Ironman at Political Calculations

Analyst, long only
Ironman at Political Calculations
Analyst, long only
Contributor since: 2009
Thank you for your comment! Although you focused on out-of-the-money call options for the situation where a downward move in stock prices was considered likely, it's not hard to fill in the blanks to see what the opposite strategy would be in the case of an expected likely upward move in stock prices. [If it's not "buy in-the-money put options", please follow up!]
There's an important bit of information to consider with the If-Then conditions as well - where stock prices are currently, with respect to where our futures-based model indicates they would be based upon how far ahead in the future investors are looking.
For example, there are times when we absolutely know that investors are going to shift their attention to a different point of time in the future, which most often happens when investors are focused on the current quarter (the end of which is still in the future), but the clock for which is ticking down, because there is only so much of the current quarter left to play out before investors *have* to shift their focus to a more distant point of time in the future. The classic example from recent years is 2012-Q4 thanks to what we call the "Great Dividend Raid" ahead of the Fiscal Cliff crisis.
Then, there are most other times where investors have to make some kind of determination of how likely an event is (such as the future timing of Fed rate hikes). You're right in assessing that the market is continually doing that, but here, we're seeing in our model that Fed meetings often coincide with investors focusing on a specific future point in time (the time at which the Fed has indicated it plans to next change interest rates), which provides a basis for setting up an investment strategy based on the likelihood of alternative outcomes.
In a sense, it's like the Monte Hall problem from statistics, where you're given three doors to choose from on a game show, behind one of which is the grand prize. The game show host shows you the prize that is behind one of the doors you didn't pick, then gives you the opportunity to choose again from the two unopened doors, so you now have the choice of sticking with your previous choice or switching it.
Statistics says it is very much to your advantage to switch from your original choice.
For our futures based model, the prizes behind the doors you get to choose are the alternative trajectories for stock prices - and unlike the Monte Hall problem, you get to see what the prize is behind each. The model plays the role of Monte Hall and shows you at certain points of time what the prize is behind a particular door is, or rather, the current level of stock prices tells you exactly how far ahead into the future investors are looking.
Unlike the Monte Hall problem, you have the option of sticking with the door through which you can see the prize. Or you can switch to one of the others based on your assessment of how likely it is investors will focus their attention toward the alternative points of time in the future they represent.
There is a probability that attaches to each, so really the question is one of how you can maximize your returns with that knowlege. Or perhaps a better way to ask the question is if you were to make a larger bet on one of those alternatives becoming the focus of investors, how would you hedge your risk if one of the other alternatives turned into the actual outcome?
The bigger question that we're trying to answer is whether the additional information that the futures-based model we've developed provide any kind of advantage in making trading decisions. You may be right and the benefit may only be minimal at best, or there may be ways of doing so that provides a consistent advantage. Either way, it's a fascinating question for which we don't yet know the answer.
ckoffend wrote:
"Personally, I'd be much more concerned about excessive dividend rate cuts if they crossed all sectors v. just one sector."
If you were complaining about not having enough sectors being negatively impacted enough to have to cut their dividends, you'll be happy to learn that dividend cuts crossed into the biotech and retail services earlier today (2 February 2016).
"All but one of YOUR dividend cuts were oil related . . . yet you want to extrapolate that to the overall economy? Don't get me wrong, I am not saying a recession is not possible and could even be moderately tied to the oil prices losses . . . "
You might consider doing what we did and use the dividend announcement resources for which we've provided links to review the period leading up to the Great Recession. Nearly all of the dividend cuts that were announced in the first half of that recession occurred in just one sector: financials. What lesson about extrapolation would you take away from that finding?
"Perhaps you would want to consider "special dividends" or "earnings" that were paid at a higher rate in December (or Q4) vs. January 2016. Is it really a dividend cut when there is a special payout dividend in December but back to the "normal" dividend in January?"
This is simply not a serious concern. S&P segregates declarations involving ordinary dividends from special (or in their terminology, "extra") dividends into their own separate categories. Meanwhile, both SA and the WSJ do likewise.
"S&P reports 55 dividend cuts and your "real-time" data sources don't even find half that many??? No offense, but doesn't that raise a huge red flag for your sources of information and their accuracy?"
