Political Calculations
Unexpectedly Intriguing!
31 October 2017

Are you ready to put all the other houses in your neighborhood to shame this Halloween? If so, you might want to employ some of the latest in digital imaging technology, where you can conjure spectres from the aether on command with the power of downloadable technology! Digital decorations developer AtmosFX explains how in the following video (HT: Core77):

If that's not enough to scare those pesky neighbors, here at Political Calculations, we have a strange tradition where we celebrate the scary in furniture on Halloween.

Except this year, we were stopped in our tracks by one of the more inexplicably disturbing videos that we've seen in quite a while, that redefines what scary in furniture can mean. We don't want to minimize it through understatement, but we would describe it as haunt your dreams stuff, and while it is safe for work, barely, we cannot explain it, nor will we. We will however warn you that you cannot unsee it after you've seen it.

You cannot say that you were not warned. Have a happy Halloween, and good luck forgetting whatever the hell that was.

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30 October 2017

The fourth week of October 2017 retold much of the same story for the S&P 500 that every other week of the month has seen, with the index closing the week near or, as was the case this week, at a new record high value.

From our perspective, that mainly means that stock prices continued to track along the upper end of the range we first forecast back in early September, when we assumed that investors would be most likely to focus upon the distant future quarter of 2018-Q2 in setting current day stock prices.

Alternative Futures - S&P 500 - 2017Q3 - Standard Model with Connected Dots Between 20170908 and 20171108 - Snapshot on 27 October 2017

Since that time, investors have maintained that focus rather steadily, which is somewhat remarkable, since the fourth quarter is often when companies will significantly update their business outlooks as they report their most recent earnings in the first half of the quarter, where their shareholders can make changes in their investing strategies before the end of the calendar year. For our dividend futures-based model of how stock prices work, that dynamic can cause both fundamental expectations about the future to change as well as change how far forward in time investors are focusing their attention.

The lack of surprising new information being announced since the beginning of the month has allowed stock prices to follow a fairly stable trajectory, which we generated to account for the past volatility of the historic stock prices that we use in our model as the base reference points for projecting future stock prices. Our need to make that adjustment to improve the accuracy of our model's projections will end in a week and a half.

As we noted earlier, the S&P 500 is continuing tracking along near the upper end of that forecast range, which tells us that while investors are mostly focused on the expecations associated with 2018-Q2 in setting today's stock prices, they are devoting a small portion of their attention to another quarter. In this case, we believe that lesser focus is being placed upon the current calendar quarter of 2017-Q4, which we're still less than a third of the way through.

That's not an accident. Both 2017-Q4 and 2018-Q2 currently share one common feature that would prompt investors to focus upon each quarter above and beyond simply focusing on new information being announced about the future outlook for individual U.S. companies: these quarters are both expected to feature the U.S. Federal Reserve announcing changes in short term interest rates, where the Fed is currently expected to increase its Federal Funds Rate by quarter percent before the end of each quarter, where the Federal Funds Rate would rise from its current range of 100-125 basis points to 125-150 bps at the end of 2017-Q4, then rising to 150-175 basis points by the end of 2018-Q2.

You wouldn't necessarily have picked up on that latter influence upon investors from the more notable headlines in the past week.

Monday, 23 October 2017
Tuesday, 24 October 2017
Wednesday, 25 October 2017
Thursday, 26 October 2017
Friday, 27 October 2017

Over at The Big Picture, Barry Ritholtz lists the week's major positives and negatives for the U.S. economy and markets.

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27 October 2017
Elizabeth Miller Cupcakes - Source: http://www.lanl.gov/science-innovation/features/faces-of-science/elizabeth-miller.php

Back in 1950, future economics Nobel prize winning mathematician John Nash developed a mathematical formula for making optimal joint decisions, such as might need to be made to peaceably divide up a limited resource between two people.

Flash forward 67 years, and Wellesley College mathematics professor Oscar E. Fernandez has featured that math in a new book, The Calculus of Happiness, in which he explores ways in which math can be used to achieve greater happiness by solving everyday problems.

Nash's optimal joint decision math is just one of the formulas presented in the book, which can be applied to problems like how to divide up cupcakes, a sum of cash or even child-free time off between spouses, where the goal is to achieve the maximum amount of happiness when compromises need to be made.

We've built a tool to do that math, where you just need to enter the number of units of the resource or thing that you would be dividing between yourself and someone else, along with selecting both your and their levels of happiness (on a scale from 1 to 10) if either of you could have all of the resource, and also what that happiness level would be if you couldn't come to some sort of arrangement. If you're reading this article on a site that republishes our RSS news feed, please click here to access a working version of this tool at our site!

