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October 18, 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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October 17, 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.

UNUSUALLY LARGE AMOUNTS OF CARBON DIOXIDE (REPORTED HERE IN GIGATONS) WERE RELEASED FROM THE TROPICS DURING THE 2015 EL NIÑO. | Source: NASA/ JPL/ CALTECH

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.

References

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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October 16, 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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October 13, 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.

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October 12, 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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