Not at all. S&P is reporting the full universe of dividend declarations over an entire month, while both SA and the WSJ are reporting a more real-time sampling of that full population from different sources - SA references news releases related to dividend announcements, the WSJ taps into the declarations reported in its database.
There's overlap between the two real-time sources, but together, they provide a sufficiently large enough sample to provide significant insights as to what sectors of the economy are going through boom or bust phases. If you're familiar with statistics, then you know that the numbers we commented upon in our article don't present any sort of significant concern.
That's not to say that SA and WSJ don't periodically have issues with their dividend reporting, as both have trouble recognizing unusual situations, such as when a firm alters its dividend payment schedule after an acquisition, which might appear like a cut, but which really is not. Unusual situations tend to be very few and far in-between however, so its not much of a factor affecting accuracy - especially since other news reports and the firm's announcements themselves can be used to verify if a unique situation really exists.
"Unfortunately, your graph with the "recessionary conditions" and "in a contraction" aren't very accurate with reality."
Thanks for leading with your opinion, which reveals that your working definitions of both "accuracy" and "reality" are likely quite different from the most commonly accepted ones.
Yes, but that's not a recent development. A number of major U.S. homebuilders adopted the strategy of building a larger quantity of lower priced homes before the end of 2014, so that part of the story has been true for all of 2015:
What has happened over the last several months however is that signs the market for very-high-end new homes has become much thinner than it has been over the last several years:
We are seeing the combined effect of both factors in the data.
Good research!
CDI also supplies a lot of contract engineers and other technical workers to the aerospace industry, which is also starting to turn south as previously expected orders aren't materializing. Boeing's announcement earlier today (27 January 2016) confirms what we've been seeing in that industry, where the downturn in outlook has already led to layoffs and contract terminations at upstream companies in Boeing's supply chain (such as at Honeywell).
CDI's planned diversification toward IT would appear to be a good move on their part.
Dividend cuts are a clear indication of distress, virtually by definition. Just consider that in order to pay dividends, a company has to have one or both of the following over a sustained period of time:
1. Positive earnings (profits).
2. Positive cash flow.
If a company is missing just one of these things, it would not be considered to be fully healthy, even if it might be able to pay its promised dividends to shareholders from the other source of funds to pay its dividends. When both of these things aren't there, the company is clearly in distress.
Now multiply that distress across an entire industry (microrecession). Or entire industries (recession).
Right now, the dividend cut data is consistent with a microrecession in the U.S. economy, which is best thought of as a period of contraction that is either too limited in scale, scope or duration to meet the official definition of a recession, as might be determined by the National Bureau of Economic Research. At this time, the main thing separating the current economic situation from a full blown recession is its scope.
We're starting to see some indication via which companies are cutting dividends that the scope of distress is expanding, but is not as yet consistent with a wider recession.
The thing to pay attention to is which companies announce dividend cuts going forward and whether they are outside the oil industry, such as today's announcement (long after our article was posted), that staffing firm CDI suspended its dividend. Since their business involves placing people with technical skills at firms with significant engineering or development projects that require specialized contract labor, it suggests a widening negative impact for the larger economy.
"... what we find is that virtually every U.S. firm that has so far announced dividend cuts through this early point in the first quarter of 2016 can be considered to be part of the U.S. oil production industry."
Does this answer your question?
Not necessarily. Because we use historical stock price data as the base reference points from which we project future stock prices, the trajectories shown can echo how stock prices behaved at those earlier points of time. When those prices were more volatile than is typical over a short period of time, the echo of those earlier events can show up in our projections as a short run rally or trough.
The easiest way to compensate for that effect is to take a step back and simply connect the dots for the longer term trends on either side of the deviation from those longer term trends, which should work well in this case.
For really large scale echoes, such as what we'll see later this year when we get to August on the anniversary of the "China crash", we'll go to the trouble of resetting the baseline reference stock prices that we'll use in our projections. We did that for much of the latter portion of 2015 and had better accuracy with our rebaselined model than did our standard model during the period where the historic stock prices we would otherwise have used experienced larger than typical levels of volatility.
