A Dash of Insight

Employment Situation Report Preview

Each month we ask the question, "What change in payroll employment would be consistent with other economic data from the same time period (the middle of the prior month)?

This is not a forecast, per se, since we do not posit any causal relationship among these variables.  They are all concomitant indicators of economic activity.  We use the four-week moving average of initial unemployment claims, the University of Michigan sentiment survey, and the ISM manufacturing report.  We carefully choose data from the correct time period.  Even though the ISM report was released today, the survey is obviously from earlier in the month.

None of these indicators have improved very much, so we continue our negative outlook on employment.  We were surprised last month when the job losses were less than we (and nearly everyone else) expected.  We are still looking for losses over 550K, much worse than the consensus loss of about 400 K.

Since our analysis is based upon the final data, after all revisions, the ultimate accuracy may not be known until next year!  That is when final benchmark revisions are done.  Also, the sampling error (90% confidence interval) alone on the payroll survey is more than +/-100K jobs.

Other Predictions

In addition to the consensus forecasts, there are various predictions using proprietary data.  These are all interesting.

TrimTabs uses data from income tax deposits of salaried employees.  They expect job losses of 472,000.

ADP uses data from their payroll administration business, information that no one else has.  They have attempted to gear their results to the "official" government report.  They forecast a loss of 473,000 jobs, amazingly close to TrimTabs.

New entrant Wanted Technologies uses an algorithm reflecting online job ads.  They have a startling forecast:  a loss of "only" 260,000 jobs.  Furthermore, they made their call on June 19th.  And why not?  That was the right time frame to match the payroll survey, and their online job data is more readily available in real time.

Conclusions

Our own prediction of the jobs report has no special inputs -- just the analysis of concurrent economic data.  We are surprised to be the most bearish of the group.  As noted, the error band is wide.  The market will react wildly without regard to the sampling error or other issues.

We do have a few predictions that we can make with more confidence:

• Whatever the job loss, the unemployment rate will move higher.  The demographic factors at work require job gains of at least 150,000 (and probably more) just to maintain current unemployment levels.  The unemployment rate is an important social and political indicator, but it will lag in reflecting an economic change.
• The assembled punditry will state, whatever the number, that it should have been worse because the government is incorrectly projecting job creation. 
• If the result is really good, the rumor mill will start, as it did last month.  When the market spiked on a better-than-expected report for May, the rumors quickly circulated that it was an error -- a government worker had a "fat finger."  Those circulating this rumor (and those believing it) have absolutely no concept about how government reports are assembled, how many people are involved, and how many check points there are.

It just shows that if you want to be short going into this report, you can have confidence that the Bearish Blogging Network (TM OldProf) will have your back.  They will take advantage of the blogosphere to spin at high speed.  The official sources have to wait for a news conference or an interview to reply.  This is plenty of time to cover your shorts.

It is an attractive trade for any hedge fund manager.  Take last month as an example.  You could come in short and be an instant winner on a bad number.  If the report was positive,  you sell more on the spike (averaging up in price).  You then cash in on the silly "fat finger" rumor and the expected monthly spin on the birth/death adjustment.

How Can this Work?

It is amazing.  Take a roomful of traders.  Ask them whether government or a trading desk is more efficient.  We know what they would say.  Trading desks can execute baskets with a keystroke.  There are "fat finger" examples and also stories about interns sitting on keyboards.

Does anyone really think that a very complicated government report is generated in the same way?  Well the silly story was good enough to move the market last month.

Monitoring the Economy

Nearly all of us are consumers of economic information and data.  We are interested because economic strength leads to corporate profits and higher stock prices.  We need to know!

The key issue is pretty simple.  Many question the "second derivative" rally in stocks.  Their point is that economic data are bad, very bad.  Evidence showing that conditions are now showing  "less weakness" -- well -- that is not really bullish.  The economy, consumers, credit, and housing are all still very bad.

