Auto Sales and Vehicles per Driver

Over at Calculated Risk there have been several posts on the auto sales numbers as that data has been released. CR's take (link to the latest post: HERE) has been that the fleet turnover ratio, currently at a record 26.8 years is unsustainable and believes that the correction in this value will take the form of an uptick in auto sales rather than a decrease in the fleet size. The comments have been in disagreement with this outlook far more than is typical for a post over there. The comments section has typically evolved into a "I've got a 1982 Honda that I've driven around the world 18 times and expect it to make another 2 trips," sort of thing. Not exactly hard evidence. There was one comment in the last string about 2 car families becoming 1 car families. This is far more interesting.

I decided to try to dig up the data on licensed drivers and the registered vehicles to see if there has been a change in the ratio or anything that would remotely resemble a historical "norm.

Here are the charts: the first one containing the data on licensed drivers, passenger cars and trucks along with one line combining those last two. Motorcycles are omitted because in the more recent sources they are not found broken out separately as in the earlier reports. (See the source links at bottom.) Also note that until 1990, the year axis is ticked off in increments of 5 years and then in 1 year increments.

The second chart shows the ratios of passenger cars to licensed drivers and passenger cars + trucks to licensed drivers over the same period. Early on in these data sets, there is a shift in the categorization of trucks and so these early points are omitted. I don't think it matters in the final analysis anyway.

One interesting thing is the decline in passenger cars and the rise in the cars + trucks ratio. I am assuming this represents the change in vehicle mix as the SUV came to be such a dominant class. However, I did not dig very deep into the specifics of the classifications in this case. The most important thing to note is that the ratio of vehicles to drivers is greater than 1 and the 2007 ratio stood at 1.19 vehicles per driver in the US. In 2001 (the last data I can find), the percentage of households with 3 or more vehicles in the US was 23.6%.

If there really is a new sense of frugality that creeps into the American household budget it does not take a great leap to imagine that the ratio of vehicles to drivers might actually fall back closer to 1. This could get even worse if the low interest credit that the automakers have been providing courtesy of the government disappears since it seems very likely that consumer credit is going to be significantly reduced in the coming year. (And justifiably so.) At any rate, simply because the fleet turnover rate has reached a hitherto unknown height does not necessarily imply that auto sales will push up. I think the data and change in patterns argues for a much closer examination of the possibility that the vehicle fleet is reduced.

Sources: FHWA Highway Stats 2006, FHWA Highway Stats 2007, National Trans. Stats Table 01_011, BTS Transportation Stats Annual Report.

Market Sector Valuation Breakdown

I really should apologize for my utter lack of posts in the last few weeks. As noted before, it’s been a combination of unsuitable-for-posting work, lack of inspiration and real-life requirements that have reduced my output to a trickle. Plus, what’s the point of posting work that relies on a data set that might literally be worthless overnight? (See: PPIC announcement, SPX reaction to as Exhibit A.) Anyhow, now that the SPX rally seems to have hit some local maxima, I figured I’d have a go at looking at valuations from a sector perspective. I thought this would be interesting on its own merits, but also because tons of bulls out there continue to state that financials aside, stocks are cheap, cheap, cheap. My belief is that they are not but unexamined assumptions have a way of biting you and giving you rabies. (Look no further than the current real-estate malaise infecting the system for proof of that assertion.)

So, here’s the background: I downloaded data on PE(ttm) and PE(fyf) for 5,214 stocks on the evening of 3/23. Included in the set was the Sector, Industry, and sub-Industry information. Not included were OTC stocks.

The first thing that I noticed was the sheer number of companies with an unreported PE, or perhaps more correctly an undefined PE. Unsurprisingly, the percentage of companies reporting an undefined PE varied considerably by sector. Here’s a snapshot:

Surprisingly, the financial sector did not have the highest percentage of unprofitable companies – that honor went to health care, though largely due to the substantial number of biotech start-ups that have never turned a profit. Anyone that has dabbled in that industry knows how many of those companies fail. On the other end of the spectrum, consumer staples and utilities were the two lowest which makes sense considering their positions in the standard “defensive” portfolio. Please note, this says absolutely NOTHING about the volume of loss within each sector. Case in point, as is clearly stated in the SP500EPSEST sheet by H. Silverblatt: AIG alone accounts for -$7.10 of the -$23.04 reported EPS loss. (Yes, AIG is apparently still in the index!) One bonus: here is a table of the PE Breakdown by Industry, which provides a bit more detail than this sector overview.

