Selasa, 10 Juli 2012

The Dividend Doldrums

Since 2012's first quarter earnings season ended, there has been very little change in the expected future level of dividends per share for the U.S. stock market:

Expected Future Trailing Year Dividends per Share for the S&P 500, 6 July 2012

Is it really all that surprising then that stock prices have largely languished in the time since?

It's true - aside from being pumped up by noise from the news and rumors of actions to prop up the failing governments of the Euro zone, stock prices have basically just gone sideways since:

SP 500 3-month chart ending 6 July 2012

In fact, stock prices would have gone lower if not for all the noise of central bank rescue rumors of fiscally-failing nations in the Eurozone! You can see that in the spike in our chart below for June 2012:

Accelerations of S&P 500 Average Monthly Index Value and Trailing Year Dividends per Share, with Futures as of 6 July 2012

As for where stock prices are today, they're still a bit elevated, but as you can see in the chart above, they're pretty close to converging with where investors focused on the expected level of dividends for the first quarter of 2013 would put them.

But looking at that chart, a good question to ask is when will the expectations for dividends in the second quarter of 2013 begin driving stock prices?

The answer, as best as we can tell right now, is sooner than you might think, and with much less benefit than you might imagine.

Which is all probably the best we can hope for in this summer of dividend doldrums!

Senin, 09 Juli 2012

The Brightest Spot in the June 2012 Jobs Report

If the major headlines posted on Google News on Friday, 6 July 2012 are any indication, the June 2012 Employment Situation Report for the United States was "tepid" at best, and "dismal" at worst.

But we found a bright spot! For one select group of Americans, June 2012 represented the best month ever since the total employment level of the U.S. economy peaked in November 2007, just before the so-called "Great Recession" officially began!

Even better, the gain in jobs for this group was enough to increase their numbers in the U.S. workforce to levels not seen since September 2009, just three months after the so-called "Great Recession" officially ended!

Who is this mysterious select group of Americans who prospered while so many others suffered? Are they the evil 1%?

Let's make that the evil 3.2%. The brightest spot in the June 2012 jobs report is represented by U.S. teens, who saw their numbers among the 142,415,000 Americans counted as being employed jump upward by 140,000, increasing to 4,528,000, or 3.2% of the entire U.S. workforce:

Change in Number of Employed by Age Group Since Total Employment Peak Reached in November 2007

The last time there were more teens with jobs in the U.S. was September 2009, when 4,641,000 people between the ages of 16 and 19 were counted as being employed. Oh, and every month before that going back to March 1965.

So why are teens making out so well in this first month of summer while everyone else, well, isn't? The Daily Kos reports from 5 May 2012:

President Obama's Summer Jobs+ program, which is lining up commitments from the private sector and from government to create summer jobs and internships for young people, has announced commitments for 90,000 paying jobs, up from the 70,000 previously announced in January, with many more unpaid internships and mentorships (which absolutely must be strictly overseen so that kids aren't just used as free labor without gaining skills or prospects; unpaid work of any kind is a poor enough substitute for paid work without being directly exploitative).

You don't suppose those commitments to hire teens are taking money and resources away from those companies being able to hire others at this time, do you?

Jumat, 06 Juli 2012

Inventions for Everything

Having previously featured the best mousetrap ever, which was invented in 1881, we decided to see if there were any modern day patents that might compare in creativity.

And then we found the invention we're featuring today.

The invention we're featuring today is real. Really. You can look it up at the U.S. Patent and Trademark Office, under its patent number 6,293,874, which was issued on 25 September 2001, if you don't believe us.

It, as it happens, is, well, there really aren't any words we can use to describe it, so we'll let its inventor, Joe Armstrong of Lenoir, Tennessee, explain it via the patent's abstract, which describes, and we kid you not, a "User-operated amusement apparatus for kicking the user's buttocks". Really. We can't make this stuff up....

