Political Calculations
Unexpectedly Intriguing!
February 5, 2016

According to new jobless claims, economic distress within the U.S. has spread outside of the oil patch states, as what had been a trend of improvement stoked by falling oil prices has apparently come to a clear end.

Here is how we know. Thanks to our adaptation of a unique kind of statistical analysis that was originally developed by Bell Telephone's Walter Shewhart over 90 years ago to improve the quality of both manufactured goods and the processes used to produce them, we are able to identify major statistical trends in the rate of seasonally-adjusted new jobless claims, including the timing of when they begin and when they end, which we base on the rules developed by Western Electric to determine when a break in an established statistical trend has occurred.

Having laid that basic groundwork, lets start by looking at the most recent statistical trend for new jobless claims for the entire United States.

Residual Distribution for Seasonally-Adjusted Initial Unemployment Insurance Claims, 31 May 2014 - 30 January 2016

In this chart, we see that what we identify as "Trend N" is still intact, as all recent data points are within the range of values where we would expect to find them based upon the variation of the data with respect to the main overall trend since it began. This trend, which began when oil prices began falling in late June and early July 2014, has been characterized by the number of new jobless claims falling at an average pace of 400-500 per week.

We also observe that there is a microtrend within the data that suggests the larger trend may be breaking down, where all data points since 28 November 2015 falls on one side of the main trend line, but nothing as yet to confirm that it is on its way to fully breaking down.

Since global oil prices have been falling steadily since September 2015, so much so that average retail gasoline prices within the United States began dropping below the $2.21 per gallon level that marked the bottom of the previous fall in oil prices from July 2014 through January 2015, we quickly assumed that the increase in new jobless claims was likely happening in the eight states where high production cost oil industries represent a significant share of their local economies: Colorado, North Dakota, Ohio, Oklahoma, Pennsylvania, Texas, West Virginia and Wyoming.

So we next looked at just the jobless claims in these states, taking the non-seasonally adjusted data reported by the U.S. Department of Labor and seasonally adjusting it with the DOL's own seasonal adjustment factors for the nation as a whole. The resulting chart showing the recent trends in new jobless claims in these states is below.

Residual Distribution for Seasonally-Adjusted Initial Unemployment Insurance Claims, 31 May 2014 - 30 January 2016, 8 Fracking States

This chart is pretty remarkable in that what we identify as "Trend P8" is very well intact, with the most recent data points falling mostly within one standard deviation of the main trend line. As you can see, Trend P8 is characterized by a flat-to-slowly falling overall trajectory, which had its origins after the sharp increase in new jobless claims in these eight states during the first period of falling oil prices, as oil prices rebounded in the months from January 2015 through July 2015.

Though oil prices have fallen in each of the months since, there has been little change in that overall trajectory. Our thinking here is that the layoffs that occurred during the earlier fall in oil prices in these states effectively cleared the field for additional layoffs in these states, at least until oil prices drop below the level where they previously bottomed.

It has only been in very recent weeks where that has happened, so we'll continue monitoring new jobless claims in these states to see if our hypothesis is valid, as changes in new jobless claims tend to lag some 2 to 3 weeks behind the events that prompt changes in the outlook for businesses.

Of course, having isolated these 8 states means that we've also isolated the remaining 42 states outside of the oil patch. And there is where we see a significant statistical break in the trend that previously existed. Our next chart shows when that trend broke down.

Residual Distribution for Seasonally-Adjusted Initial Unemployment Insurance Claims, 31 May 2014 - 30 January 2016, 8 Fracking States

As we might expect, the statistical trends for the other 42 states outside of the high production cost oil states more closely resembles the overall national trends, as falling global oil prices have not negatively impacted the economies of these states the way it has in the oil patch. The most recent "Trend N42" has been characterized by a steadily falling level of new jobless claims each week, declining at a rate of 400-500 per week.

But all of the data in the nine weeks from 28 November 2015 onward has been above the main trend line, which violates Western Electric's Rule #4, which identifies this specific pattern as a very unlikely event for a well established statistical trend. Moreover, we also see that the micro-trend represented by this limited number of data points appears to be following an upward trajectory.

