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Financial Sense Market WrapUp with Frank Barbera

Today's Market WrapUp  05.15.2007  Mon  Tue  Wed  Thu  Fri  Barbera Archive

A Little Bit of This, A Little Bit of That...
BY FRANK BARBERA, CMT

It has now been more than 6 years since the Bureau of Labor Statistics (BLS) introduced its ARIMA Birth-Death Model into the compilation of monthly payroll data. Using their own description we note that the model has two components which are used to ‘estimate’ or “impute” activity. From the BLS website, we note that:

  • Earlier research indicated that while both the business birth and death portions of total employment are generally significant, the net contribution is relatively small and stable. To account for this net birth/death portion of total employment, BLS is implementing an estimation procedure with two components: the first component uses business deaths to impute employment for business births. This is incorporated into the sample-based link relative estimate procedure by simply not reflecting sample units going out of business, but imputing to them the same trend as the other firms in the sample.

  • The second component is an ARIMA time series model designed to estimate the residual net birth/death employment not accounted for by the imputation. The historical time series used to create and test the ARIMA model was derived from the UI universe micro level database, and reflects the actual residual net of births and deaths over the past five years. The ARIMA model component is updated and reviewed on a quarterly basis.

  • The net birth/death model component figures are unique to each month and exhibit a seasonal pattern that can result in negative adjustments in some months. These models do not attempt to correct for any other potential error sources in the CES estimates such as sampling error or design limitations.

Of particular interest is the last bullet point which alludes to the “seasonal” pattern that appears in the data. Well, to say that there is a “seasonal pattern’ in the data is really putting it mildly. In the table below, I show the monthly additions and substractions that the model has generated since inception. Note the huge positive affect seen every April and May, wherein the average additional ‘jobs added’ total +174K, and +165K over the last few years. The annual downward revision of jobs lost is always updated in January, which except for July, tends to be the only month where jobs are lost in any size. Why does this matter? Well, take a look at last month’s data point, where the Birth-Death Model kicked out a gain of 317,000 jobs for the month of April. The actual report gain from BLS was a much smaller than expected uptick of +88,000 jobs, BUT, that 88,000 gain includes the Birth-Death gain of 317,000, which ex-the Birth–Death gain means we really saw the economy shedding jobs on the order of a hefty loss of –229,000. Even if we assume that part of the Birth-Death Model gains were valid, say for example, 100,000 of the 317,000 jobs, we are still looking at job losses greater then 100,000 for the month. In my view, this is proof positive that the economy is slowing and that employment in coming months will follow the weak Retail Sales and GDP numbers to the downside.

Seasonal Trends for BLS Business Birth Death ARIMA Model

 

 

 

 

 

Year:

Jan

Feb

March

April

May

June

July

Aug

Sept

Oct

Nov

Dec

2007

-175

118

128

317

 

 

 

 

 

 

 

 

2006

-193

116

135

271

201

166

21

122

13

108

36

64

2005

-280

100

179

257

207

176

-72

132

54

57

21

63

2004

-321

115

153

270

195

182

-91

120

39

42

54

78

2003

-211

8

60

228

194

167

-69

119

27

43

26

53

2002

-112

28

51

66

166

148

-11

59

14

-15

-7

12

2001

-133

31

52

47

63

45

4

35

18

15

1

1

SeasonAvg

-208.3

66

99

174

165

144

-48

93

30

28

19

36

In the next chart, we have applied a moving average smoothing factor (to dampen down some of the volatility in the month-to-month data) to the Monthly Employment reports. At this point, it is clear that the smoothed curve is turning down, and that the employment gains seen in this most recent five year recovery were by far and away the weakest seen in decades. In my view, this represents a terrible ‘failure’ on behalf of the US economy and mind you, a big chunk of the employment growth we did see was in Real Estate and Services. At the present, Real Estate is already in a full-blown recession, possibly headed for a depression, while Service sector jobs represent only minimal income ‘’value added’ benefits to the overall economy. No, what you see happening in this data is scary, and it implies that the US economy could be headed into its worst recession since the Great Depression over 70 years ago. Hopefully, we will get very lucky and that will not take place, but at this point, the odds of a very deep and lasting downturn taking shape dead ahead (over the next 12 to 18 months) seems like a strongly escalating probability.

Economagic: Economic Chart Dispenser

In my view, we can already detect signs from within the market place that the bias toward lower rates to fight a recession is well underway. Just look at the relationship between the 2 Year Note, which is a short term ‘market set’ rate and the Fed Funds Rate. In the past, at important turns the yields on the 2 Year Note have begun to tail off below the Fed Funds Rate for a period some weeks and months ahead of an actual Fed cut. This last happened in 2001, and then before that in 1995. In both cases, the spread of the 2 Year Note less Fed Funds went negative well before the Fed started ‘catching up’ by cutting rates. That is now happening once again, and strongly suggests that the Fed will likely be cutting rates in the second half of the year.


Above: the 2 Year Note and Fed Funds (bold) with lower clip, the Spread of 2 Year Notes less Fed Funds.