An amusement apparatus including a user-operated and controlled apparatus for self-infliction of repetitive blows to the user's buttocks by a plurality of elongated arms bearing flexible extensions that rotate under the user's control. The apparatus includes a platform foldable at a mid-section, having first post and second upstanding posts detachably mounted thereon. The first post is provided with a crank positioned at a height thereon which requires the user to bend forward toward the first post while grasping the crank with both hands, to prominently present his buttocks toward the second post. The second post is provided with a plurality of rotating arms detachably mounted thereon, with a central axis of the rotating arms positioned at a height generally level with the user's buttocks. The elongated arms are propelled by the user's movement of the crank, which is operatively connected by a drive train to the central axis of the rotating arms. As the user rotates the crank, the user's buttocks are paddled by flexible shoes located on each outboard end of the elongated arms to provide amusement to the user and viewers of the paddling. The amusement apparatus is foldable into a self-contained package for storage or shipping.

This is one of those times where a picture really is worth more than a thousand words:

U.S. Patent 6,293,874, Figure 2

You know, on second thought, perhaps we should build one of these for the patent examiners who approve stuff like this, who clearly need this kind of self-training device!...

Kamis, 05 Juli 2012

Mapping the Criminal Ecosystem

Source: CNN - 2003 Gang Turf in Hollenbeck
What do lions, coyotes and L.A. gangbangers have in common?

Would you believe that the same math that describes how predators in the animal kingdom stake out their territory can be used to identify the boundaries between the turf claimed by rival gangs? The evidence comes from the UCLA Newsroom:

A mathematical model that has been used for more than 80 years to determine the hunting range of animals in the wild holds promise for mapping the territories of street gangs, a UCLA-led team of social scientists reports in a new study.

"The way gangs break up their neighborhoods into unique territories is a lot like the way lions or honey bees break up space," said lead author P. Jeffrey Brantingham, a professor of anthropology at UCLA.

Further, the research demonstrates that the most dangerous place to be in a neighborhood packed with gangs is not deep within the territory of a specific gang, as one might suppose, but on the border between two rival gangs. In fact, the highest concentration of conflict occurs within less than two blocks of gang boundaries, the researchers discovered.

The math the UCLA researchers used is the Lotka-Volterra equations, which were developed in the 1930s to describe how predator and prey species interact over time. The UCLA press release explains what the math describes:

The equations are based on the principle that competition between groups determines where the boundaries between rivals form, and even a tiny amount of competition is enough to cause territories to form.

"What's at work is a competitive balancing act where both gangs are trying to keep their rival as far away as possible," Brantingham said.

The model the researchers derived from the equation predicted that gang boundaries would form midway between the home bases of rivals and would run in a perpendicular line between them.

Seems pretty straightforward and simple, right? Let's see how the study fared when real world data from Boyle Heights, an area within Los Angeles' Police Department's Hollenbeck division, was considered:

The team looked at 13 gangs in the 6.5-square-mile area of Boyle Heights, a densely populated neighborhood on Los Angeles' east side that is bounded by three freeways. Gang activity tends to be confined within the freeway-bounded area.

To determine the home bases for each gang, the researchers relied on a prior study by Tita and his UC Irvine colleagues. The locations of the home bases ranged from a specific street corner to someone's house, a neighborhood business or any other specific location where a gang gathers most frequently.

Using the Lotka–Volterra formula, Brantingham's team drew boundaries between the known gangs. Unlike law enforcement's maps, the resulting effort did not produce gang boundaries that neatly followed streets. Instead, the boundaries ran through the yards of homes and businesses and through alleyways. When the boundaries did land on streets, they were as likely to crisscross them as follow them.

Here's an example of the map UCLA's social scientists produced (excerpted from here):

Note how different it is from CNN's 2003 map of the area's gang territories, which closely follows streets.

Now, mapping out where gang crime actually occurred in the years from 1999 through 2002:

Using police records, the researchers then mapped 563 known gang crimes that occurred between 1999 and 2002 and have been attributed by police to at least one of the 13 gangs. To their surprise, most of the crimes fell on the borders that the model laid between gang territories. When crime locations did deviate from the borders, they did so in a configuration that was consistent with the model. For instance, the theory predicted that 58.8 percent of the crimes would occur within one-fifth of a mile of the border between two gangs — or just under two blocks — and 87.5 percent within two-fifths of a mile of the border — or just over three blocks. Overall, 99.8 percent of crimes could be expected to occur within one mile of the border, according to the theory.

Reality turned out to be pretty close to the theory:

In fact, the team found that 58.2 percent occurred within two blocks of the border and 83.1 percent within just over three blocks of the border; in total, 97.7 percent of the crimes took place within one mile of the border between gangs.