Anyhow, one can further refine this by removing the pharmaceutical and biotech industries from the overall total which reduces the overall percentage of undefined PEs to 37.8% making the relative value of the financial group that much worse. The reason for explaining this is that I have never read someone discussing average PE that talked about how they treated the “undefined” result. In the discussions below, the average of any group is defined as the average of the numeric response PE. To illustrate if there were 3 companies with PEs of 5,10 and undefined then the average of the group would be 7.5. Including the breakdown of unprofitable companies really helps add needed detail to the analysis.

Here’s a chart of the major sectors and their PE(ttm) binned out. The sub-0.1 bin is an artifact of an Excel quirk and is a stand-in for the “undefined” bin. This is a percentage chart within sector so that the sector-to-sector comparison is a bit easier to see. Again, it is pretty easy to see the lower representation of the utilities and consumer staples in the “undefined” bin and the very large proportion of the healthcare sector for the reasons mentioned above.

So considering the percentage of unprofitable companies in each sector and the average multiple of the remaining issues, it would appear that energy is perhaps the best value right now if one were to buy into a sector ETF for the long term. What makes this also an attractive sector to me is the average yield – at least on a trailing basis – is the 2nd highest of any sector. The first is the financial sector but this will soon change as the dividend cuts in this sector will far outweigh the devastation in the share price. While the popping of the crude bubble will have similar effects, it will likely not be as drastic going forward. (I did not include the dividend breakdown here.)Further, if/when the demand side returns in energy the price in commodities could be shocking since so many projects were cancelled. And finally, it must be mentioned that the Fed is clearly bent on inflation and commensurate dollar devaluation which can only serve to boost most commodity prices. Let’s just hope the inflationary cycle has both legs – price AND wages. If the latter fails to keep up, the demand side will fall slack as I don’t think the credit will be around to offset the lack of earning power. But that’s a long digression that will be far better covered in more professional places.

Again, all of this must be put in the context that valuation is whatever the market feels like it being. There's a funny quote about how, "only god knows the right PE," and it's true - it's totally a function of supply and demand. And I believe I have made the case in past posts (see here & here) that only earnings recovery will signal a true bottom and demand for equities will far outweigh any concerns regarding valuation when that happens. I would conceded that there are sectors where the market is "cheap" relative to historical norms and further, that within each sector there is some skewing that is occuring due to a small-ish number of very high multiple issues. These types could offer some interesting pair trades with long sector ETFs and short on the high multiple componenets. However, these observations do not support just buying a sector or index but rather very selective stock-picking. Something to investigate further...

(If anyone is interested in further industry/sub-industry breakdowns, let me know and I’ll try to post up some additional charts as requested.)

U3 & Participation Rate Updates

In a post from last December titled "Fighting the Last War," I looked at the vast differences between the initial conditions of the tech bubble recession and the one that the US entered in December of 2007. At this point, if there was any lingering doubt residing in the populace, it should be shaken.

This post then, is not to re-iterate that point but rather just to provide an update of those charts to see just how much worse things have become. First, there was the rather cluttered chart with SPX, U3, and the Fed target rate. U3 has shot up on both the SA and NSA measures to 7.6/8.5%, respectively. Keep in mind my projection of a 7.9-8.1% U3 (SA) rate from early February, so obviously I think this has room to get worse. What is ominous about this number is that JPM had a loss projections for the WM takeover that used 8.0% in its "severe recession" scenario. Obviously, that is going to be overtaken if not this month than the next. Not coincidentally, the banks have not reported their loss sensitivities based on U3 as of late.

The next chart was the U3 values with the participation rate. This make the picture even more bleak when it is noted that the participation rate is about 1% lower than during the bubble recession, even while U3 is itself 1.5 points higher. This does not bode well for consumer spending since now even more households have a single income.