The new jobless claims data, coupled with the kind of statistical analysis that has been commonly used by U.S. manufacturing firms since the 1920s, is telling us that layoffs at U.S. firms are now on the rise in states that are outside of the oil patch.

That's not what we expected to see, and certainly isn't what we wanted to see, but there it is all the same.

Data Sources

U.S. Department of Labor. Unemployment Insurance Weekly Claims Data. [Online Database]. Accessed 4 February 2016.

U.S. Department of Labor. Unemployment Insurance Weekly Claims News Releases. [Online Database]. Accessed 4 February 2016.


Political Calculations. A Closer Look at New Jobless Claims. [Online Article]. 12 May 2011.

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February 4, 2016
CPAP Machine in Use - Source: Alabama Board of Home Medicine - http://www.homemed.alabama.gov/

People who suffer from sleep apnea don't have very many good options to cope with the condition.

The Mayo Clinic describes sleep apnea as "a potentially serious sleep disorder in which breathing repeatedly stops and starts." Aside from preventing people with the disorder from obtaining a good night's sleep, which leads to daytime fatigue, more severe forms of the condition can lead to host of more severe medical problems that result from having their body's consumption of oxygen interrupted, including high blood pressure, heart problems, an increased risk of stroke, Type 2 diabetes, metabolic syndrome and liver disease.

Treating more severe cases of the condition often involve the patient being prescribed to use a Continuous Positive Airway Pressure (CPAP) machine. Here, the patient straps a bulky mask and its connecting air hoses over their nose and mouth while sleeping, which if you can tell from the picture, doesn't appear to offer much in the way of comfort, even though they are effective in promoting uninterrupted breathing.

Via Core77, we learned of a new alternative device invented by Stephen Marsh that does away with much of the CPAP's bulky apparatus, reducing it to a relatively simple nosepiece that doesn't need to be hooked up with hoses to an air pump: the Airing:

But there's a catch. The Airing nose fitting device is only good for a one-time use, while a traditional CPAP machine is good for a number of years. If an individual with sleep apnea wanted to use the Airing as they slept each night, they would have to buy a supply that they would consume at a rate of one per day, at an estimated retail cost of $3.00 per device, which compares to the average expense of $850 for a CPAP machine, which typically last for 7 to 8 years before needing to be replaced.

We wondered which option would make more financial sense. It occurred to us that the choice is really the same as the choice of buying versus renting, which is a kind of math that we're very familiar with doing.

In the tool below, we've set the annual cost of "renting" as the choice to go with the Airing device, at it's estimated retail price of $3.00 per unit, times 365 days per year. The cost of buying then would be the $850 for the traditional CPAP machine.

We then set the inflation rate to 2.03%, which agrees with the OECD's long term projections for 7-8 years from the present, which covers the expected life of the CPAP unit.

Meanwhile, we set the cost of money to be equal to the current 13.1% that Bankrate.com indicates to be the average for a fixed-rate credit card.

All that said, let's do the math. If you're accessing this article on a site that republishes our RSS news feed, please click here to access a working version of the tool on our site.

Rent or Buy Information
Input Data Values
Cost to Rent "Uninterrupted Breathing"
Cost to Buy "Uninterrupted Breathing"
Net Rate of Inflation [%]
Cost of Money (Credit Card Interest Rate) [%]

Should You Buy or Rent "Uninterrupted Breathing"?
Calculated Results Values
"Profitability" of Buying "Uninterrupted Breathing"
The Bottom Line

With our default numbers, we find that it would be more financially advantageous for a sleep apnea sufferer to choose the CPAP over the Airing device.

Playing with the numbers, we found that the cost of the CPAP machine would have to exceed $9,900 in order for the Airing to become more advantageous from a cost perspective. Alternatively, the price of the Airing would have to drop to $0.25 per unit in order for it surpass the value of a CPAP.

That assumes that the nose fitting device would have to be disposed of daily. If the effective life of the Airing unit could be extended to last for 2 weeks, at an increased cost of $3.60 per unit, it would outmatch the average CPAP unit from a pure cost perspective.

