Category Archives: forecasting

Losing Streaks in the S&P 500

We don't normally follow the Dow Industrials index (NYSE: DJI), since it really doesn't capture enough of the breadth of the U.S. stock market, but last Friday, 7 August 2015 saw a pretty rare occurrence, with the Dow having closed lower than the previous day for the seventh consecutive trading day in a row.

While the S&P 500 fared slightly better by that measure over that same period of time, declining in only six of the same seven days, we wondered what its worst streaks were over its entire history.

To find out, we tapped Yahoo! Finance's S&P 500 historical price database and ran the numbers. The chart below reveals the number and duration of two or more consecutively down days that the index has recorded over the 16,506 trading days from 4 January 1950 through 7 August 2015.

Number of Two or More Consecutively Down Days for the S&P 500, 4 January 1950 through 7 August 2015

Since 4 January 1950, we see that the S&P 500 has had losing streaks run seven tradings days or longer some 44 times, with 23 of those streaks lasting exactly seven days before the index recorded an up day to break its losing streak.

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.

Unless there is significant erosion in the expectations for future dividends or a significant negative noise event, that kind of decline is unlikely to occur in today's market, but the general trend our rebaselined model of how stock prices work currently forecasts is such that the remainder of August 2015 would appear to be set to follow a downward trajectory.

Alternative Futures - S&P 500 - Rebaselined Model - Snapshot on 7 August 2015

Things would appear set to improve in September 2015, with the biggest boost coinciding with the timing of the Federal Reserve's Open Market Committee meeting in the middle of that month, but our limited ability to peer into the farther future suggests that would provide only a short term boost, as 2015 on the whole would appear to be set to be best described as a year of relative stagnation for U.S. stock prices.

What We Do, Explained by Others

One of the nicer things ever said about the kinds of analysis we do here at Political Calculations recently surfaced over at the ChicagoBoyz blog, as Grurray took on the challenge of explaining the unique brand of stock market forecasting we do.

We can look at ways of fundamentally gauging the valuation of the stock market such as price to earnings ratio or the so-called Warren Buffet Indicator of total market cap to GDP ratio. I like to look at the Q ratio which is a simple comparison of the total price of the stock market to the replacement costs of all companies listed. This is the favored metric of billionaire black swan investor Mark Spitznagel, who by the way wrote a most excellent book, The Dao of Capital, about Boydian investment strategies.

Q Ratio Since 1900, July 2015, Data through June 2015 - Source: Doug Short - ratio - Pricey but is it dicey?

By this measure, the market looks to be at a pricey level compared to other points in time. 1907, 1929, 1937, and 1968 were all years when the stock market peaked and saw a significant decline. The problem is it’s also at the same level as 1997, which had a small pause before marking the half way point in multi-year rally. We generally have seen regression to the mean in the past, but that doesn’t necessarily suggest it has to ever happen again. We could be waiting a long time for a sanity check to take hold, especially if the definition of sanity has changed.

A shorter term answer possibly comes from the world’s best econometrics blog Politcal Calculations. They believe, convincingly in my opinion, that expectations for future dividends drive stock prices in the near future, absent any surprising shocks to upset the apple cart. Those of us who used to watch Larry Kudlow on CNBC (since his show was cancelled there hasn’t been any reason to watch that silly network anymore) remember he used to say ‘earnings are the mother’s milk of stocks’. Well if that’s true than dividends are your father’s pemmican.

What they do is take values of dividend futures traded on the Chicago Board of Options Exchange and apply a multiple (and some other math) to convert them to expected stock prices. Their calculations show a possible slide in prices for the next few weeks to few months. It has worked reasonably well in the past with a few caveats.

There are different instruments traded for different times in the future. Prices can and do take leaps from one trajectory to the other. It usually happens when someone from the FED talks about raising rates, and then the financial press speculates what specific month or quarter it can happen. In this way, stock prices behave similar to quantum particles bouncing from one energy level to another. It’s not a good way to pin down exactly where stocks are going but just gives a range.

The other caveat is this measurement only works when the market is in a state of relative order, and not buoyed or rattled by some overly cheery or dreary news. While at a smaller level the market seems to obey quantum mechanics, at the macro level it acts like a natural system, following mathematical probabilities such as those observed in predators hunting or even groups of people foraging. The market moves from more easily observable and predictable periods until the forageables (earnings and dividends) run out, in which case it moves into chaos and unpredictability until new expectations are established.

What will trigger rapid moves in either direction and out of the current financial horse latitudes is anybody’s guess. There’s a big vote in Greece this weekend, but how many times has that situation reached a cliffhanger? Perhaps too many to matter anymore. As unsatisfactory as it sounds, what usually occurs is something we weren’t expecting, not an event that seems to replay itself over and over again. The best we can really predict is that we won’t be drifting forever, and the time will come when the stock market will move far away from this level. The key is to stay ready for it when it finally does.