Resource and Happiness Data
Input Data Values
Total Units of the Resource to be Divided
How Happy Would You Be If You Could Have the Resource All To Yourself? [On a Scale from 1-10]
How Happy Would You Be If You Cannot Reach an Agreement on How to Divide the Resource? [On a Scale from 1-10, Without Exceeding Your Level of Happiness If You Had All of the Resource]
How Happy Would The Other Person Be If They Could Have the Resource All To Themselves? [On a Scale from 1-10]
How Happy Would the Other Person Be If You Cannot Reach an Agreement on How to Divide the Resource? [On a Scale from 1-10, Without Exceeding Their Level of Happiness If They Had All of the Resource]

The Optimal Division
Calculated Results Values
Your Portion of the Total
The Other Person's Portion of the Total

The default data in the tool is taken from the example that was presented at Business Insider for how two spouses could optimally divide having child-free time during the same 5 days of vacation off, where each spouse could be free of conflict to do whatever other activity they might like without distraction.

For that example, BI offers the following insights:

Plug those numbers into the formula and you see that you should get three days off and your partner should get two.

Fernandez highlights a cool implication of this formula: A simple way to get a bigger piece of the pie is to start feeling happier about the possibility that you two won't reach any agreement. In other words: The more willing you are to walk away, the more negotiating power you have.

As Fernandez points out in other parts of the book, this formula assumes that you're able to quantify your feelings — and that your feelings won't change over the course of the negotiation. So it won't work perfectly every time.

Fernandez has his own online spreadsheet version of this tool, along with 15 others from his books (as of this writing) at his Surrounded By Math web site. Do check them out!

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26 October 2017

There have been three main trends in median new home sale prices since July 2012. The following chart updates where we are through September 2017.

Trends in the Trailing Twelve Month Moving Average of New Home Sale Prices, July 2012 through September 2017

For the most recent trend, which began two years ago in September 2015, the trailing twelve month average of median new home sale prices in the U.S. has been escalating at an average rate of $906 per month.

In terms of affordability, the ratio of the trailing twelve month averages of median new home sale prices to median household income in the U.S. is near its all time high of 5.454, which following revisions in the data for new home sale prices, was recorded in July 2017. The initial value for September 2017 is 5.437.

Ratio of Trailing Twelve Month Averages of U.S. Median New Home Sale Prices to Median Household Income - Annual: 1967-2016 - Monthly: December 2000 to September 2017

Our final chart updates the relationship between U.S. median new home sale prices and median household income, with the annual data now spanning 2000 through 2016 and the monthly data covering the period from December 2000 through September 2017.

Trailing Twelve Month Averages of U.S. Median New Home Sale Prices versus Median Household Income - Annual: 2000-2016 - Monthly: December 2000 to September 2017

The annual data is based solely on the U.S. Census Bureau's annual new home sale price and household income data, while the monthly data is based on the U.S. Census Bureau's monthly new home sale price data and our preliminary estimates of monthly household income in the United States.

Data Sources

U.S. Census Bureau. Median and Average Sales Prices of New Homes Sold in the United States. [PDF Document]. Accessed 26 October.

U.S. Bureau of Economic Analysis. Table 2.6. Personal Income and Its Disposition, Monthly, Personal Income and Outlays, Not Seasonally Adjusted, Monthly, Middle of Month. Population. [Online Database (via Federal Reserve Economic Data)]. Last Updated: 1 October 2017. Accessed: 5 October 2017.

U.S. Bureau of Economic Analysis. Table 2.6. Personal Income and Its Disposition, Monthly, Personal Income and Outlays, Not Seasonally Adjusted, Monthly, Middle of Month. Compensation of Employees, Received: Wage and Salary Disbursements. [Online Database (via Federal Reserve Economic Data)]. Last Updated: 1 October 2017. Accessed: 1 October 2017.

Sentier Research. Household Income Trends: January 2000 through May 2017. [Excel Spreadsheet with Nominal Median Household Incomes for January 2000 through January 2013 courtesy of Doug Short]. [PDF Document]. Accessed 22 June 2017. [Note: We've converted all data to be in terms of current (nominal) U.S. dollars.]


25 October 2017

Political Calculations appears to be under a low grade, but escalating Distributed Denial of Service (DDOS) attack. The following chart illustrates what we're seeing in our site traffic for in the period from 19 October 2017 through 24 October 2017.