But cost is not the only perspective to consider. If sleep apnea-afflicted consumers find that the greater comfort of the Airing nose fitting device is superior enough with respect to that of a CPAP machine while providing similar improved breathing as they sleep, then we can put a value on how much a night of uninterrupted breathing in greater comfort is really worth to someone with sleep apnea. It would be the difference between the estimated $3.00 retail cost of the Airing and its competitive-to-CPAP cost of $0.25 per unit, which works out to be $2.75 per night, or a little over 34 cents per hour (assuming 8 hours of sleep per night).

And to think - people without sleep apnea have no idea how much their uninterrupted breathing is actually worth!

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February 3, 2016

What are the odds that the winner of an political contest would be determined by their ability to win six, and just six, separate coin flips?

CBS Marketwatch details the drama from Iowa:

While it was hard to call a winner between Hillary Clinton and Bernie Sanders last night, it’s easy to say who was luckier.

The race between the Democrat presidential hopefuls was so tight in the Iowa caucus Monday that in at least six precincts, the decision on awarding a county delegate came down to a coin toss. And Clinton won all six, media reports said.

Iowa State Quarter - 2004 - Source: U.S. Mint - http://www.usmint.gov/kids/teachers/library/libraryDisplay.cfm?mediaID=424

So how "lucky" was Hillary Clinton so late in the evening of 1 February 2016?

We can find out by calculating the probability of correctly calling a coin toss six times in a row, which will tell us how likely that achievement really is. Here, each flip of the coin presents the people calling either heads or tails with a 50% chance of being right. But how do the odds of success change when a coin is flipped six times, where in order to be declared the winner of a contest, the outcome of the coin toss must be called correctly by a contestant all six times?

Well, we don't call ourselves Political Calculations for nothing. We built a tool to do that math! To find out what we did, just click the "Calculate" button below. (And if you're accessing this article on a site that republishes our RSS news feed, please click here to access a working version of our tool on our site.)

Binomial Probability Data
Input Data Values
Total Number of Opportunities [Must be 170 or lower to avoid maxing out the calculator!]
Number of Times the Outcome Goes a Particular Way
Percentage Odds of Outcome Occurring for Each Opportunity [%]

The Odds of That
Calculated Results Values
Percentage Odds of the Outcome Occurring the Entered Number of Times
Odds of the Event Occurring [1 in ...]

We find that the percentage odds of correctly calling the outcome of 6 coin tosses exactly 6 times by chance is 1.56%, or rather, the odds are that this exact outcome will occur by chance just once in 64 opportunities.

Which is also to say that there was a 98.44% chance that this outcome would not occur by chance.

As for how likely or unlikely that event is, we did some probability math with data for the Dow Jones Industrial Average that goes back to 2 May 1885, where we found that the odds of winning six out of six coin tosses is slightly more likely that seeing the value of the Dow close below its previous day's closing value on five consecutive days. That is something that has happened in real life some 482 times over the 35,889 days for which we have this data, which works out to be a 1.34% probability of occurring by chance.

The bottom line is that it's unlikely that chance alone explains the outcome of a political candidate winning six out of six coin tosses, but it's not as completely improbable as you might think.

And for the record, we've routinely done far more improbable things than that for years!

Elsewhere on the Web

Richard Lowry presents the detailed calculations and an online calculator for finding binomial probabilities that gets around our tool's limitation of 170 opportunities!

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February 2, 2016

Just one week ago, we observed that the pace of dividend cuts being announced in the first quarter of 2016 was "slower than at the same point of time in the first quarter of 2015. Which is an early indication that the U.S. economy is so far performing better than it did a year ago."

This week, there is no better way to describe what happened to the pace of dividend cut announcements than to consider the immortal words of Ron Burgundy from the documentary Anchorman.

Now, look at the following chart to see why those words have become applicable to today's stock market.

Cumulative Announced Dividend Cuts in U.S. by Day of Quarter, 2015-Q1 versus 2016-Q1, Snapshot on 29 January 2016

As Ron Burgundy might say: "Boy, that escalated quickly... I mean, the apparent level of distress in the U.S. economy really got out of hand fast."

The chart above, with data through the last day of trading in January 2016, is based on our compilation of data reported by Seeking Alpha's Market Currents Dividend News and the Wall Street Journal's Dividend Declarations database.

