Political Calculations
Unexpectedly Intriguing!
January 27, 2015

From our perspective, the most important and useful part of the Efficient Markets Hypothesis (EMH) is its assumption that asset prices change quickly to reflect the impact of new information upon the future expectations of investors.

So what does the ability of investors to collectively and efficiently absorb and assess new information and to communicate the changes in their outlook through asset prices tell us about what the U.S. Federal Reserve is likely to do with respect to its plans to hike short term interest rates?

Well, if we go by how U.S. stock prices responded after the European Central Bank (ECB) announced its Quantitative Easing (QE) program on 22 January 2015, the immediate assessment of U.S. investors was that the Fed will most likely implement its rate hike plans sooner rather than later. We can see that shift in the sudden change in the trajectory of the S&P 500, where it has gone from following the trajectory associated with an investor focus on 2015-Q4, which is consistent with what had been the growing consensus that the Fed would delay its rate hikes until then, to the nearer-term future associated with a forward-looking focus on 2015-Q2, which investors would now appear to consider to be more likely.

Shift in S&P 500 Stock Prices from 2015-Q4 Trajectory to 2015-Q2 Trajectory on 22 January 2015 following ECB Announcement of QE

That assessment will most likely be confirmed after the Federal Reserve's Open Market Committee concludes a two-day meeting on Wednesday, 28 January 2015 and issues a new policy statement. The Wall Street Journal explains why investor expectations would change in response to the ECB's decision in its schedule of economic news events for the week.

U.S.: 2:00 p.m. EST. Federal Open Market Committee’s monetary policy announcement:

After the ECB’s bombshell news of last week, all eyes now turn to the Fed. If it signals its continued intent to raise rates in the months ahead, this will likely drive even more fund flows into the dollar. How the Fed views that ECB move will be key. If it interprets it as an effective move to restore growth in the eurozone, it will see it as constructive to U.S. growth and likely want to stay the course and move toward higher rates sometime in the last spring or summer. If it instead focuses on the surge in the dollar that has come from the ECB move, it could be inclined toward holding back because of the disinflationary effect of that.

We already know that the Fed pays very close attention to the stock market in weighing their future actions, which we observed previously during their own QE programs. The reaction of the U.S. stock market to the ECB's action to initiate a QE program for the EU is such that the Fed is likely to hike short term interest rates in the US above their current 0-0.25% range by the end of 2015-Q2.

And that will hold until newer information might force the Fed to adapt its plans.

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January 26, 2015
The Science of NFL Football - Source: National Science Foundation http://www.nsf.gov/news/special_reports/football/

Can physics explain what's wrong with Tom Brady's balls?

We're going to find out. Picking up on the speculation offered by a Boston sportswriter, who argued that weather alone was responsible for half of the underpressurization found in 11 of the 12 balls that the New England Patriots' offense brought with them to the 2015 AFC Championship game, we thought we'd check their math.

It's a good thing that we did, because they botched it. Badly.

We know that because of the physics that applies here, the combined gas law, which defines the relationship that exists between the internal pressure, volume and temperature of an enclosed vessel like a football will be a constant. That means that we can nearly perfectly predict how much the internal pressure, or inflation, of a football might change when the temperature of the ball changes from one point in time to another, using the following formula:

Combined Gas Law - Source: Wikipedia http://en.wikipedia.org/wiki/Combined_gas_law

We're going to do that math using the information we know about the situation. We'll assume that the footballs were inflated at a temperature of 68 degrees Fahrenheit, which is consistent with the interior thermostat setting recommended by the U.S. Department of Energy for optimal personal comfort and low energy consumption in the winter, the gametime temperature of 51 degrees Fahrenheit, the minimum acceptable inflated pressure specified by the NFL's rules of 12.5 pounds per square inch, and the approximate internal volume of the football of 258.5 cubic inches, which we'll assume is unchanged from the time when the footballs were filled and checked to when they were discovered to have deflated by roughly 2.0 pounds per square inch.

Enough talk - let's do some math using the tool we built just for that purpose!

Football Inflation Data Before the Game
Input Data Values
Initial Measured Internal Pressure [psi]
Initial Volume [cubic inches]
Initial Temperature [degrees Fahrenheit]
Football Inflation Data at Halftime
Internal Pressure at Halftime [psi]
Volume at Halftime [cubic inches]
Temperature at Halftime [degrees Fahrenheit]

How Much of Football Deflation Is Explained by Weather?
Calculated Results Values
Expected Internal Pressure of Footballs at Halftime
Actual Internal Pressure of Footballs at Halftime
Percentage of Change in Pressure Explained by Change in Temperature
If you're reading this article on a site that republishes our RSS news feed, click here to access a working version of this tool!

