Political Calculations
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July 29, 2016
Wordle - Pseudoscience

Are there personality traits that characterize the people who intentionally engage in junk science?

You might not know names like Diederik Stapel, Jan Hendrik Schön, or Haruko Obokata, but to the scientists who work in their respective science fields of social psychology, condensed matter physics and developmental biology, they first rose to prominence and then sunk into infamy thanks to their choices to engage in junk science.

Why did they do it?

All three were recently profiled by Ian Freckleton, who dove into the psychological elements that all three appear to have shared as they engaged in extraordinarily damaging behavior (emphasis ours).

Often individuals who engage in scientific fraud are high achievers. They are prominent in their disciplines but seek to be even more recognised for the pre-eminence of their scholarly contributions. Along with their drive for recognition can come charisma and grandiosity, as well as a craving for the limelight. Their productivity can border on the manic. Their narcissism will often result in a refusal to accept the manifest dishonesty and culpability of their conduct. The rationalising and self-justifying books of Stapel and Obokata are examples of this phenomenon.

When criticism is made or doubts are expressed about their work, these scientists often react aggressively. They may threaten whistleblowers or attempt to displace responsibility for their conduct onto others. Such cases can generate persistent challenges in the courts, as the scientists in question deny any form of impropriety....

Research misconduct often has multiple elements: data fraud, plagiarism and the exploitation of the work of others. People rarely engage in such conduct as a one-off and frequently engage in multiple forms of such dishonesty, until finally they are exposed.

Having had some experience in revealing examples of pseudoscience, we can attest that the personality markers noted by Freckleton appear to us to be pretty spot on.

The consequences of pseudoscientific misconduct however go far beyond the perpetrators' behavior.

This intellectual dishonesty damages colleagues, institutions, patients who receive suspect treatments, trajectories of research and confidence in scholarship.

That's certaintly true in the cases of Stapel, Schön and Obokata, whose scientific legacies have proven to be so damaging that they singlehandedly set back real progress in each of their disciplines. As a result, other scientists wasted far too much of their time in trying to build on their false foundations, which meant that years of good faith effort had to be scrapped. The same scientists had to then add the hard work of reestablishing credibility for their disciplines to the challenge of having to restart their regular work from scratch because of the scholarly misconduct of their corrupt peers.

And all for nothing on the part of the perpetrators, because in the end, all their pseudoscience was exposed as the fraud it was when real science prevailed and they lost their jobs, their titles and their reputations. The sad part is that at least two of the three seem happy with achieving infamy, if their book deals and sales are any indication.

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July 28, 2016

In the future, the way your clothes get dry after they are washed may not involve exposing them to heat or prolonged exposure to air, but may instead involve ultrasonic amplifiers, which can make water molecules so excited that they virtually jump out of wet fabric.

Thanks to work being done today at Oak Ridge National Laboratory, in partnership with China's Haier-owned GE Appliances, that possibility is much closer to reality today. (HT: Core77).

Other than the technology itself and the sheer speed that it can dry fabric, the most surprising thing we learned from watching the video above is that 1% of all electricity generated annually in the U.S. today is used to dry clothes after they are washed.

Now, if we can just get the technology behind dessicant-enhanced evaporative cooling into residential air conditioning units, the amount of electricity that Americans consume to keep cool during the summer might be reduced below the 5% of all electricity generated in the U.S. annually that it takes to do the job today, without any loss of quality of life.

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July 27, 2016

For months, we've been tracking the number of dividend cuts in the U.S. stock market in near real-time, where we've been watching the number of announced reductions reach very worrying levels.

That's why we're pleasantly surprised to be able to report that up to this point in the third quarter of 2016, we're seeing something very positive developing in the market. The cumulative number of dividend cuts that our two near real-time sources have reported for 2016-Q3 through Tuesday, 26 July 2016 is falling both well below what was recorded on the same day of the quarter in the first two quarters of 2016.

Cumulative Dividend Cuts Announced in U.S. by Day of Quarter, 2016-Q3 vs 2016-Q2 and 2016-Q1, Snapshot on 2016-07-26

And for the first time in 2016, the cumulative number of dividend cuts declared through this day of the current quarter (2016-Q3) is running well below the figures that were recorded in the same quarter a year ago (2015-Q3).

Cumulative Dividend Cuts Announced in U.S. by Day of Quarter, 2016-Q3 vs 2015-Q3, Snapshot on 2016-07-26

As measured by the number of dividend cuts declared through this point of time through our two main news sources for this information, 2016-Q3 is so far shaping up to be the best quarter of 2016, keeping well within the "green zone" that corresponds to a relatively healthy condition for the U.S. economy. Or perhaps more accurately, where the level of distress in the private sector of the U.S. economy has dropped to levels that are consistent with stronger economic growth.