Finally, but on a similar point, the home ATM is now functionally empty. I'm not putting that chart up but the net equity extraction from homes went to a -$64B for Q3/08. (The last data point available.) Suffice to say, this is very bad for anyone that had relied on consumers tapping their houses for big ticket items. I'm looking at you, HOG!

Bottom line: the picture is growing darker.

Update (3/6/09): U3 (SA) was 8.1% today and the NSA value hit 8.9%.

U-3: NSA vs. SA

The unemployment report from BLS came out today and it was ugly, even with the headline reporting of the seasonally adjusted numbers. What stuck out at me when I looked into the A-12 table was the difference between the non-seasonally adjusted (NSA) and seasonally adjusted (SA) values. They were respectively 8.5% and 7.6%. Consider the following stories from the last part of 2008:

- "November retail hiring was 53 percent lower than a year ago, when retailers added nearly 458,000 holiday workers, compared with 217,200 hires last month, according to an analysis by Challenger, Gray & Christmas Inc. (Source: Boston Globe - Dec. 5, 2008)

- "Department stores hired 88,000 fewer people this November compared with 2007, and clothing and accessories stores cut 65,000 jobs, according to the Labor Department. (Source: Forbes - Dec. 11, 2008)

There are tons more of these stories if you're inclined to look. If you read a local Picayune, Gazette, or News you'll likely recall similar headlines. So with that backdrop, how valid is the U-3 SA number? As ever on this blog, to the charts!

The first chart looks at the monthly trend in the difference between the NSA and SA numbers. You would expect there to be a pattern because of the whole idea behind the NSA value. However, there is some variation inside in the monthly differences which would be expected. The question is whether or not this is a systematic pattern or just noise. The next chart can shed some light on that question.

This chart requires a little bit of explanation. It uses the difference values for all the January numbers from 1989-2009 and plots them against the U-3 NSA value. The line fits reasonably well with an R2 = 0.805. This certainly seems to imply some correlation with the background unemployment level - a higher U-3 number tends to have a higher difference between the NSA and SA values. I think the stories noted above explain the reason behind this phenomenon.

The SA model would assume that post-holiday season there would be more seasonal workers in the job market just as there should have been more seasonal workers employed in Q4. However, this year that doesn't seem to have been the case. This year, holiday hiring was muted at best and thus the substantial differences between the two measurements. Bottom line: the most recent period does not fit the pattern that the SA modeling assumes.

What to look for in February? Predicting a bump in the U-3 SA number would seem like a no-brainer at this point. The question to me is how much of the difference between the SA and NSA values will be bridged. I would not be surprised to see the NSA number actually hold steady and the SA value to creep up one or two tenths to maybe 7.7 - 7.8%. (see update below)

One other note: the participation rate slid further to 65.4% (SA) and 65.5% (NSA). These are 20 year lows. I've omitted discussion of that for brevity's sake but these are also important to watch as signs of a very anemic labor market. I've touched on that before in my original post to this blog.

Update: I have been thinking more about this and want to revise my expectations of SA unemployment. Here's why: First, the normal SA model appears to expect a fall in February NSA employment figures and compensates upward a bit as a result. I don't believe that this year, there will be a fall in February NSA unemployement and the NSA number is already very elevated. Second, the ongoing mass-layoff stories would point to a higher value. So my revised estimate is 7.9-8.1% for SA unemployment in the next report.

Ashes to Ashes...

OK... did you mentally sing "funk to funky" or fill in the more somber "dust to dust"? That question sounds a lot like one of those queries on a personality test that purports to tell you something profound but the results instead read like a horoscope out of the Sunday paper. But the title was chosen deliberately.

In the last few months I've read a few stories about assigning blame and generally at least some of it has been laid at the feet of the Fed and their too-loose monetary policy. To be more specific, their absolute refusal to "take away the punch-bowl" to use the most favored phrase. And it's probably true. As usual, here's a chart - this time of the Fed Funds rate. For reference, the data set begins on July 1, 1954 with a Fed funds rate of 0.80% and the last update is 0.18% on 1/15. Interesting and kind of symmetric in a way that appeals to my sense of order.

