Political Calculations
Unexpectedly Intriguing!
February 9, 2016
Junk in Your Trunk Sale - Source: Aberdeen, WA - http://www.aberdeenwa.gov/wp-content/uploads/Junk-in-the-Trunk.pdf

Yesterday, the news broke that the Apollo Education Group (NASDAQ: APOL) has successfully negotiated the sale of itself to a group of private investors. Once approved, the $1.1 billion sale of the Apollo Education Group to the Vistria Group, which is affiliated with Apollo Global Management (NYSE: APO), and the private investment firm Najafi Companies would be expected to be closed in August 2016, just ahead of the education company's academic year..

What won't be part of the sale is the Apollo Group's Carnegie Learning division, which we've previously described as "damaged goods", where we had concluded our previous analysis of the division as follows (emphasis added):

Any potential buyer for Carnegie Learning can expect that the University of Phoenix will not be a customer for the division's products. The Apollo Group recorded a $13 million write off for "certain Carnegie Learning technology intangibles that were no longer being used. The associated technology had been incorporated into University of Phoenix’s academic platform and as a result of the University ceasing use of the technology, no future cash flows associated with the technology were expected over its remaining useful life."

That's a major vote of no confidence in Carnegie Learning's products. Especially from an education institution that has so thoroughly degraded its academic standards for evaluating student performance in math so much, especially as compared to other institutions.

From a business perspective, the failure of Carnegie Learning's math curricula products at the University of Phoenix would suggest that if a sale is made, it will be at an extreme discount with respect to the $75 million price that the Apollo Education Group paid in acquiring the operation.

We suspect however that the more likely disposition for Carnegie Learning will be for its remaining assets to be unloaded to multiple buyers as part of the division's outright liquidation, as they will prove to be worth more than its future prospects as an ongoing business.

We were wrong about two things in the sections of the above passage that we highlighted. First, we were wrong that the Apollo Education Group's purchase price of Carnegie Learning was just $75 million. In reality, that $75 million was indeed the amount they paid for Carnegie Learning, Inc., but the Apollo Education Group also agreed to pay an additional $21.5 million to acquire additional technology from Carnegie Mellon University to support its acquisition, which it agreed to pay over a 10 year period.

Second, our assessment that outright liquidation would be the most likely disposition for the Apollo Education Group's Carnegie Learning division has turned out to be incorrect. It would appear that the Apollo Education Group did manage to find a single buyer for its damaged goods, which it disclosed through its 10-Q statement back on 11 January 2016. Here is the relevant part of the statement, which also outlines the depreciated value of the other assets it acquired as result of its purchase of Carnegie Learning:

During the first quarter of fiscal year 2016, we completed the sale of Carnegie Learning for a nominal amount resulting in a $2.8 million loss on sale. We do not have significant continuing involvement with Carnegie Learning after the sale.

During fiscal year 2015, we began presenting Carnegie Learning’s assets and liabilities as held for sale on our Condensed Consolidated Balance Sheets and its operating results as discontinued operations on our Condensed Consolidated Statements of Operations for all periods presented. As discussed further in Note 17, Segment Reporting, Carnegie Learning’s operating results were previously included in Other in our segment reporting, and certain additional Carnegie Learning expenses associated with University of Phoenix’s use of Carnegie Learning technology were included in our University of Phoenix reportable segment.

The major components of Carnegie Learning’s assets and liabilities presented separately as held for sale on our Condensed Consolidated Balance Sheets as of August 31, 2015 are as follows:

($ in thousands)
As of
August 31, 2015

Accounts receivable, net

Property and equipment, net

Intangible assets, net


Allowance for reduction of assets of business held for sale
Total assets

Deferred revenue


Total liabilities

In being sold for a claimed $2.8 million loss, can you say "extreme discount"?

The sale of Carnegie Learning to a private investor group was facilitated by Tyton Partners, which was previously known as Education Growth Advisors. The firm works closely with private equity firm Education Growth Partners, which while not identified in the Apollo Education Group's SEC filings, is whom we believe is the most likely acquirer of what remains of Carnegie Learning based upon the kinds of firms they've bought in previous acquisitions.

Unofficially, we're happy that our "damaged goods" post helped the purchaser set their price for taking on the remnants of Carnegie Learning's operations, where in the absence of the analysis we provided, they might have otherwise paid far more than they should.

And with Carnegie Learning finally off its books, the fire sale of the Apollo Education Group's remaining damaged goods, itself, would appear to be successful. For a firm whose market cap once peaked at $16.46 billion back in May 2004, its sale price of $1.1 billion indicates that it sold at a discount of 93.3% with respect to its peak valuation.

By our estimates, from the time we decided to take on the Apollo Education Group's problems back on 21 May 2015, the firm lost over $1 billion of its market value, which fell from $1.784 billion on 18 May 2015 to $0.754 billion on 5 February 2016.

Unofficially, we're happy to have helped accelerate the market consensus in determining the Apollo Education Group's true diminished value.

Labels: ,

February 8, 2016

At the end of the last week of January 2016, stock prices rallied on the news that the Bank of Japan would implement negative interest rates in that country and that the Fed was likely to back off its plans to hike interest rates again before the end of 2016-Q1.