So we find that, at best, the change in temperature in going from a room inside the stadium where the internal pressures of the footballs the New England Patriots brought to the game were inspected to on the field during the game can only, at best, explain 20% of the change in pressure that was measured.

We were curious to find out what of temperature would have to be held in order to produce the observed amount of deflation, and used trial and error in our tool above to find that Tom Brady's balls would have had to have been inflated and inspected at a temperature of 148.4 degrees Fahrenheit to account for a decrease in internal pressure from 12.5 psi to 10.5 psi.

That, of course, assumes that the volume of the bladder inside the football didn't change size. Going back to our initial temperature range, using trial and error in our tool once again, we found that it would have to expand to 297.85 cubic inches, or 115% of its initial volume, to account for the observed change in pressure.

That is something that might perhaps seem plausible, but a reality check indicates that would involve the footballs growing to be larger than the maximum dimensional specifications mandated by the NFL. It would have been incredibly easy for even the NFL's officials to determine that something was greatly amiss with the Patriots' footballs if that were the case.

Instead, the physics involved are such that it is clear that Tom Brady's balls achieved their deflated state through other means.

And if nothing else, we have perhaps demonstrated that one cannot trust either the scientific or mathematical claims made by a hack sportswriter from Boston.


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January 23, 2015

There are more Boeing 737s flying in the skies of Earth today than any other model of commercial air transport. Back in 2000, to keep up with demand, the company began producing 737s at the then record rate of 1 per day, or rather, 30 per month. Ten years later, the company was producing 737's at a rate of 31.5 per month.

At that point in 2010, the company's orders were finally strong enough to justify speeding things up. By 2014, the company was producing 737s at a rate of 42 per month and now has plans to increase its production rate further with the goal of delivering 47 per month in 2017 and possibly as many as 52 per month in 2018.

The YouTube video below reveals some insights into how Boeing's mechanics do it.

To get an idea of how much the video has been speeded up, the assembly line shown after the wings are attached to the fuselage, where 737s are "flying" down the factory floor in single file, moves forward at a continuous rate of two inches per minute.

Altogether, the production of a Boeing 737 represents anywhere from 367,000 to 600,000 individual parts (depending on the exact model) that are assembled to fly together in close formation.

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January 22, 2015
Brent Crude Oil Price Projections - 1987-2040 - Source: AEO2014 EARLY RELEASE OVERVIEW, http://www.eia.gov/forecasts/aeo/er/early_prices.cfm

How much of a change in global oil prices can be attributed to changes in the relative demand for oil? And how much might be attributed to changes in the relative supply of oil?

Those are questions that we've asked and answered before, but now, for the first time, we can finally quantify the extent to which either of these economic factors may be driving the price!

We can do that math now thanks to the work of James Hamilton, who built a model of how much world oil prices change in response to changes in the prices of other commodities - ones that are particularly sensitive to changes in the demand for them: copper, U.S. dollars, and 10-Year Constant Maturity U.S. Treasuries.

Our tool below is built to do that math, with the default values being the values recorded for the week of 4 July 2014 (for the "Previous Values" and for the week of 12 December 2014 (for the "Current Values"), which Hamilton recommends because they smooth out some of the big swings in values that are recorded in the day-to-day data. If you want to do the math for the current day, here is where you can obtain the data for the "Current Values" to replace the default values we've entered in the tool below:

Got all that? Here's the tool....

Value of Global Demand Sensitive Commodities
Input Data Previous Values Current Values
Copper [USD/lb]
Trade Weighted U.S. Dollar Index
Constant Maturity 10-Year U.S. Treasury Yield [%]
Brent Crude Oil - Europe [USD/barrel]

Projected Price of Crude Oil Based on Demand Factors
Estimated Results Values
Expected Price of Brent Crude Oil If Only Affected by Global Demand Factors
Differences from Previous Price of Brent Crude Oil
Estimated Change in Price of Brent Crude Oil Due to Demand Factors
Actual Change in Price of Brent Crude Oil
Percentage of Actual Change in Brent Crude Oil Price Attributable to Demand or Supply Factors
Percentage of Change Attributable to Demand Factors
Percentage of Change Attributable to Supply Factors
If you're reading this article on a site that republishes our RSS news feed, click here to access a working version of this tool!