Over the coming months, we will be watching closely to observe more signs of a potential on-setting recession. In terms of actually gauging a trend reversal in the broad economy, one of our favorite gauges is the “Boom-Bust Barometer,” designed many years ago by Edward Yardeni, the well know economist who now owns Yardeni.com. Originally, Yardeni divided monthly Spot Commodity Prices by the trend for Initial Claims in Employment using a monthly average for the employment data. Over long periods of time, the underlying series tended to have an upward bias, which removed some of the utility in the signals. In our work, we found that detrending the underlying data using a 5 year moving average puts each cycle on something more of a common platform. We then compare the Detrended Data with a 2 year moving average yielding the oscillator shown in the next chart. This gauge tends to be quite coincidental with the official start of recessions, which would be delineated whenever the oscillator moves into negative territory (below zero).

As can be seen from left to right, there was a deep recession in 1973-1974, then a double dip recession in 1979-1981, the Gulf War recession in 1991, and then the Tech Bust recession of 2001. The gauge to this point is still not that far from all time highs, but has broken back sharply over the last few months. Note how the 2 year moving average is now flattening out (ed. a lot) and how the gauge is rallying back to the underside of the flattened moving average. This is a sign of trouble ahead and is similar action to what was seen just ahead of the 1973-1974 major downturn. In our view, if energy prices spike as expected over the summer of 2007, the negative cash flow affect on most households may be the last straw to cause “Joe Consumer” to put his wallet firmly back in his hip pocket. The resulting cut back in discretionary spending would be the quick ticket to recession in 2008.

 

OK, I know, enough about the economy, Barbera, what about the markets? How will the equity markets handle a slow down or worse, a recession. In a word: Think Bear Market. In my view, I presently see the stock market as extremely over-extended and running up against massive resistance for the S&P in the form of the old highs at 1530-1550. Yes, it is true that the stock market is entirely decoupled from the underlying reality of an economy now in the process of rolling over. Yet, in the past we have seen markets decouple – for a time, only to end up playing catch up on the downside. What signs can we look for to tell us this market is about to reverse. At the moment, the S&P is still residing atop a wave of strong upward near term momentum, such that a decline of more than 2% is unlikely over the next two to three weeks, barring some major unforeseen geo-political event. Yet, as we noted last week, the Shanghai Stock Exchange looks dangerously unstable, and in my view, that is a key market to be watching as the volatility there continues to increase, with prices tumbling last night by nearly 4%. Again, it is very possible that the Shanghai Market may continue to move higher still, expanding its parabolic arc to the 4,500 level, but if that is to happen, it will happen soon as the parabolic bust is now knocking on the proverbial door -- with mid-to-late June a prime candidate.

Above: The long term weekly chart of the Shanghai Composite…perhaps a few more weeks, then POW! Right in the kisser. Expecting a 30% sell off in Shanghai early this summer; it will not be pretty and it will likely not go unnoticed by other markets.

In our ongoing search for clues as to the timing of the next BUST, it is at this time of the stock market cycle, where we always zero in on our old friends, “The Creatures of Confidence.” The brainchild and invention of a good friend and top money manager here in Los Angeles, the idea is to focus (even obsess) a bit on the “best-of-the-best” market leaders as we move into the later stages of a market cycle. In this case, because we know for a fact that the Dow is now pushing historical time limits in terms of days without a 10% correction, and even months sustained within a bull market, that in the scheme of things we are dealing with a grey beard cyclical bull. Within that framework, the school of thought continues that you want to be studying the price action of those stocks which have been the Institutional Money Manager favorites over the recent cycle. Since we live in the age of an Institutionally dominated market, these stocks must be the big winners, i.e. high relative strength stocks, that institutions love to trade. Since volume is key to institutional minds, each stock must be liquid and easy to enter and exit.

Thus, we set off on our study to isolate a select list of Institutional favorites, the so-called, “Creatures of Confidence.” In our efforts, we generally tried to keep the list composed of issues with a market cap of 10 Billion or more, and with average daily volumes of 2 million or more. However in some cases, where relative strength numbers were very high, we included the stocks to form an index of 30 High Confidence Issues. In the case of the Relative Strength numbers, we use TC 2000 and Worden as our input, wherein numbers over 140 are extremely strong stocks. In a very rough sense, a Worden TC 2000 +140 would be roughly akin to an IBD rating of 90%, with readings closer to 200 on Worden akin to a 99 on IBD. We are being a bit general in our commentary here, so please do not barrage us with the various nuances, all of which we already understand. The point is to isolate high relative strength issues which are heavily traded and then begin to watch them for signs of weakness that could emerge as the market gets closer to a final top.

 

Company Name:

Sym

Market Cap

Relative
Strength

P/E Ratio

PEG Ratio

1

China Mobile

CHL

188.68

155

14.36

1.32

2

Google

GOOG

108.03

136

25.10

1.00

3

Compania Rio

RIO

107.61

161

9.34

16.67

4

Rio Tinto

RTP

97.03

111

11.10

0.94

5

Apple Corp

AAPL

94.05

153

27.41

1.49

6

China Life

LFC

89.69

189

14.36

1.32

7

China Petro&Chem

SNP

86.70

140

11.41

0.50

8

American Movil

AMX

69.81

143

13.32

0.50

9

Posco

PKX

36.97

151

8.12

1.57

10

Research in Motion

RIMM

28.01

198

24.31

1.08

11

NovoNordisk

NVO

27.46

179

21.47

1.40

12

Southern Peru Copper

PCU

26.57

150

10.33

0.50

13

Amazon.Com

AMZN

25.22

155

49.76

2.52