As analysts, what we want to see over the next several weeks is whether this positive trend continues. As economic observers however, we have to caution that we've found that dividend cuts are a near-real time indicator of the health of the U.S. economy, telling us how businesses perceived their future outlook in the very recent past. Other measures of economic health, such as jobs, are lagging indicators, which means that the high level of distress that we've just seen peak in the form of dividend cut announcements in the previous month may not yet have transmitted through the economy, where bad news for those lagging indicators would still lie ahead.

Data Sources

Seeking Alpha Market Currents Dividend News. [Online Database]. Accessed 26 July 2016.

Wall Street Journal. Dividend Declarations. [Online Database]. Accessed 26 July 2016.

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July 26, 2016

Each month, Gordon Green and John Coder of the private sector income and demographics analysis firm Sentier Research report on the level of median household income that they estimate from monthly Current Population Survey data published by the U.S. Census Bureau. We've found their estimates to be an invaluable aid for assessing various aspects of the relative real-time health of the U.S. economy.

We use their reports (the latest is for June 2016) to record a nominal estimate for median household income each month, which as future reports are released, we adjust for inflation as measured by the Consumer Price Index for All Urban Consumers in All U.S. Cities for All Items (CPI-U).

Since the beginning of 2016, we've been observing a developing trend for which we now have just barely enough data points to begin making relevant and useful observations, where we find that there are two developing stories. So you can see what we are seeing, here is a chart showing the evolution of median household income in both nominal and real terms from January 2000 through June 2016.

Monthly Median Household Income in the U.S., January 2000 through June 2016

The first and more important story is that nominal median household incomes would appear to have stalled out since December 2015, which is significant because it indicates that the U.S. economy has not been successful in generating higher paying jobs during the last several months.

The second story has to do with the changes in oil and fuel prices, which is greatly affecting the real median household income. In 2015, with those prices falling through much of the year, and particularly in its second half, the effect was to help boost the real incomes of Americans, where those incomes were also growing in nominal terms.

But in 2016, with oil and fuel prices having bottomed and rebounded since the beginning of the year, the effect has been to shrink the real incomes of American households.

Given that 2016 is a presidential election year, you can reasonably expect that whatever trends develop here throughout the year will have an impact on the election's results.

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July 25, 2016

The S&P 500 in the third week of July 2016 ran a bit to the hot side for what our future-based model forecast, but still well within the typical volatility that we would expect. In the chart below, we find that investors are largely continuing to focus on the expectations associated with 2017-Q2 in setting current day stock prices. But we also see that our futures-based model is on the verge of a period of time during which we expect that it will be less accurate than it has been in recent months.

Alternative Futures - S&P 500 - 2016Q3 - Standard Model - Snapshot 2016-07-22

For the last several years, we have been developing a dividend-futures based model for projecting future values of the S&P 500, which incorporates historic stock prices to use as base reference points from which to project the future. More specifically, our standard model incorporates actual S&P 500 closing values that were recorded 13 months earlier, 12 months earlier and 1 month earlier than the period being projected.

In using those historic stock prices however, we have a huge challenge in coping with what we call the echo effect, which results when the historic stock prices we draw upon to create our projections are pulled from periods that experienced unusually high amounts of volatility. A good example of the kind of volatility we're looking to address would be the kind the market saw just a month ago from the market's reaction to the Brexit vote, but much more significantly, on the one-year anniversary of what the market experienced during China's meltdown back in August 2015.

To work around that looming challenge and to try to improve the accuracy of our forecasting model during the periods where we know in advance that our model's forecast results will be less accurate because of the echo effect, we're looking at substituting the actual historic stock prices in our model with prices that reflect the historic mean average trajectory of stock prices.

There's more than one way that we might go about that, but our initial idea is to simply replace the projections of our standard model during the that show the echo effect with the trajectory that would apply as if it were paralleling the mean historic trajectory of the S&P 500 as averaged over each of the last 65 years, which may minimize the discrepancies produced by historic noise between our model's projections and actual future stock prices (absent current day volatility events).

What we're doing assumes that the volatility of the past doesn't have much influence over today's stock prices, which itself is something we strongly suspect, but for which the supporting evidence is less definitive. We also don't know yet to what degree this approach will work, but we'll find out during this quarter. If you follow us, we typically post updates to our projections on Mondays, so you can find out how what we're doing is working almost at the same time we do. Here's the first chart where we're featuring this modified model, which we've imaginatively called "Modified Model 01".

Alternative Futures - S&P 500 - 2016Q3 - Modified Model 01 - Snapshot 2016-07-22

Because the context of how far forward investors are looking in time is so important to determining which of the alternative trajectories that the S&P 500 applies, we make a point of recording the headlines that catch our attention for their market moving potential influence each week. Here are the headlines we identified during Week 3 of July 2016, where much of the news cycle was dominated by reports from the Republican National Convention in Cleveland, Ohio. If you're a serious market investor, you should note how none of them have anything to do with any of the political news from the week, which was a non-event as far as the market was concerned!

Monday, 18 July 2016
Tuesday, 19 July 2016
Wednesday, 20 July 2016
Thursday, 21 July 2016
Friday, 22 July 2016

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