Here's the link to our stock market forecasting math and here's our math-free description of how stock prices work.

Now, to address Grurray's "other caveat"! When you get into our model, you'll find that our math actually does continue to work when stock prices go on what's called a Lévy flight, which is the pattern that Grurray is referring to when he links to articles describing how both predators and people adapt their hunting and foraging methods when food is scarce. We know it continues to work in that situation because we invented behind our analytical methods in the latter months of 2008, when stock prices were collapsing (we publicly introduced the discovery we made that enabled us to develop our forecasting methods on 10 December 2008).

Behind the scenes, in the early months of 2009, we were finding that we could anticipate where stock prices were heading as they were crashing after they had entered into Lévy flight, because what was changing was the expectations for dividends in the future, changes in which preceded subsequent changes in stock prices, which is what allowed us to confirm the direction of causality in the relationship between the two.

Not to mention being able to quickly confirm just a week after the fact that the bottom had been set for that particular Lévy flight for U.S. stock prices. We later proved (again, behind the scenes) in late 2012 that our model is capable of handling the opposite situation. That latter episode also confirmed that the quantum nature of those expectations always applies - even during Lévy flight.

Where Grurray's other caveat is correct is when stock prices are driven by factors other than their basic fundamentals. The classic example here actually predates our model's development by a number of years, where we don't believe that our forecasting model could have tracked stock prices very well without considerable adjustment during the period of the Dot Com Bubble. That event was caused by a disparity in the tax rates that applied to capital gains and to dividends, which greatly changed the results of the investment rate of return math for dividend versus non-dividend paying stocks for investors so much that it continued to distort the entire U.S. stock market until the disparity between the investment tax rates was finally fixed in late May 2003.

Unfortunately, we are not able to put our model to the test of the Dot Com Bubble because we lack the historic dividend futures data during that period of time, which prevents us from being able to accurately re-create what the future looked like in those days.

Other than those significant non-fundamental stock price driving factors, the rest for us is pretty much noise - things that actually are the result of investors reacting to the relatively random onset of new information as it becomes known, the speculation associated with which accounts for much of the apparent day-to-day random walk of stock prices (you know, like the reaction in the U.S. market to what's going on in Greece). We spent several years after our original discovery of how stock prices work collecting the necessary data and documenting the ongoing context behind it to quantify that aspect of how stock prices behave, which allows our model to determine not just the general future trajectory of stock prices, but also the likely ranges we can reasonably expect stock prices will fall during periods with "typical" levels of noise in the market.

We've come a long way. We've gone from only being able to anticipate what the average prices of stocks would be during the next month to accurately anticipating the actual trajectory of stock prices within a small margin of error on each day of the next month (as we've previously demonstrated under optimal conditions). Or if you prefer longer range forecasts, we can reasonably anticipate the general trajectory of stock prices several months in advance.

But not much more than that. Although we can project the alternative trajectories that stock prices are likely to take on a daily basis as much as a year into the future, it is far more likely that the expectations we use in our forecasting model will change well before that distant forecast future arrives.

After all, a man's got to know his model's limitations!

Decoherent Expectations and the S&P 500

A week ago, we went to the very specific trouble of spelling out three very specific "what-if" scenarios for the trajectory that U.S. stock prices, as measured by the closing value of the S&P 500, would take during the week to be. Thanks to optimal forecasting conditions, one of those scenarios was almost perfectly dead on target.

Alternative Futures for S&P 500, 2015-Q2, Standard Model, Snapshot on 2015-06-19

The what-if scenario in question is the one where we projected what the S&P 500 would be if investors were to shift their forward-looking focus to 2015-Q3 in making their current day investment decisions. As for what made our forecasting conditions optimal, we have to thank the relative absence of noise in the market, where the Federal Reserve's Open Market Committee meeting provided the primary market news for the week.

That news was that economic conditions had improved since the first quarter of 2015, which investors interpreted as indicating that the Fed would be likely to act sooner rather than later to start hiking short term interest rates, which had become the dominant expectation on Monday, 15 June 2015. Although the Fed did not commit to a specific timetable or other details for its interest rate hiking plans, our standard model suggests that the stock market behaved in a way that is fully consistent with investors shifting their focus from 2015-Q4 in the previous week to instead fix their focus on 2015-Q3 and then holding it there through the end of the week.

So how come we couldn't have specifically forecast that specific trajectory? Why would we go to the very specific trouble of forecasting three separate likely trajectories for stock prices that differed only by how far in the future investors might focus their attention?

Well, as we keep saying, it is because stock prices obey the rules of quantum physics, where stock prices actually exist in a state of superposition, much like atoms and subatomic particles.