Political Calculations Site Traffic, Daily Summary, 19 October 2017 through 24 October 2017

The attack appears to originate from a number of ISP servers associated with Online Sas based at Southend in the United Kingdom. The attack began on 19 October 2017. The following screen shot shows the first incursion by the botnet that we detected:

Political Calculations Site Traffic Excerpt, 19 October 2017 23:22:17 AM PDT

Since then, the number of site visits from Online SAS servers has escalated. The next screen shot of our site traffic shows a the most recent three minute period (at the time we snapped the picture) on 25 October 2017.

Political Calculations Site Traffic Excerpt, 25 October 2017 04:40:28 AM PDT to 04

Other than the frequency, the main thing to take away from this screen shot is the number of different servers that are involved. Beyond that, Online SAS/Poneytelecom.eu's servers have been associated with a number of server-based attacks in the last year.

As attacks go, the botnet behind the DDoS at work here is pretty low grade. We don't think it will succeed in disabling our site, but the escalating frequency of the attacks is a concern. We can confirm however that being probed by a mysterious botnet is much less creepy than some of the stalking-like behavior we've observed in our site traffic statistics in the past.

Update 26 October 2017: Shining a light on the activity appears to have produced a positive result - the automated attack has ended. While we described it above as a "low grade" attack, we think it was perhaps more of a sniffing or probing event. We'll be curious to find if other sites encounter a similar experience.


24 October 2017

The U.S. government's 2017 fiscal year officially ended on 30 September 2017. From the end of its 2016 fiscal year (FY2016) a year earlier, the total public debt outstanding of the U.S. government increased by $671.5 billion, rising from $19,573 billion (or $19.6 trillion) to $20,245 billion (or $20.2 trillion) during FY2017.

The following chart shows the major breakdown of who the U.S. government has borrowed that total $20.2 trillion from:

FY 2017 (Preliminary): To Whom Does the U.S. Government Owe Money?

According to the U.S. Treasury Department, the U.S. government spent some $665.7 billion more than it collected in taxes during its 2017 fiscal year. The difference between this figure and the $671.5 billion that the total national debt actually rose can be attributed to the government's net borrowing to fund things like Federal Direct Student Loans, which collectively account for nearly $1.1 trillion of the government's $20.2 trillion debt, or 5.4% of the total public debt outstanding.

Put differently, the U.S. national debt would be 5.4% less at roughly $19.1 trillion if not for the federal government's takeover of the student loan industry from the private sector in March 2010. Since that time, approximately $1 of every $10 that the U.S. government has borrowed has been for the purpose of funding its student loan program.

Overall, 69% of the U.S. government's total public debt outstanding is held by U.S. individuals and institutions, while 31% is held by foreign entities. China has resumed its position as the top foreign holder of U.S. government-issued debt, with directly accounting for 6.9% between institutions on the Chinese mainland and Hong Kong.

Beyond that, China likely has additional holdings that are currently being shown as being held in the international banking centers of Belgium and Ireland, which together account for 2.0% of the U.S. national debt, where China's holdings are believed to represent a significant portion of the amounts currently being credited to both these nations.

The largest single institution holding U.S. government-issued debt is Social Security's Old Age and Survivors Insurance Trust Fund, which is considered to be an "Intragovernmental" holder of the U.S. national debt, and which holds 13.9% of the nation's total public debt outstanding. The share of the national debt held by Social Security's main trust fund is expected to fall as that government agency cashes out its holdings to pay promised levels of Social Security benefits, where its account is expected to be fully depleted in just 17 years. Under current law, after Social Security's trust fund runs out of money in 2034, all Social Security benefits would be reduced by 23% according to the agency's projections.

The largest "private" institution that has loaned money to the U.S. government is the U.S. Federal Reserve, which accounts for nearly one out of every eight dollars borrowed by the U.S. government. It lent nearly all of that total since 2008, mainly through the various quantitative easing programs it operated from 2009 through 2015 in its attempt to stimulate the U.S. economy enough to keep it from falling back into recession. In September 2017, the Fed announced that it would begin reducing its holdings of U.S. government-issued debt.

Data Sources

U.S. Treasury. The Debt To the Penny and Who Holds It. [Online Application]. 30 September 2017.

Federal Reserve Statistical Release. H.4.1. Factors Affecting Reserve Balances. Release Date: 28 September 2017. [Online Document].

U.S. Treasury. Major Foreign Holders of Treasury Securities. Accessed 21 October 2017.

U.S. Treasury. Monthly Treasury Statement of Receipts and Outlays of the United States Government for Fiscal Year 2017 Through September 30, 2017. [PDF Document].


23 October 2017

The third week of October 2017 saw the S&P 500 close at a new all time high on each day of the week, which is the first time that's happened since 1998.

In the meantime, the trajectory of the S&P 500 continues to track along the top edge of the range we first forecast back in early September 2017.

