by Lee Adler, Wall Street Examiner
The latest weekly jobless claims data accelerated to faster than trend, declining at an annual rate around 12%. The July 6 reporting week had a slightly below normal increase in claims for the first week of July. The rate of improvement in the claims data does not support the gains in stock prices however. They remain dangerously extended relative to the improvement in the jobs market. That extension seems likely to get worse if stocks enter a parabolic blowoff phase. This would play into the hands of FOMC hawks who want to cut back QE.
The Labor Department reported that the seasonally adjusted (SA) representation of first time claims for unemployment rose by 16,000 to 360,000 from a revised 344,000 (was 343,000) in the advance report for the week ended July 6, 2013. The consensus estimate of economists of 345,000 for the SA headline number was too optimistic (see footnote 1).
The headline seasonally adjusted data is the only data the media reports but the Department of Labor (DOL) also reports the actual data, not seasonally adjusted (NSA). The DOL said in the current press release,
“The advance number of actual initial claims under state programs, unadjusted, totaled 384,829 in the week ending July 6, an increase of 49,778 from the previous week. There were 442,192 initial claims in the comparable week in 2012.” [Added emphasis mine] (See footnote 2).
The advance report is usually revised up by from 1,000 to 4,000 in the following week, when all interstate claims have been counted. Last week’s number was approximately 1,000 shy of the final number for that week released Wednesday. For purposes of this analysis, I adjusted this week’s reported number up by 1,500. The adjusted number that I used in the data calculations and charts for this week is 386,000 rounded. It won’t matter that it’s a thousand or two either way in the final count next week. The differences are essentially rounding errors, invisible on the chart.
The actual filings last week represented a decrease of 12.6% versus the corresponding week last year. That’s an improvement from the 9.4% drop the week before. The average year to year improvement of the past 2 years is -8.4%. The range is from near zero to -20%. The year to year comparisons are now much tougher as the number of job losses declined sharply between 2009 and 2012. The fact that the rate of decline in recent weeks has been better than average is a sign of a steady to accelerating rate of increase in economic activity. This data does not support the reductions of already weak economic growth forecasts that were prevalent in the media yesterday.
The current weekly change in the NSA number is an increase of 51,000 from the previous week. That compares with an average change of an increase of 57,000 for the comparable week over the prior 10 years. Last year’s comparable week had an increase 72,000. The current weekly performance is stronger than last year, but not materially stronger than the average of the previous 10 years.
Looking at the big picture, this week’s data is in line with the trend of the past 2-1/2 years. Neither stopping or starting rounds of QE seems to have had an impact. Nor did the fecal cliff secastration. The US economy is so big that it develops a momentum of its own that policy tweaks do not impact. Policy makers and traders like to think that policy matters to the economy. The evidence suggests otherwise. That’s not to say that monetary policy does not matter to financial market performance. In some respects it’s all that matters. We must separate economic performance from market performance. The economy does not drive markets. Liquidity drives markets, and central banks control the flow of liquidity most of the time.
Some economic series correlate with stock prices well. Others don’t. This is one that has, and therefore it’s of some use in making a judgment about the health of the equities market. The correlation is most visible when the claims trend is plotted on an inverse scale with stock prices on a normal scale. I give little weight to economic indicators when analyzing the trend of stock prices, but economic indicators can tell us something about market context, which can be useful in formulating investment strategy and tactics. In this case, the data suggests that bubble dynamics are at work in the equities market.
Stock prices were running with the initial claims trend until the Fed started QE3 and 4 late last year, causing the stock price rise to accelerate. The Fed’s QE3-4 money printing campaign has had far more success in elevating stock prices, which was one of Bernanke’s stated goals, than in driving economic growth. The stock market appeared to be in parabolic blowoff mode by February as a result of the excess liquidity. It reached at least a temporary limit in May.
When the market reached the top of the trend channel in May, it was ripe for a correction. The market pulled back to support and then resumed its rise. With Bernanke yesterday seemingly reaffirming that QE will be around for a while longer, there’s an increased likelihood that stock prices will decouple completely from economic indicators in the weeks ahead and continue in parabolic blowoff mode until the Fed takes concrete steps to reduce QE.
Bernanke and his Fed cronies have sown tremendous confusion about when they will end QE, a reflection of their own confusion. I wrote in the Fed Report a couple of weeks ago that the Fed now faces a situation where it will have no choice but to cut back on QE in the months ahead. With some FOMC members increasingly worried about asset price bubbles, a stock market blowoff could be an added catalyst.
More charts below.
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Footnote 1: Economists adjust their forecasts based on the previous week’s number, leading to them frequently getting whipsawed. Reporters frame it as the economy missing or beating the estimates, but it’s really the economic forecasters who are missing. The economy is what it is.
The market’s focus on whether the forecasters have made a good guess or not is nuts. Aside from the fact that economic forecasting is a combination of idolatrous religion and prostitution, the seasonally adjusted number, being made-up, is virtually impossible to consistently guess (see endnote). Even the actual numbers can’t be guessed to the degree of accuracy that the headline writers would have you believe is possible.
Footnote 2: There is no way to know whether the SA number is misleading or a reasonably accurate representation of the trend unless we are also looking at charts of the actual data. And if we look at the actual data using the tools of technical analysis to view the trend, then there’s no reason to be looking at a bunch of made up crap, which is what the seasonally adjusted data is. Seasonal adjustment just confuses the issue.
Seasonally adjusted numbers are fictional and are not finalized until 5 years after the fact. There are annual revisions that attempt to accurately reflect what actually happened this week. The weekly numbers are essentially worthless for comparative analytical purposes because they are so noisy. Seasonally adjusted noise is still noise. It’s just smoother. So economists are fishing in the dark for a fictitious number that is all but impossible to guess. But when they are persistently wrong in one direction, it shows that their models have a bias. Since the third quarter of 2012, with a few exceptions it has appeared that a pessimism bias was built in to their estimates.
To avoid the confusion inherent in the fictitious SA data, I work with only the actual, not seasonally adjusted (NSA) data. It is a simple matter to extract the trend from the actual data and compare the latest week’s actual performance to the trend, to last year, and to the average performance for the week over the prior 10 years. It’s easy to see graphically whether the trend is accelerating, decelerating, or about the same.
The advance number for the most recent week is normally a little short of the final number the week after the advance report, because the advance number does not include all interstate claims. The revisions are minor and consistent however, so it is easy to adjust for them. Unlike the SA data, after the second week, they are never subsequently revised.
The Labor Department, using the usual statistical hocus pocus, applied a seasonal adjustment factor of 0.935 to the current weekly data. Over the prior 10 years the factor for the comparable week has ranged from about 0.983 to about 0.769.