It certainly supports the premise that the Fed was unwilling to tighten policy since Volker was in charge. Since his tenure each time the rates were cut, they are never subsequently raised back to the level prior to the cuts. One could argue that the Fed has become more supine to the Executive or generally just wants the good time to keep on a-rollin'.

Now, waaaaay back before I started reading about any of this stuff in relation to markets and trading I had a basic academic/political interest in national debt and what-not. If you look back at 1954 as the US emerged from WW2 with some fairly substantial debts, the national debt to GDP ratio in 1954 was 73.3%. (Trivial aside: this number peaked at 121% of GDP in 1946.) In late 2008, this number was... ~72.5%! I must admit, I do like coincidences even if they don't really mean anything.

So moving forward, will we see a return to progressively tighter policy at the Fed? I guess that depends on how much of the money currently being shoveled into the fires of the financial sector manages to remain unburnt and floats off into the broad economy to reappear as inflation. On the flipside, will it even matter as rates are forced upwards because nobody (or at least fewer somebodies) wants to buy the debt? That's perhaps a more ominous possibility. It feels like this could be a great entry point to explore a rich topic but it will have to wait for another post.

Source: St. Louis Fed FRED data

Fighting the Last War (or: This Is Not a Replay of 2001)

Who doesn’t want to look at the current economic forecasts and want to do some prognosticating based on the last recession? After all, there's a lot of nostalgia for a recession that was practically over before it was even called out for being what it was. The NBER declared it started in March 2001 and over in November 2001. And lately, I’ve read a few market projection opinion pieces that sure sound like they are trying to run the playbook from the last recession, even if that premise is not explicitly stated. So what’s different?

As usual, I’ll start out with a chart:

This chart needs a little clarification:
- The days are done on market sessions for SPX rather than on calendar days. (True for subsequent charts as well.)
- Day 1 is one calendar year prior to the NBER declared start of the recession. March 2001 for the tech bubble and December 2007 for the current one.
- The data series noted with “TB” are the tech bubble runs.

All things considered, the charts are not that much different if you were just to take a quick glance at it – U3 moving up, Fed slashing rates, SPX plummeting – albeit at much faster rates on those last two items. But when more detail is added to the picture it gets far darker.

Here are some additional specifics on the unemployment rate then and now. (For more, revisit my inaugural blog post.)

At a similar point in the last recession, U3 (SA) was 5.7% vs. the 6.7% currently observed. But worse, the participation rate was 66.6% whereas now it is 65.8%, which likely adds to the general malaise in the employment area.

Unemployment is not the entirety of the picture here, however. There is also the consideration of the recovery from the recession in 2001, and this is where it starts to get uglier. Homeowner’s equity stood at 56.98% in Q4/2001 and consumer credit held by commercial banks was just about $235B. Flash forward to today and homeowner’s equity as of Q2/2008 rests at 44.66% and consumer credit has shot up to $363.1B. Additionally, net equity extraction has declined precipitously to $9.5B – probably reflecting the combined reality of less credit available via HELOCs and limted remaining equity in homes. Over the period from Q3/2001 until the Q2/2008, the total net equity extracted has been approximately $3.72T.

And all of this is happening on the backdrop of an economy for which consumer spending drives nearly 70% of GDP.

My 2 Cents worth of 2001 narrative: The broad economy stabilized but many households had one less income, reflected in the participation rate which never recovered. Once the employment situation allowed for enough comfort to do so, these households and others, decided to juice their lifestyles (despite new income levels) via equity withdrawal and spending on credit. (See chart at source 4 below)

Bottom line: be very wary of anyone who sounds like they are trying to replay the last recession. The conditions are vastly different and far more disturbing.

Sources:

1) Federal Reserve Data Series: FL155035015.Q, FL155035065.Q
2) http://www.bls.gov/cps/cpsatabs.htm
3) http://www.wealthscribe.com/wp-content/uploads/2008/11/equity-extraction-data-2008-q2.pdf

4) http://research.stlouisfed.org/fred2/series/REVOLNCB