Alternative Futures - S&P 500 - 2017Q3 - Standard Model - Connected Dots for 2018Q2 Trajectory Between 20170908 and 20171108 - Snapshot on 20 October 2017

The S&P 500 index continues to track along near the top end of that range, shown as the red-shaded box, in which we assumed that investors would largely remain focused on the distant future quarter of 2018-Q2 as we accounted for the past volatility of stock prices on our dividend futures-based model. That adjustment has another two and a half weeks to run before we expect to be able to return to using the raw projections of our standard model.

From our perspective, one of the bigger stories of the past week was General Electric's (NYSE: GE) earnings announcement, which had been expected to come with a dividend cut announcement that would have noticeably affected the expectations for future S&P 500 dividends.

As GE announced its earnings before the start of trading on Friday, 20 October 2017, indicating that its future earnings would be on the order of 30% below their previous forecasts as its cash flow was also strained, GE's stock price at first plunged by 7% of its previous day's closing value in the day's pre-market trading.

What didn't happen however was GE's anticipated dividend cut announcement. Going by our theory of how stock prices work, where the fundamental driver of stock prices is expectations for their underlying dividends per share, that would mean that the initial reaction of investors to the company's earnings and cash flow announcement would likely turn out to be a short-lived noise event. And so it was, as GE's stock price reversed its plunge and went on to close up on the day by 1%, which ZeroHedge described as "GE-Dip-Buying-Panic".

As Bloomberg summarizes, the dollar rose, Treasuries sank and all three broad stock indexes are heading for a record close on bets a budget compromise will bring Washington closer to agreeing on Trump’s promise of tax reform. The dollar touched a three-month high and 10-year Treasury yields approached 2.4% while the Canadian dollar tumbled after inflation and retail sales missed estimates. Some clarity on a budget resolution, a good quarter of earnings and the anticipation of an announcement of the next Fed chair has led to market confidence. One stock clearly bucked the earnings trend; GE posted results before the bell, missing analysts’ estimates significantly and slashing its profit forecast. The stock erased losses after falling 7% in premarket trading.

So - GE did this...

ZeroHedge: GE on 20 October 2017

GE investors however are not yet out of the woods with respect to a potential dividend cut. The company may still announce that it will cut its dividend at its upcoming shareholder meeting on 13 November 2017. How that may affect the company's investors will now largely depend on how much of that anticipation is already reflected in the company's stock price, which has fallen by a quarter since the beginning of the year.

Meanwhile, there was a lot of other stuff that happened that was worth noting during Week 3 of October 2017....

Monday, 16 October 2017
Tuesday, 17 October 2017
Wednesday, 18 October 2017
Thursday, 19 October 2017
Friday, 20 October 2017

Barry Ritholtz notes a number of usually strong statistics among the positives and negatives for the U.S. economy and markets in Week 3 of October 2017.

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20 October 2017

Every October, many stock market investors celebrate their own pre-Halloween scare tradition, thanks to a calendar-based phenomenon called the "October Effect", which is "the theory that stocks tend to decline during the month of October."

As Investopedia goes on to describe it, "the October effect is considered mainly to be a psychological expectation rather than an actual phenomenon. Most statistics go against the theory." And indeed, that's true. Examining the month's track record over the years, one finds that truly scary market events like the Black Monday Crash of 1987, which celebrated its 30th anniversary this week, are often balanced against the month's coincidental timing in marking the beginning of long term rallies.

Still, we can still offer some insight into why both those phenomenons exist in the month of October. It is because the second week of the month marks the beginning of the year's fourth quarter's earnings season, which is the time that publicly-traded U.S. firms will announce if they are doing better or worse than expected for the year, where company leaders will also communicate changes in their expectations of how their businesses will perform in the next year.

ZeroHedge is reporting an example of the negative side of this dynamic play out on this Friday, 20 October 2017, with General Electric (NYSE: GE), which for GE investors, looks like a Black Friday-type event.

While it may not have slashed its dividend, yet, General Electric shares plunged 5% in the pre-market after the company cut its 2017 profit forecast while its new CEO grapples with one of the deepest slumps in the iconic US manufacturer's history. The company reported that adjusted earnings this year are expected to be only $1.05 to $1.10 per share, down over 30% from a previous range of $1.60 to $1.70 a share. This is also sharply lower than the sellside consensus of $1.54 a share.

ZeroHedge: GE Slides, 20 October 2017

For the current quarter, the industrial conglomerate and maker of jet engines and gas turbines reported adjusted Q3 EPS of 29 cents, nearly 50% below the 50 cent consensus estimate.