One mind-boggling consequence of quantum physics is that atoms and subatomic particles can actually exist in states known as "superpositions," meaning they could literally be located in two or more places at once, for instance, until "observed" — that is, until they interact with surrounding particles in some way. This concept is often illustrated using an analogy called Schrödinger's cat, in which a cat is both dead and alive until beheld.

Superpositions are very fragile. Once disturbed in some way, they collapse or "decohere" to just a single outcome.

For stock prices, the things that exist in superpositions are the expectations for the amount of cash dividends that will be paid out by specific points of time in the future, so we automatically have the situation where multiple expectations exist simultaneouly in the market. When investors observe, or in our terminology, "focus" upon a specific point of time in the future in response to new information as it becomes known, stock prices will collapse or decohere to a single outcome that is consistent with the expectations for dividends at the point of time they've focused upon within a relatively small margin of error - at least, given the amount of noise that typically exists in the market.

That situation applies when nearly all investors shift their attention to a single point of time in the future. There have been times when we've observed investors splitting their forward-looking attention between two separate points of time in the future, with stock prices falling between the "100% focused" trajectories our model forecasts, with stock prices being weighted accordingly with respect to the percentage split in investor focus.

As you might imagine, depending upon how different the expectations are for different points of time in the future, changes in stock prices that result from shifts in how far ahead in time that investors are focusing their attention can be very pronounced. Those shifts are a major contributor to volatility in the stock market when they occur and account for much of the apparently chaotic behavior of stock prices.

Knowing all that then, projecting the future trajectories of stock prices with some degree of accuracy is a complex proposition, but not a difficult one once you have the data that applies for each future point of time whose expectations for dividends are known. Anybody who can solve a simple quantum kinematics problem can do it.

Dividends: The Absence of Worse

According to Standard & Poor's Monthly Dividend Action Report [Excel Spreadsheet], in May 2015, 21 U.S. companies acted to cut their dividends. That's three more than did in April 2015 and a clear sign that recessionary conditions are still present in the U.S. economy.

Monthly Number of U.S. Publicly-Traded Firms Announcing Dividend Cuts, 2004-01 through 2015-04

For those who insist that winter weather was a significant factor dragging down the entire first quarter's GDP, or that the Bureau of Economic Analysis' seasonal adjustments for the first quarter in the U.S. are somehow responsible for that quarter's negative GDP figure, the number of dividend-cutting companies says otherwise. They also say that 2015-Q2 is shaping up to be better than 2015-Q1. And since we were virtually the only observer of the U.S. economy to correctly forecast that 2015-Q1's GDP would be recorded as negative, in large part because we pay attention to the number of companies that announce dividend cuts each month, that's probably something that so-called "Blue Chip" and Federal Reserve forecasters can stand to learn to do as well, if getting economic forecasts right is somehow important in any way.

What's more, they also say that the last two weeks have been the best weeks of 2015, by far. So good, in fact, that the cumulative number of U.S. companies cutting their dividends has fallen behind the pace that was being set in the first quarter of 2015.

Cumulative Number of U.S. Publicly-Traded Firms Announcing Dividend Cuts by Day of Quarter - 2015Q1 and 2015Q2, through 31 May 2015

That doesn't mean that the U.S. stock market is about to take off however. At present, it would appear that investors are progressively shifting their focus away from the current quarter of 2015-Q2 in setting stock prices to instead make their investment decisions in more and more accordance with the expectations associated with 2015-Q4, where most of that transition has occurred in the last week.

Alternative Futures for S&P 500 in 2015-Q2 - Standard Model - Snapshot Through 2015-06-01

That's understandable since that's fits the recent conventional wisdom that the Fed will wait until its December meeting to finally begin implementing its plan to start hiking short term interest rates. As you can see in our chart showing each of the alternate futures that stock prices might follow depending upon which point in the future that investors fix their attention, that transition is consistent with stock prices either moving sideways or slightly higher. Pretty much in keeping with what our forecast has been for the year to date.

Going back to the evidence of dividend cuts, what we see now is consistent with a U.S. economy on track to experience a sluggish-to-slow positive growth rate in 2015-Q2. As for where distress was to be found in the U.S. economy of May 2015, it predominantly remains small firms in the oil, gas and mining industries that are being most negatively impacted. Here is the full list we recorded from Seeking Alpha's Market Currents reports and the Wall Street Journal's Dividend Declarations reports.