We see that the pace of dividend cuts accelerated significantly in the last week of January 2016, rising from being just above a level that would merely suggest that recessionary conditions are present in the U.S. economy to falling right in the middle of the borderline region that suggests that a significant portion of the U.S. economy is experiencing some degree of outright contraction.

Looking at the companies whose announced dividend cuts were reported by our two real-time news sources, we find that all but three of the announcements in January 2016 were made by firms in the oil producing sector of the U.S. economy. For the other three, staffing firm CDI Corporation (NYSE: CDI) places a lot of contract employees at U.S. oil producers, CSI Compressco (NASDAQ: CCLP) provides manufacturing services to the oil industry, and only New York Community Bankcorp (NYSE: NYCB), whose dividend cut following its acquistion of another bank was finally recorded after it first announced it would take this action back in November 2015, can be considered to not have been influenced by increasing distress among U.S. oil producers.

But at a combined total of 22 dividend cuts (24 if we include the duplication of earlier dividend cut announcements by Kinder Morgan (NYSE: KMI) and Teekay Corporation (NYSE: TK), our two sources of real-time dividend cuts announcements fell far short of the full total of 55 that was reported by Standard and Poor for the month of January 2016.

Monthly Number of Public U.S. Companies Announcing Dividend Cuts, January 2004 through January 2016

Assuming that S&P's count of dividend cut announcements is not revised, this figure indicates that a significant part of the U.S. economy is experiencing a moderate-to-severe level of contraction.

Our updated chart also provides an opportunity to highlight the key factors that are negatively impacting the U.S. economy: the ongoing distress in the U.S. oil producing industry, which is the result of the significant decline in global oil prices that has hammered the industry's revenues, and also the recent rate hike by the U.S. Federal Reserve, which has increased the costs for a number of interest-rate sensitive firms, such as mortgage-related Real Estate Investment Trusts.

The bottom line? Something is badly broken within the U.S. economy. That thing is primarily the U.S. oil production industry and also industries that are especially sensitive to interest rate hikes. According to dividends, falling oil prices and poorly considered interest rate hikes by the Federal Reserve are responsible for the increase in distress that took place in January 2016.

Data Sources

Seeking Alpha Market Currents Dividend News [Online Database]. Accessed 31 January 2016.

Wall Street Journal. Dividend Declarations. [Online Database]. Accessed 31 January 2016.

Standard and Poor. Monthly Dividend Report. [Excel Spreadsheet]. Accessed 1 February 2016.

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February 1, 2016

What if you had advance knowledge of how the U.S. stock market would behave in the upcoming week? Or at the very least, you were told by someone who works in the future exact how the market would respond to a given set of circumstances that would be likely to play out in the week ahead, but not exactly when the market when the market would react to those circumstances.

Would you be able to craft an investment strategy that would be able to take advantage of such foreknowledge?

We ask, because last week, we wrote the following:

In this next week, the Federal Reserve's Open Market Committee will command an outsized portion of the attention of investors on Wednesday, 27 January 2016. In addition, earnings season continues as a number of very large companies, especially in the distressed oil industry, will be announcing their earnings and addressing investors regarding their business outlook during the week.

With investors currently focused on 2016-Q2, should the Fed hold tight to its plans to hike short term interest rates again before the end of 2016-Q1 at the same time that U.S. firms announce that their outlooks are less bright than currently expected, it is highly likely that investors will once again shift their attention back to 2016-Q1, sending stock prices considerably lower.

On the other hand, should the Fed indicate it will adopt a more dovish stance combine with news that troubled U.S. firms see the potential for real improvement in their outlook by the end of the year, then we could see a fairly strong rally as investors shift their focus to more distant future quarters.

And if the combination of market driving news mixes elements of these two scenarios, then it's likely that the market will stabilize somewhat and largely move sideways within a relatively narrower range than the previous week during the week to come.