As Bloomberg reports, the revision underscores the severity of the challenges facing Chief Executive Officer John Flannery, who took over Jeffrey Immelt's longtime post in August. With hurdles from poor cash flows to slumping power-generation markets, GE is by far the biggest loser on the Dow Jones Industrial Average this year and has seen a quarter of its market value evaporate.

The cut is the latest step in what is shaping up to be a dramatic repositioning of GE under its new leadership. Flannery this month welcomed a representative of activist investor Trian Fund Management to GE's board and announced several management changes. He is seeking deep cost cuts and has said he will consider all options, including portfolio changes.

In addition to GE no longer using a "shadow" private jet for its CEO, not to mention slashing its fleets of private cars and other corporate perks as the WSJ infamously reported yesterday, expect thousands more in layoffs from what was once America's most iconic company, which in turn will follow to more complaints by the Fed about America's growing "qualified labor shortage." And now we wait news on the fate of the company's dividend which wall street expects to be "massively" cut.

Now, balance that bad news against the week's example from the positive side of the future expectations adjustment ledger, where Netflix (NASDAQ: NFLX) reported much higher than expected earnings and more importantly, a higher level of subscriptions, which portends a brighter earnings future for the streaming media delivery company going into 2018.

It's that kind of stuff that makes October an exciting month for investors. Whether its a scary month or the beginning of a new market rally all hinges on how expectations for 2018 will be collectively set by all the publicly-traded companies who will announce any changes in their outlooks during this earnings season.

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19 October 2017

2017 hasn't been a good year for General Electric (NYSE: GE), and now, the company's new CEO, John Flannery, who took over from Jeffrey Immelt in August 2017, is shaking up the company as its financial problems are reaching a crisis point, all while its stock price continues its 2017 trend of descent.

GE Stock Price History - 2017 - Snapshot on 2017-10-17 - Source: Google Finance

That much is evident from the just announced departure of the company's new Chief Financial Officer, Jeff Bornstein, who had just moved into the CFO position at the same time Flannery was elevated to be GE's Chief Executive Officer. The unexpected change points to ongoing issues with the company's financial situation, which appears to be deteriorating.

GE's management has been over-promising and under-delivering, and you only have to look at the nearly 27% decline in the company's stock price this year to see the impact. GE hasn't formally abandoned its EPS targets for this year and the next, but the commentary around those targets has grown increasingly negative. Moreover, there are signs of deteriorating quality of earnings. Consider:

  • GE significantly missed its own expectations for cash flow generation by $1 billion in the first quarter.
  • On the second-quarter earnings call, Bornstein guided investors toward the bottom end of the full-year earnings and cash flow guidance ranges.
  • Immelt's long-held target of $2 in operating EPS in 2018 is significantly above the analyst consensus of $1.63.

In a nutshell, market analysts believe that GE isn't going to make its earnings numbers, and what's more, they also believe that GE's cash flow is in trouble.

... when GE reported a cash flow shortfall of $1 billion in the first quarter--with $300 million of it from contract assets--it highlighted the fact that GE has been booking revenue and earnings which haven't been dropping through into cash flow as yet.

The combination of lackluster earnings and strained cash flow means that the company will likely be forced to cut its dividend. As a general rule, companies need at least one of these two things working in their favor in order to sustain their dividends without negatively impacting their other operations and costs, but since GE has neither of these going for it at this time, there is a very real possibility that the company will be compelled to slash its dividend in the very near future as part of an overall restructuring initiative. As in today or tomorrow, with a potential 25% cut from the current quarterly dividend payout of $0.24 per share down to $0.18 per share....

Since GE is one of the largest company's in the U.S., at least as measured by its market capitalization, what happens to GE will have a noticeable effect on major stock market indices like the S&P 500 (Index: INX). Because we use the future expectations associated with the index' dividends per share to project its future trajectory, we wondered how much GE cutting its dividend might affect those future expectations.

So we built the following tool to do the math. If you're accessing this article on a site that republishes our RSS news feed, please click through to our site to access a working version of the tool. The default stock price, market cap, and dividend data in the tool applies for General Electric and the S&P 500 as of the close of trading on 17 October 2017.

Individual Company Stock Data
Input Data Values
Stock Price per Share
Dividends per Share Paid During Last 12 Months
Number of Shares Outstanding
New Dividends per Share Paid During Next 12 Months
Reference Market Cap-Weighted Index Data
Reference Market Capitalization of Index
Reference Index Value
Current Stock Market Index Data
Current Index Value
Index Dividends per Share Paid During Last 12 Months

Market Capitalization and Dividend Change
Calculated Results Values
Index Dividends per Share To be Paid Over Next 12 Months
Change in Index Dividends per Share

For the default data that applies for GE in October 2017, we find that should the company cut its dividend by 25% from its current dividend level, the impact to shareholders of S&P 500 index funds would a reduction of $0.23 per share in their annual dividend payouts, or a little under 0.5%.

