Weekly Wrap-up: Risk and the 4-Year Cycle

By: Adam Oliensis | Mon, Apr 3, 2006
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The following article was originally posted at The Agile Trader on Sunday, April 2, 2006.

Dear Speculators,

The Dynamic Trading System did not close any trades this past week so it has no realized gains or losses to report. The System has two open positions, which we will continue to update in our daily Morning Call and Afternoon Note.

In this space we have recently been discussing the 4-Year Cycle on the SPX. And this week I'd like to go into some detail on that cycle and why, for now, we remain bearish, though not aggressively so, for the period between now and October.

Let's start with a logarithmically scaled chart of the SPX that dates back to 1962.

As you can see, such periods are rare (less than 5% of the time), though we are in one such period now. In general such periods augur near-term bearish for the SPX, though there are some exceptions. Those exceptions, though, (in the early '60s and in 1995) exist historically primarily in the 1st year of the 4-Yr Cycle and exclusively in the 1st half of the cycle.

During the past 44 years there is no precedent for the market's refusing to retrench during the 4th year of the cycle, and the latest prior onset of such a retrenchment was in February of the 4th year, where we are now all the way into April of the 4th year of this cycle without having suffered one.

Note: in 1994 the SPX was able to move up +5% after going uncorrected for 90 trading days. However that 5% was subsequently sharply corrected (and then some) before the SPX launched into the great bull market of the latter '90s.

Conclusion? Though there is a low-probability "exception" scenario (ala 1994), we are likely overdue for a sell-off.

So, why doesn't it feel like it? For our long-time readers, I'd like to remind you of our discussion of the human tendency toward complacency at the statistically least opportune times, and for those of you who are new to our work...

Here's an example that illustrates the general point:

Let's say there's a statistically unlikely event that takes place 1% of the time, which is to say on 1% of the opportunities for it to happen. So, suppose, just for argument's sake, that if you go for a walk in New York City, 1% of the time you will get hit by a bus. (Obviously this is a greater chance of disaster than there is in reality, but we're just trying to understand something about how risk works, statistically speaking, over time.)

So, if you go out for a walk 1 time, you have a 99% chance of not getting hit and a 1% chance of getting squashed. But suppose you go out for 1 walk every day for 10 days. The chance that you will get hit on 1 of those occasions rises. And the way it's calculated is by figuring the odds that the LIKELY event will obtain at every single iteration and then subtracting that from 100%. The equation is:

D = 1-(1-P)^N

Where

D=cumulative percentage chance of disaster
P= Percentage Chance of disaster on each opportunity (iteration)
N=number of iterations

So, if you go out for 10 walks, your chance of getting turned into chopped meat is

1-(1-.01)^10 = 9.6%.

And if you go out for a walk every day for, say, 90 days, your chance of getting obliterated is

1-(1-.01)^90 = 59.5%.

Here's what the series looks like.

And in this scenario, if you go out for a walk every trading day of the year (about 252 times) the odds are about 92% that you will meet your demise.

But the funny thing about our human nature is that if, say, you went out for 252 walks in New York City and came back 252 times, without having had any violent encounters with city vehicles, you would assume that experience was teaching you that there was very little danger. (And indeed it might be, if you didn't already know the likelihood of getting run over.)

As human beings we are especially primed to generalize from experience (that's science) but most especially to generalize from our most recent experiences (which is less reliable science--or anecdotal evidence). So, the more walks we go on without getting pulverized the less likely we FEEL it to be that we will ever get pulverized, irrespective of what statistics might tell us. As our risk increases, statistically speaking, we feel safer and safer.

We are all familiar with the expression "tempting fate." One has to wonder if our savings-short, consumer-spending-driven, mortgaged-to-the-gills, trade-deficit-heavy, job-exporting economy isn't doing just that. That is, it's worth considering that we might be somewhere fairly far along on the curve charted above, feeling safer and safer carrying all these economic loads, but with an ever greater and greater chance developing of the incidence of one or another severe, "dislocating," and "unlikely" events.

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OK, now that our shoulders are up around our earlobes and we're all terrified of getting run over by a bus...or by the stock market... let's look at the range of likely magnitudes for what we anticipate will be a corrective period in the SPX.