Publicly Traded U.S. Companies Cutting Dividends in May 2015
Date Company Symbol Old Dividends per Share New Dividends per Share Percent Change
1-May-2015 Voya Prime Rate Trust PPR $0.02900 $0.02750 -5.2%
1-May-2015 AllianceBernstein AB $0.57000 $0.45000 -21.1%
4-May-2015 SandRidge Miss Tr II SDR $0.37500 $0.29000 -22.7%
4-May-2015 SandRidge Permian Trust PER $0.65600 $0.64000 -2.4%
6-May-2015 AmTrust Dep. Pfd. C AFSIC $0.47656 $0.44792 -6.0%
6-May-2015 Och-Ziff Capital Mgmt OZM $0.47000 $0.22000 -53.2%
6-May-2015 NVE NVEC $2.06000 $1.00000 -51.5%
7-May-2015 AuRico Gold AUQ $0.02360 $0.01000 -57.6%
8-May-2015 Apollo Global Mgmt A APO $0.86000 $0.33000 -61.6%
8-May-2015 Chesapeake Granite Wash CHKR $0.44960 $0.38990 -13.3%
8-May-2015 ECA Marcellus Trust I ECT $0.18000 $0.08400 -53.3%
8-May-2015 Ormat Technologies ORA $0.08000 $0.06000 -25.0%
8-May-2015 Sabine Royalty Tr UBI SBR $0.27658 $0.22925 -17.1%
8-May-2015 Terra Nitrogen TNH $2.50000 $2.08000 -16.8%
8-May-2015 Viper Engy Ptrs L.P. Un VNOM $0.25000 $0.19000 -24.0%
13-May-2015 National Bankshares NKSH $0.58000 $0.53000 -8.6%
13-May-2015 PPLUS FR Call Ser GSC-2 PYT $0.19167 $0.18125 -5.4%
18-May-2015 Marine Petroleum Trust MARPS $0.31009 $0.14480 -53.3%
19-May-2015 Cross Timbers Royalty Tr CRT $0.15696 $0.05237 -66.6%
19-May-2015 Permian Basin PBT $0.02378 $0.01567 -34.1%
21-May-2015 Dom Res Black Warrior Tr DOM $0.17455 $0.09875 -43.4%
21-May-2015 Mesa Royalty Tr MTR $0.07796 $0.05736 -26.4%
22-May-2015 China Yuchai CYD $1.20000 $1.10000 -8.3%

There are two trading entities who were recorded as having cut their dividends in May 2015 that likely were not included in S&P's official count: AmTrust Dep. Pfd. C, a preferred stock, and China Yuchai, a China-based company whose stock trades on the NYSE.

Noting those two "false positives", we believe we've fully captured all the firms that acted to cut their dividends in May 2015. And speaking of how good the last two weeks have been, no U.S. companies have announced dividend cuts since 21 May 2015.

Data Sources

Standard & Poor. Monthly Dividend Action Report. [Excel Spreadsheet]. Accessed 1 June 2015.

Seeking Alpha Market Currents. Filtered for Dividends. [Online Database]. Accessed 1 June 2015.

Wall Street Journal. Dividend Declarations. [Online Database]. Accessed 1 June 2015.

Spring 2015 Snapshot of Expected Future S&P 500 Earnings

Every three months, we take a snapshot of the expectations for future earnings in the S&P 500 at approximately the midpoint of the current quarter. Today, we'll confirm that the expected earnings per share for the S&P 500 throughout 2015 has continued to fall from the levels that Standard and Poor had projected they would be back in February 2015.

Forecasts for S&P 500 Trailing Twelve Month Earnings per Share, 2010-2016, Snapshot on 21 May 2015

The table below quantifies the carnage for what can now be described as a deepening earnings recession, which Standard & Poor continues to forecast will run through the third quarter of 2015:

Expected Future Earnings per Share for the S&P 500
Future Quarter 2014-Q4 2015-Q1 2015-Q2 2015-Q3 2015-Q4
On 13 November 2014 $109.96 $118.23 $124.48 $131.07 $134.89
On 15 February 2015 $102.89 $103.34 $103.77 $105.00 $112.03
On 21 May 2015 $102.31 $99.25 $98.79 $99.49 $106.61
Change in Expectations Since 13 November 2014 (mid 2014-Q4) $7.65 $18.98 $25.69 $31.58 $28.28

Much of the decline in earnings expectations is tied to the decline in global oil prices, which primarily affects the oil industry, and also affects the business outlook for financial institutions and capital equipment manufacturers.

What we find especially curious however is that S&P would currently appear to expect an exceptionally robust recovery in the S&P 500's earnings per share beginning in the fourth quarter of 2015, largely driven by the energy-related sector of the S&P 500 index. Based on what we see in the expected future for crude oil prices through the end of 2015, we don't think that earnings recovery based on improving revenues is well supported, unless a significant amount of cost reduction occurs within the industry. Since that reduction in economic activity would ripple outward from the energy sector and negatively affect other sectors of the economy, we think that the overall earnings for the S&P 500 would be likely to perform much less well than S&P currently expects.

Data Source

Silverblatt, Howard. S&P Indices Market Attribute Series. S&P 500 Monthly Performance Data. S&P 500 Earnings and Estimate Report. [Excel Spreadsheet]. Last Updated 21 May 2015. Accessed 22 May 2015.