Because we built this tool to be able to consider the impact of a change in dividends paid out by any dividend-paying component of a market cap-weighted stock market index, you're more than welcome to use it to consider the dividend change situation at other companies - just make the appropriate substitutions in the tool, and we'll take care of the math.

The tool however does not consider what the other dividend-paying components of the index are doing with their dividends, so it should be used only to consider what effect that a change in a single company's dividend policy might have on the dividends that would be paid to investors in a market cap-weighted index fund.

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18 October 2017

We're busy behind the scenes today here at Political Calculations, but to mark the occasion of new highs for the U.S. stock market, we thought we might revisit the past for the S&P 500 and its index predecessors.

First, a quick look at the average value of the S&P 500 in each month since January 1871.

S&P 500 Average Monthly Index Value, January 1871 to October 2017 (Through 17 October 2017)

Now that you've seen the chart, you might want to extract some of the data for certain periods from it. That's where our The S&P 500 At Your Fingertips tool comes into play, because not only can we tell you what the value of the S&P 500 or its predecessor indices was in any of those months, we can also tell you the index' earnings per share and dividends per share, as well as the rates of return that were realized between any two of months that you might select, both with and without considering the effects of inflation and dividend reinvestment! We update this tool monthly.

But wait, that's not all! Our Investing Through Time tool uses that data to estimate how much the inflation-adjusted value of an investment made between any two months from January 1871 through the present might be worth. If you're the kind who wants to consider worst case scenarios, just set "June 1932" as the end date for your hypothetical investment.... We also update this tool monthly.

We also present a tool for the Quarterly Data for the S&P 500, Since 1871, since that provides the raw data we use for the earnings and dividend data in the other two tools. We update this tool annually, where it presently provides data through the fourth quarter of 2016.

Finally, we'll revisit the data for the average monthly value of the S&P 500 in chart form, but this time, using a logarithmic scale.

S&P 500 Average Monthly Index Value, January 1871 to October 2017 (Through 17 October 2017)

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17 October 2017

Last week, NASA scientists published their blockbuster findings of what they learned from the observations they obtained over the first two years of operation of the Orbital Carbon Observatory-2 (OCO-2) satellite.

Launched on 2 July 2014, OCO-2 has the ability to measure the concentration of carbon dioxide in the Earth's atmosphere at spatial resolution down to 1.3 kilometer by 2.25 kilometer rectangles, a significant improvement over the 50 by 50 kilometer squares that marked the limit that previous satellites were able to produce. With that level of detail, the satellite's instruments are better able to detect the emission of carbon dioxide from both natural sources and from human activities much closer to their points of origin, before they become more generally dispersed into the Earth's atmosphere.

The timing of the launch of the OCO-2 satellite was particularly fortuitous, because it came in time to capture the effect of the very strong El Niño anomaly of 2015-2016 upon the level of carbon dioxide that was added to the Earth's atmosphere during those years.

But more to the point, the satellite data was able to determine the amount and source of that additional carbon dioxide produced from natural sources. The following chart shows that almost all of that contribution came from the tropics, where a combination of higher temperatures and drought conditions led to less carbon dioxide being captured by plants in the Earth's equatorial belt.


NASA totaled up the numbers related to the 2015-2016 El Niño event:

A new NASA study provides space-based evidence that Earth’s tropical regions were the cause of the largest annual increases in atmospheric carbon dioxide concentration seen in at least 2,000 years.

Scientists suspected the 2015-16 El Nino -- one of the largest on record -- was responsible, but exactly how has been a subject of ongoing research. Analyzing the first 28 months of data from NASA’s Orbiting Carbon Observatory-2 (OCO-2) satellite, researchers conclude impacts of El Nino-related heat and drought occurring in tropical regions of South America, Africa and Indonesia were responsible for the record spike in global carbon dioxide. The findings are published in the journal Science Friday as part of a collection of five research papers based on OCO-2 data.

“These three tropical regions released 2.5 gigatons more carbon into the atmosphere than they did in 2011,” said Junjie Liu of NASA’s Jet Propulsion Laboratory (JPL) in Pasadena, California, who is lead author of the study. “Our analysis shows this extra carbon dioxide explains the difference in atmospheric carbon dioxide growth rates between 2011 and the peak years of 2015-16. OCO-2 data allowed us to quantify how the net exchange of carbon between land and atmosphere in individual regions is affected during El Nino years.” A gigaton is a billion tons.