[Although it's something of a headache to deal with, one of the advantages of using historic stock prices as we do is that we have a very good idea in advance when our standard model of how stock prices work will be most effective and when we need to adapt it to account for the echo effect.]
As for whether stock prices will take a second dive in 2016 - that will depend more upon why and when investors might shift their focus from one future quarter to another. Right now, they would have to fully shift their attention to 2016-Q1 to get down to 1800, which became less likely given Atlanta Fed president Lockhart's comments yesterday afternoon (you can tell within a few minutes of when he made them in a one-day chart!)
To get there, we think that other Fed officials would have to contradict Lockhart's comments to refocus investors on 2016-Q1, or alternatively, a spate of really bad news could do that as well, especially if it might affect the expectations for dividend payouts.
That said, once investors set their focus on a particular point of time in the future, investors should expect stock prices to generally drift downward over the quarter. If they select 2016-Q3 or 2016-Q4, we'll have a sharp rally before that drift sets in. If they select 2016-Q1, we'll have a crash before that happens. Or if they stay focused on 2016-Q2, we'll mostly likely skip both the rally and the crash and just have the downward drift.
Hope this helps!
If you're going to claim that we're giving a one-sided story, you might consider getting the story that you want to tell right. In fact, the story you're trying to peddle is pretty old news - the increase in bank foreclosures is entirely attributable to clearing the backlog that developed when compliance with new laws following the bursting of the bubble back in 2006 slowed down a large portion of their regular foreclosure process to a crawl, which they're finally working through following recent court decisions. The story linked below is specifically for Nevada, but very similar stories apply elsewhere:
The more interesting story is that RealtyTrac is reporting that the year over year total number of foreclosures across the U.S. has fallen, from about 115K to 105K (at least through November 2015). Even with that nearly 60% year over year increase in Bank Reposessed Properties that you appear to be so worked up over, which really represents foreclosures that should have happened months and years earlier, but didn't, which as a result has contributed to the excessively slow recovery for the industry.
Hope this helps clear things up!
For the detailed data we have from the 2015-Q4, which indicated 77 non-ETF firms that cut their dividends:
36 = oil/natural gas
13 = finance/banking
9 = mining
7 = real estate investment trusts
6 = manufacturing
2 = technology
2 = shipping
1 = chemicals
1 = food
We think that if not for the Fed's interest rate hike pump fake back in September 2015, which prompted nine interest rate-sensitive REITs to cut their dividends at that time, the number of dividend cut announcements in 2015-Q4 would have been at least that much higher.
We won't know the actual number though until S&P updates their monthly dividend report, which we'll likely cover sometime next week.
We have data for the entire stock market that extends back to January 2004, which we used to identify the various thresholds shown as the backdrop of our charts. Ideally, we'd like to have several additional business cycles worth of data than what is available to be able to extract more insights from historical comparisons.
For those who would like to see how a hypothetical investment would have performed over time (rather than just consider rate of return data), we have another tool you might find useful - "Investing Through Time":
It uses the same data we provide through our "S&P 500 At Your Fingertips" tool, and will give you inflation adjusted results for the performance of your hypothetical investment in terms of the dollars of the year at the end of the period of time that you select. It will also let you consider the effect of reinvesting dividends, which is where most of the income accumulated for investments in the period from say January 1891 through December 1974 would have been obtained. We update both tools monthly, shortly after the Bureau of Labor Statistics publishes the inflation data for the preceding month.
Thank you for your question. We will not publicly present our model's projections for 2016 until sometime in 2016.
If you're in any way competent, you can do so yourself. Just follow the links provided in the last paragraph of our article, just above the references and links to the original data sources.
Hope this helps!
Good question. It's very natural for incomes to follow a lognormal distribution - if they don't, it's an indication that some sort of artificial restraint has been forcefully imposed upon earning incomes, which comes with a tremendous price - much more widespread and much more severe poverty, characterized by rampant corruption. The modern day case study is Venezuela.
Skew is only an issue if one erroneously assumes that the distribution of income in the U.S. is distributed normally (per a Gaussian, normal bell curve type, distribution).