In the first week of February 2016, investors started the week still focuses on 2016-Q3, but quickly shifted their attention back toward the near term, holding it on 2016-Q2 through the end of the week, which is why stock prices fell on Tuesday, 1 February 2016, was largely flat through Thursday, 4 February 2016, and then fell again on Friday, 5 February 2016, as investors ended the week splitting their focus between 2016-Q1 and 2016-Q2.

Alternative Futures - S&P 500 - 2016Q1 - Standard Model - Snapshot on 2016-02-05

Click here to see what this chart looked like last week. Here are the main news events that drove the outcome we see in the chart above.

  • 1 February 2016: On a day with little other news to affect their forward-looking focus, investors maintained their focus on 2016-Q3, following the news during the weekend that the Fed's vice chairman Stanley Fischer had indicated that the Fed was concerned about market volatility resulting from the global economic slowdown.
  • 2 February 2016: Investors were compelled to shift their attention toward the nearer term, specifically to 2016-Q2, as the third largest company in the S&P 500, ExxonMobil (NYSE: XOM), reported that its profits had tumbled by 58%, and that it would slash its planned capital expenditures by 25%, signalling that even the largest firms in the U.S. energy sector would not escape being negatively affected by the oil industry's ongoing distress. At the same time, other firms indicated that they were also likely to cut back on their capital investments, suggesting that they also expected weaker growth ahead.
  • 3 February 2016: The day started strong, as New York Fed president Bill Dudley emphasized his concerns that the strong U.S. dollar would lead to "significant consequences", leading investors to once again shift their focus toward 2016-Q3 again as the statement suggested he would not support another rate hike before that time. Trading during the day was volatile however, and the market ended up by a small margin to close the day as oil prices appeared to firm up.
  • 4 February 2016: Stocks prices rose along with commodities as the U.S. dollar weakened. However, the upside potential of that news was muted as U.S. investors resumed their focus on the near term as Cleveland Fed president Loretta Mester offered her comments suggesting that she still thinks the Fed should jack U.S. interest rates higher, as she believes the U.S. economy's poor performance in recent months is just a short term "soft patch".
  • 5 February 2016: A "good" employment situation report for January 2016 opens the door to the Fed continuing its planned interest rate hikes, which leads investors to pull their forward-looking attention even closer to the near term, causing stock prices to fall in response.

Let's discuss some of the dynamics that were at work in the market during the week. First, the fall of stock prices on Tuesday, 2 February 2016 in response to ExxonMobil's earnings news.

Here, the worsening of the expected outlook for U.S. oil producers caused investors to focus more on the nearer term because of the impact that change would have on that industry and because of the timing of when that impact would be felt. As it happened, the oil companies that reported earnings in the first week of February 2016 consistently indicated that they were also cutting back on their planned capital investments, indicating that they see little prospects for growth ahead, and one, ConocoPhillips (NYSE: COP), went so far to cut its dividend too.

At the beginning of this article, we stated that as of Friday, 5 February 2016, investors were splitting their forward-looking attention between 2016-Q1 and 2016-Q2, although if you look closely at our chart, it would appear that investors were tightly focusing their attention to 2016-Q2.

The only reason it appears that way is due to our use of historic stock prices as the base reference points from which we project the alternative trajectories of future stock prices, where the echoes of the market's activity from 13 months ago, 12 months ago and 1 month ago contribute to our projections. In this case, the echoes of that past volatility makes it appear that investors are closely focused on 2016-Q2 in our model, rather than splitting their focus between 2016-Q1 and 2016-Q2. (The quick and easy way to confirm that assessment is to simply connect the dots for each of the alternative trajectories on each side of the volatility indicated by the short term echo event.)

Finally, on an upcoming programming note, we plan to follow up our post last week where we sought feedback from readers on Seeking Alpha on how to exploit the kind of information our futures-based model can provide later this week.

Previously on Political Calculations

Labels: ,

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.

Labels: ,

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!

Labels: , , ,

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!

Labels: , ,

About Political Calculations

blog advertising
is good for you

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:

ironman at politicalcalculations.com

Thanks in advance!

Recent Posts


This year, we'll be experimenting with a number of apps to bring more of a current events focus to Political Calculations - we're test driving the app(s) below!

Most Popular Posts
Quick Index

Site Data

This site is primarily powered by:

This page is powered by Blogger. Isn't yours?

Visitors since December 6, 2004:

CSS Validation

Valid CSS!

RSS Site Feed

AddThis Feed Button


The tools on this site are built using JavaScript. If you would like to learn more, one of the best free resources on the web is available at W3Schools.com.

Other Cool Resources

Blog Roll

Market Links
Charities We Support
Recommended Reading
Recommended Viewing
Recently Shopped

Seeking Alpha Certified

Legal Disclaimer

Materials on this website are published by Political Calculations to provide visitors with free information and insights regarding the incentives created by the laws and policies described. However, this website is not designed for the purpose of providing legal, medical or financial advice to individuals. Visitors should not rely upon information on this website as a substitute for personal legal, medical or financial advice. While we make every effort to provide accurate website information, laws can change and inaccuracies happen despite our best efforts. If you have an individual problem, you should seek advice from a licensed professional in your state, i.e., by a competent authority with specialized knowledge who can apply it to the particular circumstances of your case.