In 2015 and 2016, OCO-2 recorded atmospheric carbon dioxide increases that were 50 percent larger than the average increase seen in recent years preceding these observations. These measurements are consistent with those made by the National Oceanic and Atmospheric Administration (NOAA). That increase was about 3 parts per million of carbon dioxide per year -- or 6.3 gigatons of carbon. In recent years, the average annual increase has been closer to 2 parts per million of carbon dioxide per year -- or 4 gigatons of carbon. These record increases occurred even though emissions from human activities in 2015-16 are estimated to have remained roughly the same as they were prior to the El Nino, which is a cyclical warming pattern of ocean circulation in the central and eastern tropical Pacific Ocean that can affect weather worldwide.

Doing the math, that additional 2.5 billion metric tons of carbon translates into an additional 1.17 parts per million of carbon dioxide being emitted into the Earth's atmosphere from natural sources during the period of the 2015-16 El Niño anomaly.

Having now isolated that natural contribution to the increase in the concentration of atmospheric carbon dioxide over that period of time, we can now subtract it out from the total to quantify the portion that might be attributable to human activities combined with what would be considered to be typical levels of CO2 generated from natural sources, which would be more directly comparable to the kind of readings that would be obtained in years where El Niño events are not a significant factor affecting atmospheric carbon dioxide concentration measurements.

Year-Over-Year Change in Parts per Million of Atmospheric Carbon Dioxide, January 1960-September 2017

That in turn can tell us something about the relative health of the Earth's global economy, since human activities are primarily responsible for the increase in the year over year change in the concentration of atmospheric carbon dioxide over time. In this case, after subtracting out the contribution of the 2015-2016 El Niño anomaly on those measurements, we find that the peak value that would have been reached during this time would have fallen below the peak reached in 2013 and would be about the same as the peak reached in 2014.

For the Earth's global economy, that suggests that economic growth was largely flat from 2015 through 2016, where we would expect a faster rate of increase in the year over year change in CO2 levels if the Earth's economy was growing on net during that time.

Ideally, we'd like to get a month-to-month breakdown of how much additional CO2 was produced from natural sources during the 2015-2016 El Niño event, which would let us drill down into greater detail for the global economic performance that was realized during those years. And with data from the OCO-2 satellite, that might just be possible, which would allow us to directly take natural anomalies like a very strong El Niño episode into account in near-real time, as we would be better able to isolate and separate those factors from the CO2 produced via human activities.

That in turn would transform our vision for using the changing level of carbon dioxide in the Earth's atmosphere from human activities as a near-real time indication of the performance of the world's entire economy into a hum-drum practical achievement.

At least as the changing level of carbon dioxide in the Earth's air continues to be largely in proportion to the scope of human activities.


Florian M. Schwandner, Michael R. Gunson, Charles E. Miller, Simon A. Carn, Annmarie Eldering, Thomas Krings, Kristal R. Verhulst, David S. Schimel, Hai M. Nguyen1, David Crisp, Christopher W. O’Dell, Gregory B. Osterman, Laura T. Iraci, James R. Podolske. Spaceborne detection of localized carbon dioxide sources. Science. Vol. 358, Issue 6360, eaam5782. DOI: 10.1126/science.aam5782. 13 October 2017. Accessed 13 October 2017.

National Oceanographic and Atmospheric Administration. Earth System Research Laboratory. Mauna Loa Observatory CO2 Data. [File Transfer Protocol Text File]. Updated 5 Octobedr 2017. Accessed 8 October 2017.

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16 October 2017

Following the records set in the first week of October 2017, the S&P 500 (Index: INX) continued to mark new highs during the second week of the month.

More specifically, the 2555.24 that marked the level of the S&P 500 at the close of trading on Wednesday, 11 October 2017 upped the ante for the index's series of new high closing values, although it wasn't much of a gain over the previous week's closing value of 2549.33 on Friday, 6 October 2017. Nor was it far below the S&P 500's all-time intraday high of 2557.56 that the index reached at 10:46 AM EDT a week later on Friday, 13 October 2017, before slipping back to end the week at 2553.17.

Alternative Futures - S&P 500 - 2017Q4 - Standard Model with Connected Dots Between 20170908 and 20171108 - Snapshot on 20171013

The S&P 500 continues to track along near the upper end of the echo effect-adjusted range that we first forecast back in the first week of September 2017. At that time, we observed that investors were largely focusing on 2018-Q2 as they considered the future for the S&P 500, where we constructed our forecast based on the assumption that they would largely continue focusing on that distant future quarter over the next two months.

As things stand today, we're now past the halfway point, with just three and a half weeks to go before we reach the end of our need to account for the echo of past volatility in stock prices in our dividend futures-based model of how stock prices work.