A Review of Key Sources

 The advance data on 1st Quarter GDP came in worse than expected.  A big decline in GDP is not good.  Some noted a few positives:

• Richard Hamilton at Econbrowser, one of our featured sources,  is a realist with his own recession method.  His rating is negative, but he notes the increase in consumption and cautiously observes that growth could be positive by year end.
• Joe Wiesenthal, citing economist Richard Moody, also suggests Positive GDP as Soon as Next Quarter.  He notes (emphasis from original), "Thus, through the process of what we call addition by less subtraction, the deductions from real GDP figure to be significantly smaller in Q2 than was the case in Q1. As such, a modest increase in real GDP during Q2 is not out of the question."
• Calculated Risk (another featured source) emphasizes that GDP is a lagging indicator, although he is cautious on the strength of the recovery.  Readers should click through to see the excellent charts.

There are other miscellaneous indicators.  Ed Yardeni, one of our favorite economists, sees twelve positive factors drawn from economic data and earnings.

Looking Forward

Most data sources provide analysis of coincident or lagging data.  We all hope to look ahead, but few provide such insight.

The ECRI (Economic Cycle Research Institute) has a strong record of forecasting recessions and recovery.

My RealMoney Colleague Anirvan Banerji does a careful explanation and defense of the ECRI indicators, which were excellent in predicting the recession.  (Subscription required and worth it.  Regular readers know that we subscribed to RealMoney for years before joining as a contributor.  Consider a trial subscription.)  The key quote is as follows:

The "giant error of pessimism" is now rampant. This is why many will be blind to the light at the end of the tunnel that marks the exit from this recession. But to ECRI's array of objective leading indices, designed specifically to spot recessions and recoveries, the end of the recession is now in clear sight.

The indicators show that the economy is "on the cusp of a growth rate cycle."

Our Take

We expect pre-occupation with the stress test results, due for release on Monday.  Many are suggesting that the assumptions in the test are too soft.  Meanwhile, there are strong indications that the assumptions might be acceptable.

We expect another bad payroll employment report next week (a lagging indicator) and continuing skepticism about the economy.  It all fits our explanation for why the market has defied the lagging economic news.  Current equity prices started building in depression scenarios after the fall of Lehman and the first TARP debate.  The market is now climbing the wall of worry.

Oil Prices and Stock Prices

Yesterday we wrote about the link between oil prices and energy ETF's, including stocks that should be responding to long-term expectations, not the front-month spot prices.  There is a lot of "floating storage" right now.

There is an expiration effect, with a front-month imbalance.  Meanwhile, the effects drive down the prices of anything in the energy sector.

The Role of Speculation - a New Concept for Links Posting

Last night, 60 Minutes had a segment on oil prices, emphasizing speculation and the need for greater regulation.  There were some good points in the segment, but we found the overall impression to be quite misleading.

Regular readers know that we are big fans of those who are the gatekeepers of the Internet, and we feature the sites that do this well.

Here is a new idea:  How about pulling together links on a specific topic, providing the intelligent reader an opportunity to see a range of thought on the issue.  The articles do not always appear on the same day, the general format for the gatekeepers.

Let us give it a try.

Our own explanation about the over-emphasis on the front month.

Eddy Elfenbein's excellent take on what 60 minutes should have asked, but did not.  You can also see the complete video.

Barry Ritholtz analyzing what 60 minutes missed.

Todd Sullivan, looking at how actual supply and demand affected prices.

And most importantly, how a thoughtful economist, writing peer-reviewed work analyzes the role of markets and speculation in influencing prices.  This is not an easy read, because it is detailed and analytical, with plenty of charts.  It is quite clearly argued, and accessible to anyone willing to take the time.  Investors should follow the excellent work of Prof. James Hamilton here and here.  It shows the oil price influence on the recession, and what we should be watching.

Conclusion

It is always a challenge to look forward, but the information is there for those willing to make the effort.  The overall conclusion is that speculation is only part of the effect on prices, with a need to balance the various factors.  Our own view is that forward pricing is a good leading indicator.

How to Deal with Economic Data: The Example of the Employment Situation Report

Each month the market focuses on the Employment Situation Report.  At "A Dash" we have studied this carefully, perhaps more so than anyone else.  Understanding this report requires a combination of methodological skills.  These include research design, survey methodology, time series analysis, and economic forecasting.

Most observers have some, but not all, of this background.  As a result, most observers make various mistakes.