Back then, that was the future, as expressed in what might as well have been a sequence of "If-Then" statements from high school geometry. Now, here is how Week 4 of January 2016 actually played out. First, for 2016-Q1 to date:

Alternative Futures - SP 500 - 2016Q1 - Standard Model - Snapshot on 29 January 2016

And in the larger scale of 2016 to date:

Alternative Futures - SP 500 - 2016 - Standard Model - Snapshot on 29 January 2016

Here were the week's main events:

  • 25 January 2016: Stock prices fell as investors shifted their forward-looking focus toward 2016-Q1, as oil prices continued sliding as the future outlook for energy firms dimmed.
  • 26 January 2016: Even though the news that China's stock markets plunged more than 6% opened the day, the combination of a rebound in oil prices and positive earnings reports brightened the outlook of investors, who shifted their focus back toward 2016-Q2, in a day whose trading was described as "schizophrenic".
  • 27 January 2016: Investors remained tightly focused on 2016-Q2, all the way up until the Federal Open Market Committee of the Federal Reserve announced that it would leave interest rates unchanged in January. The initial reaction of the statement was negative, sending stock prices lower as investors shifted their attention back toward 2016-Q1 in setting today's stock prices, as they initially interpreted the statement to indicate that the Fed would hold to its previously announced plans. However, a deeper analysis of the FOMC's statement revealed the Fed was backing off those plans somewhat, citing its concerns for "global tumult". The S&P 500 rebounded on that latter assessment, closing the day with investors returning their focus to 2016-Q2 as they give just over a 50% probability that the Fed might hike short term interest rates before the end of June 2016.
  • 28 January 2016: The S&P 500 was little changed on Thursday, as the Fed's communicated change in stance becomes more widely understood.
  • 29 January 2016: Global tumult arrives well before the market opens, as the Bank of Japan announces that it will adopt a negative interest rate policy, in direct opposition to its public statements of its policy plans from a week earlier. With the Fed having cited its global concerns, investors shift their forward-looking focus to the more distant future quarter of 2016-Q3, reinforced by a weaker than expected initial report for GDP in the fourth quarter of 2015, hopes that a deal to limit the supply of oil in a glutted market would be reached, and also the confirmation by two Fed officials that the Fed was indeed backing off its previously planned pace for interest rate hikes.

Before concluding with what we really want to get to in this post, let's take a closer look at the reported comments of San Francisco Federal Reserve Bank president John Williams from Friday, 29 January 2016 to understand why investors only shifted their focus to 2016-Q3 and not, as yet, to a more distant future quarter as they consider the likely timing of the Fed's next change in the level of U.S. short term interest rates:

At the time, officials at the Fed, the U.S. central bank, had as a group expected about four further rate hikes this year, and Williams had said that was in line with his own expectation.

That view appears to have changed, after investor worries about a global slowdown and weakness in China sent equities and oil prices plunging through most of January. Meanwhile the dollar has strengthened, pushing down on U.S. inflation, which is running well below the Fed's 2-percent target.

"Standard monetary policy strategy says a little less inflation, maybe a little less growth ... argue for just a smidgen slower process of normalizing rates," Williams said.

"We got a little stronger dollar, some mixed data on the economy, some weakness in (fourth-quarter U.S. GDP growth), all of those coming together kind of tell me that we probably need a little bit more monetary accommodation this year than I was thinking in the middle of December."

Getting back to what we really want to get at, do you see how all these changes in the value of the S&P 500 were specifically covered in our If-Then conditions representing how stock prices would be most likely to behave during the fourth week of 2016?

And since they were, the question of how you as an investor could have taken advantage of the foreknowledge of how stock prices would behave under the circumstances we described, but not the knowledge of the exact timing of when the changes in stock prices we described would take place, is a very open question. One where the strategies you might have used in the fourth week of January 2016 would be very similar to what you might do in future weeks when similar circumstances come back into play.

So what would you have done with your investments to maximize your returns given these circumstances (and the benefit of 20-20 hindsight)? If you're reading this article on Seeking Alpha, we'll monitor the responses addressing that question in the comments over the next week, and will share the more interesting strategies that are put forward through that venue in our next discussion of our alternative futures model for the S&P 500.

Previously on Political Calculations

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Welcome to the blogosphere's toolchest! Here, unlike other blogs dedicated to analyzing current events, we create easy-to-use, simple tools to do the math related to them so you can get in on the action too! If you would like to learn more about these tools, or if you would like to contribute ideas to develop for this blog, please e-mail us at:

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