Through Week 2 of October 2017, there was nothing to really prompt investors to shift their focus toward a different point of time in the future, which can be seen in the headlines that we flagged during the week.

Monday, 9 October 2017
Tuesday, 10 October 2017
Wednesday, 11 October 2017
Thursday, 12 October 2017
Friday, 13 October 2017

Elsewhere, Barry Ritholtz broke the second week of October 2017 down into its economic and market pluses and minuses.

And that's the week that was! As for the week ahead, unless investors shift more of their focus toward other points of time in the future than they are already, look for the S&P 500 to continue falling within the range shaded in red in this week's spaghetti chart update.

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13 October 2017

It's a short one-minute long video from Ford, but it explains so much!

More seriously, what Ford's engineers are working on is a very real problem, and is one reason why industrial robot manufacturers add "eyes" to their products that aren't needed for their primary functions; it is so they can "communicate" where they're going to go with the human employees around them, which in turn, helps both machine and human coordinate their activities and helps avoid industrial accidents.


12 October 2017

Tracking the growth rates of trade over time can be a valuable exercise because of what that figure can tell us about the relative health of the national economies engaged in that trade.

For example, when a nation's economy is growing more strongly than what its domestic economy can support on its own, it will import an increasing amount of goods to meet its needs. And vice versa - if a nation's economy slows down to where it's domestic economy can more fully meet its needs, the amount of goods and services that it imports will decrease.

But don't take our word for it. Just read the following excerpts!...

If anyone still needs proof that trade isn't a zero-sum game in which success depends on turning imports into exports, an examination of data for over 160 countries provides it. For almost four-fifths of countries last year, the volume of exports and imports marched together, up or down, in lockstep. Growing an economy is not a matter of turning imports into exports. Robust economies do more of both....

Taking data aggregated in the CIA’s World Factbook, for countries with a population of a half-million or more, one finds that between 2015 and 2016, 129 countries experienced increases or decreases in both exports and imports. Only 33 countries experienced an increase in one category and a decrease in the other. and only three of those rank among the world’s 25 leading exporting nations. Reduced imports do not correlate with increased exports.

The ratio is even higher for OECD countries, the so-called rich man’s club made up of developed and rapidly developing countries. Between 2015 and 2016, the volume of exports and imports moved up or down together in 29 of the 35 member countries. This was also true of all G7 countries....

Imports are not a necessary evil; they are a necessary ingredient. Companies requiring inputs toward a finished product need to get the best price, quality, and service levels they can to compete. They need the widest potential network of potential suppliers. Being able to import – and therefore obtain the best possible terms and conditions from domestic and foreign suppliers – is crucial to being able to efficiently make products for export.

In fact, the opportunity to import helps achieve productivity and prosperity more than the opportunity to export, because it does more to broaden choice. Importing widens the circle of potential suppliers competing to meet the needs of consumers and intermediate producers. It forces domestic companies to become more efficient and compete more effectively. It generates economies of scale, spreading production costs over a wider and larger market. It allows countries to utilize comparative advantage, importing goods and inputs from countries that are most efficient at making them. And it transfers knowledge, allowing importers to benefit from technological spillover.

Notice that the data to support this analysis was taken from the U.S. Central Intelligence Agency's World Factbook? There's a reason why the CIA is interested in that kind of data - it provides a window into the relative health of foreign economies, including into the world's most repressive nations, where economic information is often either tightly controlled (such as North Korea) or where the limited information that is available is of comparatively low quality (such as China).

For example, for August 2017, in calculating the exchange rate-adjusted year over year growth rate of the value of goods and services imported by the U.S. from China and imported by China from the U.S., we find that the world's two largest economies are continuing to experience robust growth.

Year Over Year Growth Rate of Exchange Rate Adjusted U.S.-China Trade in Goods and Services, January 1986 - August 2017

As you can see in the chart, that hasn't always been the case, where both China and the U.S. experienced recessionary conditions as recently as 2016. In China's case, that situation was something that the nation's official economic statistics obscured.

To be fair, China's national statisticians are working to improve the quality of their data as the nation has progressed toward greater openness. It's a considerable challenge.

In the meantime, we can use the export ledgers of China's trading partners to gain insight into the relative health of its economy. It's one of the advantages to the kind of double-entry bookkeeping that nations do to measure their trade balances.

Data Sources

Board of Governors of the Federal Reserve System. China / U.S. Foreign Exchange Rate. G.5 Foreign Exchange Rates. Accessed 12 October 2017.

U.S. Census Bureau. Trade in Goods with China. Accessed 12 October 2017.


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