Here are our main conclusions, which you do not see anywhere else:

1. The basic method is an attempt to estimate the total number of jobs in the US in one month, the total number in another month, and subtract to get the difference.  This method, even if done very well, has a built-in error range.
2. The sampling error from the survey is about +/- 100K jobs.  Most market watchers infer false meaning from changes less than this.  Check this out at our Payroll Employment Game site.
3. The initial report has only partial information from businesses, leading to later revisions.
4. The final results are benchmarked against actual data from state reports.  These are much more accurate, since no one pays taxes unless required.  These reports pick up the new businesses, but are available only after a delay of six months or more.
5. There is non-sampling error, because new businesses are not sampled.  Most observers have an inaccurate fixation on this part of the process -- the birth/death adjustment.  This has actually been very accurate, but the conventional Wall Street Truthiness holds the job creation number to be wrong.  These observers have not studied the data.

Our "Forecast"

Here is a brief explanation of how we estimate the monthly change, as reported Monday on RealMoney:

My monthly employment model is a pretty good fit as these things go, but there is plenty of luck involved in each specific month. The 90% confidence interval is +/- 100K, and that is on the data as ultimately revised. I look at three pieces of data collected at the same time as the jobs surveys (the week including the 12th of the month). These are concurrent economic indicators including the ISM manufacturing survey, (terrible at 32.4) University of Michigan Sentiment Index (awful at 60.1), and the 4-week moving average of initial claims as of the relevant week (disgusting at 556,000). The job loss consistent with those other data points is around 580K, about 100K greater than I am seeing from other sources. With the error band, it could have a "6" handle. A positive surprise seems unlikely. I suspect that some economists have a similar method, since the whisper numbers have moved more negative (and closer to mine) in each of the last few months.

Conclusion

The data represent a snapshot from three weeks ago.  It should be no surprise that things were very bad during the fourth quarter.  Today's ADP report had an estimate of job loss even greater than ours, by more than 100K jobs.

The question for investors is not whether things were bad in the fourth quarter, since we all know that.  Normal business activity drew to a halt in October, when the commercial paper market and other short-term lending hit a complete freeze.

Instead, the question is whether the various government programs have improved normal lending and helped conditions.  Employment data, like most other economic statistics, are coincident indicators at best.

When will the market look forward?  We do not know, but we suspect that a bit of evidence will be needed first.

Starting with the Result: The Blowout of the Week

Stock market methods have different time frames.  If a method trades on an intra-day basis, the trader can get into the "long run" very quickly.  If the trades are weekly, it takes longer.

The long run is elusive.  Since prices are more psychology than value, the definition of the long run depends upon changes in cycles of psychology.

This concept is very difficult to grasp.  We all want to render a verdict.  When is the right time?

Looking Outside the Box

One of our regular themes at "A Dash" is educating investors by getting them to think about something different.  Only then do we bring the point back to investing.

This is most easily done with examples where there are frequent predictions and results.  The world of sports provides such an arena for testing.

Readers should note our earlier article, Investing is not Gambling.  Having said this, the predictive problems share many elements.  There is a wide array of methods, both fundamental and technical.  There are many pundits using methods of all types.  The nature of the forecasts involves probabilistic distributions, even though the consumers of forecasts do not realize this.

When the results are in, it all seems to have been certain, almost pre-ordained.  The various factors that cause swings get lost in the outcome.

The Blowout of the Week

Since we do not condone any illegal wagering, let us suppose that the reader resides in Nevada and can make a legal bet on an NFL football game.  Each week there are many choices.  Let us consider this week's big winner.

The Minnesota Vikings were a three-point underdog at Arizona.  The Vikes, trying to nail down the NFC North championship ran up a 28-0 lead and coasted to victory.  Those who bet on them never had to breathe hard.

Their great running back, Adrian Peterson, rushed for 165 yards on 28 carries.  Getting another chance to start in place of the injured Gus Frerotte, Tavaris Jackson threw for four TD's.  The Viking defense had continual pressure on Cardinal QB Kurt Warner.  The Arizona coach felt that his team "did not come to play."

This was an obvious wire-to-wire victory for those who saw the correct elements.  Right?

