investors.  The media commentary points out that he manages a gazillion dollars or so.  Maybe a few of those investors should look to managers who are more grounded in facts.

And by the way, maybe Maria should cite Granthams track record — 47% — before claiming that he has made so many great calls.  Anyone who takes this silly prediction seriously should look back forty years for a comparison.

  • The fiction.  The latest new and greatest recession indicator.  This is from Lance Roberts (who without apology highlighted the bogus 100% recession indicator).  He is now back with a new entry, endorsed by John Hussman.  Roberts takes some existing economic forecasting indicators that do not initially give the result he hopes for.  He then does some arithmetic and creates something that has a lame correlation to past recessions.  Hussman (who does similar things) embraces this approach.

The Reality.  The St. Louis Fed creates about 60,000 data series.  If you do some math transformations as Roberts did, you can turn this into a million or so possibilities.  If you then set a "trigger"  at an arbitrary level based upon a handful of past cases (the way Hussman does)  you can multiply this into the hundreds of millions range.

It is bad research, bad methodology, and a seriously misleading result.  It is impossible to prove, since the bad guys used all of the data.  There is nothing left to prove them wrong.


So much bogus commentary, and so little time.  Can't a guy take a few days off?

I will follow up on all of these themes.  Here are the main ideas:


The ECRI errors will require a more careful review — it is on my agenda.  Meanwhile you can get the basic concept of their mistake by reviewing my recession forecasting page.

Fiscal Cliff

This theme continues with silly trading in the absence of information.

Listen up!!  We have no new information since the election.

We will not know anything new for a few weeks.  Trade at your peril.


It almost seems too obvious.  So many have much at stake in scaring investors.  They have clearly won the battle, with aggressive money flowing into anything with a high yield and conservative money going to farmland and ammunition.  My conversations with investors show that many are scared witless (TM OldProf).

Since the big rewards go to the contrarian investor, there are some great opportunities.

I like CAT as the proxy stock for an economic rebound, although it is (incorrectly) China-centric.

I also like some health care insurers and defense stocks — UNH and LMT as examples — as winners in the fiscal cliff compromise.

AFL is a good play if there is no disaster in Europe.

These are complex questions, so I plan to write more on each issue.




Are You Smarter than a Doctor?

If so, you are also smarter than a major fund manager.

Once again investors are confronted with a LIST OF WARNINGS!!!

The basic idea is that the end of the world is near.  The evidence is a laundry list of events occuring in close proximity with former occasions of the end of the world.

The reasoning offered is seductively persuasive.  The background story is great — sort of like the Hindenburg Omen or the Death Cross.

Your BS detector should be on red alert when you see this stuff, but can you really see the error?  It seems so persuasive…..

The Doctors' Problem

As I have often suggested, investors benefit from stepping outside of their normal world.  Try to think clearly about the following problem:

1% of women at age forty who participate in routine screening have breast cancer.  80% of women with breast cancer will get positive mammographies.  9.6% of women without breast cancer will also get positive mammographies.  A woman in this age group had a positive mammography in a routine screening.  What is the probability that she actually has breast cancer?

Only 15% of doctors answered the question accurately.

Give it a try yourself.  If you grasp the concept, the answer will be easy.

If you can solve this problem, you will have a great feel for the error in the list of warnings.  Please do not post exact answers in the comments, except to say that you have solved it.  Email the answers to jmiller at newarc dot com and I'll hand out the awards!  Some of my readers will nail this one.

I know that readers like things wrapped into a a nice one-article package, but I am not going to do that today.  There are several important lessons here and you won't get them if I put it in a single piece:

  1. Hardly anyone can do probability problems accurately.  You need to see how seductively wrong this is.
  2. Even the smartest market participants make many errors on causation and inference — the includes some high-profile managers and high-priced analysts.
  3. If you can figure out problems like this, you have a real advantage.


I created and used a lot of problems like this in my teaching, but I saw a really good source with a more modern example.  I'll catch up on giving credit with the solution.

No fair searching to help your answer!  Do your own work!

And take pride if you solve this problem.