Using the default data, which applied for the week of 12 December 2014, we find that 42.8%, or $20.29 of the $47.45 per barrel change in Brent crude oil prices following the week of 4 July 2014 can be attributed to a negative change in global demand (from slowing national economies, particularly in Europe and Asia), while 57.2% might be attributed to the relative changes in the supply of crude oil (thanks largely to increases in U.S. oil production.)

And so, just like the recent discovery involving the causality associated with the chicken and egg dilemma, we now know not only whether its changes in demand or supply factors that are mostly driving changes in the price of oil in the world, but can now also determine tow what extent each factor is responsible!


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January 20, 2015

With President Obama's 2015 State of the Union address now upon us, we thought we'd follow up on a 2011 post, which showed that the post-recession jobs recovery in the U.S. wasn't quite as good as claimed by the President's political supporters in the U.S. Congress.

Specifically, those supporters were claiming that the jobs recovery under President Obama were faster than those seen during the 1990 and 2001 recessions. Here's the chart we featured to show how things really stood at that time:

Percentage of Maximum Payroll Job Losses in Post WWII Recessions, Aligned at Maximum Job Losses, through December 2010

The jobs recovery from the 2007 recession was still a work in progress however, and in January 2011, even though it was the worst on record, it really wasn't too far out of sync with the typical payroll jobs recovery seen in every recession since the end of World War 2, where the typical recovery in jobs takes approximately the same number of months as it did for the maximum job loss to occur during each period of economic contraction.

Let's next reveal how the total nonfarm jobs recovery following the 2007 recession really played out.

Percentage of Maximum Payroll Job Losses in Post WWII Recessions, Aligned at Maximum Job Losses, through May 2014

Unlike every other recession since the end of World War 2, the jobs recovery from the 2007 recession was especially protracted, making it an atypical event, but also an asymmetric one.

That outcome is a direct result of the policies that were adopted during President Obama's tenure in office, particularly those that were implemented after 2010 through the President's phone and his pen, the net effect of which was to derail the jobs recovery from even coming anywhere close to following the typical pattern seen after every other recession in the modern era.

Which is why we call the recovery following the 2007 recession the worst recession jobs recovery ever.

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In the process of testing out and selecting a new color scheme for displaying complex data on a Microsoft Excel chart, we somehow managed to accurately forecast the overall trajectory of stock prices last week. Over a week in advance.

Here's how we did that. The complex data we were displaying was generated from our standard model of how stock prices work, which combines future-oriented data related to the amount of dividends expected in future quarters with historic stock prices, which our model uses as base reference points for projecting stock prices into the future.

Specifically, our standard model for forecasting stock prices incorporates the historic value of the S&P 500 from 13 months earlier, 12 months earlier and one month earlier in projecting a particular day's most likely stock prices. The chart below shows the trajectories for each that apply in 2015 (the heavy black line represents current day stock prices).

S&P 500 Index Value (Historic Data Base Reference Points) Used in Standard Model Forecast Projections, 2015

If you pay close attention to our chart, you'll find that the current day S&P 500 is almost perfectly following the trajectory that stock prices did exactly one month earlier, when investors were weighing the potential negative impact of falling oil prices on the growth prospects upon the U.S. stock market in the future. That dynamic is what our model has picked up upon.

The fact that it would appear to be repeating is a phenomenon that's largely driven by the U.S. bond market. Our thinking is that the investment decisions that were made in December 2014 are being repeated again in January 2014 with the maturation of one-month U.S. Treasuries. It's kind of like an aftershock after an earthquake, or in this case, a noise event in the U.S. stock market, where a past event is actually driving stock prices in the current day, to the extent that such an event can.

The degree to which events in the past might drive today's aftershocks or to more often dissipate as yesterday's echoes would really appear to depend greatly upon what investors expect for the future as the maturity and option expiration dates associated with their previous investment choices come to pass and provide the means for executing new decisions. If the future doesn't change in the interim, why should the investment decisions of investors change?

So it's actually luck that is behind that our model's ability to have accurately projected the trajectory that stock prices followed last week. It's just fun to see that it's possible to build a particular kind of luck into a mathematical model!

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