Getting it Right

We have identified a handicapper who predicted this victory on his "premium service."  Should we sign up for his package next weekend?  Does he have special insight into football?  Into the Vikings or the Cardinals?  He absolutely nailed this blowout pick......

There were some free services where the prognosticators picked the Vikes to win.  Should we look to them?

It is something to think about......

Dangerous Extrapolation

Much of what we read in investing includes reaching back in history to a few instances of something and then suggesting that "today is like that."  We have often pointed out the danger of such reasoning.

As a test, we heard a bit of trivia which seems to be correct.  There is a fundamental "setup" that has occurred six times over 70 years.  This "setup" has had a 100% success rate.  It covers all of the potential instances, and therefore does not seem to be data mining.

There are good psychological and motivational reasons to believe in this relationship.

Are you ready to make the trade?  Do you want to know?

The Trade

The last six coaches of the University of Michigan football team have beaten Ohio State in their first season, going back to Fritz Crisler and Bennie Oosterbaan.

Tomorrow will be the first Michigan/Ohio State game in the Rich Rodriguez era.  Ohio State is favored by about three touchdowns.

Would you take Michigan?

If not, remember this example the next time someone shows you a stock chart of the current market compared to some other country or time period.

Employment Report Preview

A challenge for the market is the ongoing evidence of further weakening in the economy.  Each month the market places tremendous emphasis on the employment situation report.

The market is correct in believing that employment is important.  It is wrong in expecting too much from a measure that attempts to estimate total employment in two different months, subtract one from another, and report the difference.  The sampling error alone is +/- 100K jobs, and there are plenty of other non-sampling issues.  Readers can check out their own estimates on our Payroll Employment Game site.

Our own method asks what reported job change (after all sampling and benchmark revisions) would be consistent with other economic reports.  For a more complete description, please check out this past article.

Our  Conclusion

Our method suggests that the job loss may exceed projections by a wide margin, perhaps exceeding 200K.  Were this to occur, it could create significant market weakness in front of the House vote on the "bailout" legislation.

Simple Models and Housing Prices

We are taking a new slant on modeling and forecasting.  At the risk of over-simplifying, let us start with two schools of thought. 

The professionals take classes in various modeling methods, learn techniques in real-life situations, and then go into the world to predict, to explain, and to advise.

The naysayers disparage the work of the professionals.  They point out the errors in the forecasts, without seeming to make any of their own.  They proclaim that all models include errors.

This represents a clear divergence of thought and a challenge for investors.  If there is no expertise involved in modeling and forecasting, than anyone's opinion (or anecdote) is as good as anyone else's.  It is the Wild West democracy of the blogosphere.  Great fun, but is it profitable?

We recently read a comment from a journalist praising the economic blogs as "better than the economists."  The reason?  She saw a more accurate prediction of the housing situation on a blog than she could recall from a newspaper.  The problem?   You can find a blog predicting almost anything.  Will her "winning blog" be right the next time?

Our Take

There is an important concept which every investor should understand:

^{_{Every pundit does modeling.  Every pundit makes forecasts.}}

The difference is that professional modelers have learned techniques that recognize and measure probable errors, determine an appropriate level of complexity for the model, and accept responsibility for the results.

An Illustrative Example

We have an excellent ARIMA model for volatility forecasting.  It has a twist or two.  It is not very popular with options traders, although we have used it successfully.  Why not?  The model results include an error band.  The traders see the band and (correctly) say that the model is not very accurate.  The inaccuracy is because volatility is difficult to forecast, not because the model is bad.

The options trader uses simple heuristics.  He mentally parses some stock history, the recent market action, and a knowledge of upcoming events.  The options market includes his opinions and the rest of the market makers in the pit.  There is definitely a wisdom of the crowd.

But there is a problem:  The crowd does not specify an error band or confidence interval.  The actual agreement among peers, strongly influenced by the flow of paper, has no formal analytic basis and no "confidence interval."  No one knows if it is correct, and no one keeps records on the performance of the pit forecasters.

A Current Example

There are many pundits -- too many to cite -- who believe that housing prices must decline to a certain level before any stability is possible.  They typically use a simple heuristic like home prices as a ratio to income.  They compare historic values with more recent ratios.