It's not. Instead, the distribution of income is lognormally distributed, which becomes very evident when the incomes at the top end of the income-earning spectrum are counted in the same size increments (or "bins") as all the other incomes. The "top coding" or grouping of all incomes earned above a certain threshold into a single data point in the animated chart showing the Pew Research Center's household data is what gives the false impression that skew isn't explained by the data.
It's a pretty common error, especially for those who aren't very familiar with lognormal distributions.
Yes, the "disappearing middle class" is a demographic illusion. It is caused by shifting age demographics of the U.S. income-earning population over time coupled with their average lifetime income trajectories.
It reflects the situation where the physical population of people in the typical "middle-income" earning years of their lives is much lower than the population of people who are at or just past their peak earning years (Baby Boomers) and also much lower than the population of people are are at the lowest levels of their lifetime income trajectory (Millennials).
Your argument is a bit strange in that it suggests that somehow, the actual number of people in the middle income earning years of Age 35-50 would somehow be larger if not for the sad fate of places like Detroit or Braddock, or for that matter, Silicon Valley or Austin, when the real issue is that fewer people of those ages exist in the U.S., which has been the case since their births.
The shifts indicated in the animated graphic over time are entirely consistent with the shifting age demographics of the U.S. income-earning population over time combined with their average lifetime income trajectories. The middle class has shrunk only because households led by people whose age places them within Generation X are much fewer in number than the much larger populations of the Baby Boomers and Millennials, who respectively occupy the highest and lowest ends of the income earning spectrum in the U.S.
Don't be silly. We know, within a fairly small margin of error, how stock prices will change in the future through the end of the year, but we've left the job of determining the exact trajectory they might take up to you, as we're only willing to hold your hand so far.
All you have to do is figure out exactly how far in the future investors are focusing their attention, and when they might shift their focus from that point to another point of time in the future. Oh, and which other point of time in the future that might be. Once you've done that, the rest of the forecasting job becomes really easy - like shooting fish in a barrel.
We have a follow on article that spells out exactly which entities announced dividend cuts in October 2015:
The original article is at our site, which displays the table with the information in the web-friendly format we originally presented:
Yes and no. A rather large number of companies bank on big, end-of-the-calendar year performances, where it is not until the earnings season in the fourth quarter that they announce if they expect to hit, surpass or miss their projections.
A good case in point is Caterpillar, which is actually getting ahead of the upcoming year-end earnings reporting curve in altering their projections going forward today (24 September 2015).
It looks like SA's editors just took a screen shot of our animated chart - you can view it in motion at our site:
Answering your questions:
1) As-reported earnings.
2) We don't follow Thomson Reuters' reported earnings, so we cannot offer an opinion.
Following the "losing streak in the S&P 500" link we provided:
The longest losing streak recorded over this period of time lasted twelve consecutive trading days, which began after it peaked on 21 April 1966 and lasted through 9 May 1966.
The timing of that longest losing streak roughly corresponds to the fallout from the Fed's decision on 12 April 1966 to begin "'restricting' rather than 'moderating' the growth in the reserve base, bank credit, and the money supply" available to the U.S. financial system, inaugurating a prolonged period of increased distress for the U.S. economy. That distress was indicated by the reversing momentum of the S&P 500 index, where it coasted on its previous upward inertia to top at 92.42 on 21 April 1966, after which it entered into a general period of decline until it finally bottomed at 73.20 on 7 October 1966, some 20.7% below its previous peak level. It would not recover to that former peak until 27 April 1967.
WeMustResist: We wouldn't describe our cumulative dividend cuts by day of quarter chart as forward looking, as its really communicating the relative health of the market in real time.
We have other tools for looking forward:
All you need to do to figure out where stock prices are going is to determine how far head in time investors are looking. The chart linked above shows how stock prices would be different based on which future quarter they focus upon.
But then, that's because stock prices are just a simple quantum kinematics problem!...
swisspete: Good questions! Those levels are based on our correlation of weak or negative economic growth quarters in the U.S. with the announced dividend cuts documented in S&P's Monthly Dividend Report, which you can access through their S&P 500 page, under the "Additional Information" drop down menu.