It's like economics in a way - the most significant activity happens at the margins. But here, the typical transactions involve assault and murder. The areas closest to these margins, or boundaries between territories controlled by different gangs, account for over half of all gang crime recorded between 1999 and 2002!

More interestingly though, we find that its the competition between adversaries that defines where the boundaries between them form, rather than vice versa.

Elsewhere on the Web

Jeff Brantingham, one of the study's authors, has put other mathematical models to work to map out areas where burglars are most likely to be operating. The early results suggest that applying the math to direct police patrols may have reduced burglaries in some areas of Los Angeles by as much as 25%.

References

Brantingham, P. J., Tita, G. E., Short, M. B. and Reid, S. E. (2012), The Ecology of Gang Territorial Boundaries. Criminology. doi: 10.1111/j.1745-9125.2012.00281.x. 25 June 2012. [Ungated Version: Adaptation of an Ecological Territorial Model to Street Gang Spatial Patterns in Los Angeles.]

Rabu, 04 Juli 2012

Selasa, 03 Juli 2012

Testing a Hypothesis for New Jobless Claims

Do high gasoline prices affect the number of layoffs in the United States?

We're going to put our empirical observation-backed hypothesis that "Yes. Yes They Do" to the test during the next several weeks to see if we can get a solid answer to that question!

Here, we're defining "high gasoline prices" as being when the average price of a gallon of regular (unleaded) gasoline in the U.S. exceeds $3.50 per gallon in terms of 2011-12 U.S. dollars, as reported by the U.S. Energy Information Agency. We're also measuring the number of layoffs in the U.S. by the number of seasonally-adjusted initial unemployment insurance claims that are filed each week, as reported by the U.S. Department of Labor.

The test we're about to run hinges on an event that occurred in the week between 18 June 2012 and 25 June 2012, when the average price of gasoline in the United States fell back below the $3.50 per gallon mark.

Here, if our hypothesis holds, we'll see a shift in the trend for new jobless claims being filed some two to three weeks later, as employers react to this positive development which reduces their cost of doing business and also increases the disposable income of U.S. consumers after their current pay cycle ends and their next pay cycle begins.

Since most people in the U.S. are paid on a weekly, biweekly, or semi-monthly basis, that means a two to three week delay between when an event affecting employee retention decisions takes place to when it actually shows up in the weekly data for new jobless claims in the U.S.

After that, it can take several weeks longer to confirm the change in trend. Speaking of which, our chart below shows the previous two trends, along with the current trend:

Residual Distribution for Seasonally-Adjusted Initial Unemployment Insurance Claims, 26 March 2011 - 23 June 2012

We could see a shift begin as early as this week or next, however we expect it will be several weeks beyond that before we could confirm such a shift in the trend, given the effect the Fourth of July holiday will likely have on data reporting and the BLS' continuing issues with upward revisions to their initially-reported data in subsequent weeks.

Senin, 02 Juli 2012

Forecasting GDP for 2012Q2

Now that the U.S. Bureau of Economic Analysis has released its third estimate of GDP in the first quarter of 2012, we can now officially project where U.S. GDP for the second quarter of 2012 will be when it is nearly finalized three months from now!

Our chart below shows the forecast, expressed in terms of the inflation-adjusted chained U.S. dollars of 2005:

Real GDP vs Climbing Limo Forecast vs Modified Limo Forecast, 2003-Present

Going by our preferred Modified Limo forecasting technique, we see a 50% probability that real GDP in 2012-Q2 will be over $13,572.5 billion, and a 50% probability that it will be under that level.

We'll also give the following odds that it will be between the indicated values (again, in terms of constant 2005 U.S. dollars):

  • A 68.2% probability of being between $13,367.7 billion and $13,649.9 billion.

  • A 95.0% probability of being between $13,226.6 billion and $13,790.9 billion.

  • A 99.7% probability of being between $13,085.5 billion and $13,932.0 billion.

Looking at our forecast for 2012-Q1 from three months ago, where we had forecast that GDP in the first quarter of 2012 would be finalized at or near a mid-range value of $13,508.8 billion in terms of 2005 U.S. dollars, we were off the BEA's third (and for now, final) estimate of $13,491.4 billion by 0.13%.