We applaud approaches like this.  One can get a lot of mileage out of a single variable.  Strong predictive models use as few variables as possible.  The approach is supported by logic -- the need the homeowner's  paycheck to cover many things.

A great starting point.

So the question becomes, "Are any other variables relevant?"

Anyone who has bought a home knows that affordability is not merely the price of the home but the size of the payment.  Much of the subprime lending problem came from loans that artificially reduced payments.

So it is obvious that a variable is missing.  The rate of interest on a fixed, 30-year mortgage is certainly relevant.  Comparing all of history with a time when rates are close to historic lows is quite misleading.

Conclusion

We are looking for an astute economist who examines historic affordability in terms of payments, not merely price-to-income.  Meanwhile, we expect that housing sales will stabilize sooner than most believe, since no one seems to grasp this crucial point.

Is This a Tradable Bottom?

We have had some inquiries about our "Gong Model."  They say that no one rings a gong at the bottom, so our marketing department thought this was a cool name.  This article showed a good description of the last time the Gong sounded.

Many traders are seeking "oversold signals" and calling the bottom.

The Gong is not now signaling a bottom, and it is not close.  The Gong model has two parts.  First the hammer must be drawn back, and we are not yet at that stage, nor close to it.  Second, the mallet must come forward.  We'll provide some updates.

Can We Be Wrong?

Of course.  We can certainly be wrong.  If tomorrow's payroll number is surprisingly good, given the +/- 100K confidence interval, the market could rally by a couple of hundred Dow points on a report showing surprising strength.  Our report on The Gong, and other methods, are available to readers on request.

Our intermediate-term outlook has grown increasingly bearish over the last month or so, as documented in our participation on the TIckerSense blogger sentiment poll.  We have reported this both there, and on the weekly updates of our TCA-ETF system.

It is entirely possible that we will have a rally without The Gong.  Also, the gong model gives an entry signal, but not an exit.  We have searched hard for the ultimate bottom-calling method, but we are realistic.  It is not easy.

The Importance of Time Frames

While our system signals have been negative, we have been less convinced by the fundamentals.  In our programs, we have the system (affectionately called the "Vince Model") and the fundamentals, (called the "Jeff Model").  The time frames are different.  The "Jeff'" model is geared to the long-term investor and has a great long-term record.  It is thematic, and the themes have worked over a period of more than ten years.  It is not a trading system, although we obviously try to find the most promising stocks and sectors.  We currently believe that people have become far too negative about the economy and economically sensitive stocks.  Vince sees more pain in the near term.

Readers may be interested in our discussion of the importance of time frames.  We also have written about how a single trade can have two winners -- those who have different time frames or investment objectives. It is not just a question of the immediate stock reaction.

Conclusion

In a difficult market it is important to have one's primary objective in mind.  Traders and investors can reach different conclusions.  One theme is the reaction of the individual investor -- scared out at market bottoms.

Is this the bottom?  Probably not, but that does not mean bailing out of one's retirement account.  We have a nice list of attractive stocks with good valuations.  When the Gong sounds, we will get more aggressive.

Employment Situation Preview: A Risky Outlook

Each month we report the results from our payroll employment model.  This is not really a forecast.  We take a number of different economic indicators from the middle of the preceding month and ask what change in payroll employment is consistent with the other data.  The variables are not causally related, but are all different measures of the economy.

We get a pretty good fit from the University of Michigan sentiment reading (yet another new low this month), the four-week average of initial claims (using the period ending in mid-month), and the ISM manufacturing report.

The data are all consistent with continuing weak economic growth and a loss of about 90,000 jobs.  The market is looking for a loss of 60,000.  Since the 90% confidence interval (sampling error only) is about +/- 100,000, we think that an actual gain is pretty unlikely, while a big loss is possible.

It is interesting that whatever is reported is overly hyped and interpreted as an official count, rather than as a statistical estimate.

Readers interested in learning more can do three things:

1. Take a look at last month's article, where we explored forecasting issues.
2. Check out Little Known Facts about the Payroll Employment Report.  They are still little known!
3. Try playing our Payroll Employment Game.  It shows you the range of different results the BLS might get even from a well-designed survey.  It is cheaper than trading the actual report.