The following site shows both the full time series and the previous edition of our cumulative dividend cuts by day of quarter chart (which we developed to get a more real-time reading on the state of the U.S. economy):
Because of the limited amount of data, which only goes back to January 2004, the levels we present should be treated more as rough guidelines rather than definitive thresholds - there's definitely some gray areas (or rather, orange) for making a clear call.
There are two things that all investors should know about dividend cuts:
1. They are very painful to the owners and managers of the companies (often the same people) that announce them, because it directly cuts their income and are almost invariably accompanied by drops in the value of the stock they own, which directly cuts their wealth.
2. A company needs at least one of two things to make good on their promised dividend payments: positive earnings (or profits) and positive cash flow. If both of these things are missing, it's a clear indication that they have misjudged their business situation and need to make changes to remain solvent or to restore their solvency.
While these factors may be influenced by business/economic cycles, they are not influenced by things like the age of the companies or whether other companies are maintaining or increasing their dividends (stopping dividends is the same as cutting them.) Given the pain factor involved, dividend cut announcements perhaps provide the clearest signal of where distress is occurring within the economy/market.
In fact, if we were asked what one bit of economic data is the most valuable to know for telling us how the market or economy is doing today, we'd want to know how many companies have cut their dividends within the last 30 days. It's perhaps the best real-time indicator of the relative health of the economy.
We're just getting our feet wet with the data - we'll be returning to it periodically in the future (where you've provided some interesting suggestions!)
We thought the generic data on winning and losing streaks was interesting in and of itself, and is something that we plan to turn into a tool, where calculating the odds of a particular streak enduring for a given number of days might also be of interest.
We should note that tool is unlikely to be selected by SA's editors to be featured here. It will however be available on our site, and since we've included the math on which it will be based in these articles, is something that anybody with sufficient math skills can do on their own if they want to get a jump on us!
Only for those afflicted with anosognosia.
Everyone else, and we do mean everyone else, would simply recognize it as an updated observation on the state of the U.S. housing market.
DonPaul-O asked:
"What are we supposed to do with it anyway?"
If you cannot figure it out, despite our holding your hand, we are not inclined to help you.
Dean Mitchell wrote:
"I don't understand how you can call this a bubble?"
It might help if you familiarize yourself with the definition of what a bubble is:
For housing, we would want to use rent as the representative of the income that might be otherwise earned from owning a house, but there isn't any data reporting median rent for the nation on a monthly basis. Fortunately, there is an extremely strong relationship between what people pay to live in houses and their before-tax income, which allows us to substitute income for rent in our analysis. You can find out more about that relationship at the following link:
We found your following comment to be really weird:
"You show charts that indicate New home prices that a rising faster than median incomes, then make the comment that builders have stopped building for the lower income segment."
If you had bothered to read just one paragraph further than you apparently did, you would have discovered that we also said:
"That second phase now appears to have lasted up until February 2015. A third phase, in which U.S. homebuilders would once again appear to have begun producing a larger number of new homes for the lower end of the market, with the results of that change in business strategy beginning to show up in the national level data after February 2015."
We'd offer additional comments on the rest of whatever it was that you wrote, but opted to follow your example and stop reading them after the first paragraph.
Whoops! You would seem to have missed the biggest changes in the U.S. housing market in the past year. If it helps, you might want to investigate the specific strategic changes that homebuilders like D.R. Horton, Lennar and Pulte Homes have implemented, where they have increased their sales by specifically producing much less expensive homes aimed at the broader market.
Then again, perhaps you're not familiar with these particular builders. If it helps, see:
"I find the omission of any reference to interest rates or other expenses of owning a home to be the most glaring error. In the real world, it's the average Joe's monthly cost of owning vs actual take home pay that matters."
You must live in a very odd world, because those things make very little difference in what people actually pay to live in a home.
For at least every year since 1984 (as far back as the data goes), the average amount that Americans pay to live in a home (incorporating all their expenses for doing so), regardless of their income, is about 10.4% of their income before taxes, plus or minus ~1% for any given year. That tiny variation from year to year is all the difference that might be attributed to the factors you claim are somehow important.
Also, if it helps clear up any confusion you may have regarding our obligation to produce "actionable information" for you, the last we checked, you have not provided any payment for us to do so. Since we will not accept any payment from you, you can expect that we will continue not producing any actionable information for you.