For a variety of reasons we continue to expect a relatively benign 4-year low to be made in 2H06. (Our definition of benign in this context is a retrenchment of less than 20%.) And here is a weekly chart showing one set of our reasons for holding this view...there's a lot going on here, so let's dig in:

Let's repeat that last one just to get it straight. The red highlights appear when 2 conditions obtain simultaneously: 1) the PE is below 15.1 and 2) the SPX will suffer a weekly closing low, down 20% or more during the subsequent year.

Of the 4,134 weeks studied here 185 show red highlights. And 119 of those came by 1946. So, all told, red highlights have shown up about 4.5% of the time, and since 1946 red highlights have appeared just 2.2% of the time. (New red highlight is unlikely.)

So, unless we have a Great Depression, a World War, or Runaway Inflation (as per the fat red stripe in the middle of the chart in the mid '70s) the odds of a drop of more than 20% from current levels look pretty darn slim.

Here are some other fun facts that we discovered using this study:

As for why the correction is likely to be relatively modest by 4-Yr Cycle Low standards, let's look at some macroeconomic data.

This chart plots Q/Q Annualized Nominal Gross Domestic Product Growth (dashed purple line), the 4-Yr Average GDP Growth Rate (thick purple line), and 1 Standard Deviation from the 4-Yr Average (blue line). (The blue line represents the value of 1SD, it's not measuring 1SD from the purple line.)

What we see on this chart is that Nominal GDP is growing at a solid rate and that, after the dip in 2001 the non-volatile trend has been resumed. What's remarkable is that GDP continues to grow, that inflation remains low by recent historical standards, and that the volatility of growth remains so low as well.

The 4-year average for Nominal GDP is above 5% with 1 Standard Deviation at 1.8% (meaning that about 68% of the time GDP has come in between 6.8% and 3.2%). Strong growth, low volatility of growth, and low inflation are what make up the "Goldilocks" economy. But the question is, what has allowed for this improvement. And one answer, (over and above New Technology, Increased Productivity, REFI Cashouts, and Fiscal Stimulus) is Money Supply.

This chart shows the 13-Week Annualized Growth of M3 , the broadest measure of Money Supply (blue line), and the 50-Wk Average of that 13-Wk Growth (black line).

What stands out to me is how volatility in M3 rose sharply in the '90s, stayed high through the bear market and may now be declining. So, as the volatility of GDP has stayed low the Money Supply has been tinkered with, counter-cyclically, like "shock absorbers," increasing the volatility of M3 in order to "smooth the ride" in the GDP numbers.

At this point the trend in M3 growth is very close to its long-term median, despite the alarmist writings of perma bears. And the Fed is ceasing to publish this data (which is a damn shame)...but one can well imagine that the extreme volatility on this chart is both a) embarrassing to monetary authorities and b) very difficult to interpret in real time. So, while speculation is rampant as to why this data will now disappear from public view, its volatility suggests that the Fed has been extra-active in managing the supply of money, and perhaps susceptible to the charge of being too aggressively interventionist.

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EARNINGS AND VALUATION

We continue to be concerned with the deteriorating trend in EPS estimates. The growth rate of the F52W EPS (blue line below) has shrunk to +13.3%. And while that's still fairly robust, the 3-month annualized rate of growth of the Consensus (red line below) is down at +5.6% and leading the blue line lower.

 

 

Once that blue line drops below +10% the market is likely to struggle, as per the yellow highlighted areas on this chart.

Our Risk Adjusted Fair Value target is below the SPX price for the first time since mid '04.

We derive this target using this equation:

F52W EPS / (TNX + Med ERP)

Where

F52W EPS = Forward 52-Week EPS ($86.47)
TNX = 10-Yr Treasury Yield (4.853%)
ERP = SPX Earnings Yield - TNX (6.68% - 4.8535% = 1.83%%)
Med ERP = Median Post-9/11 ERP (1.95%)

$86.47 / (0.04853+ 0.0195) = 1271

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Summing all this up...the odds favor a correction on the SPX of more than 5% but less than 20% between now and October. Beyond that, it would appear likely that the index will make a higher high by the spring of '07, if not before.

In our daily issue of the Morning Call we'll examine the technical charts on the leading and lagging indices this coming week, as we seek confirmations and divergences on the major market indices. If you'd like a free, no risk 1-month trial to our daily work, please join us at The Agile Trader. And if you're interested in auto-trading futures based on our Dynamic Trading System (model portfolio has netted +393% in realized position gains since July '05), click on The Agile Trader Index Futures Service to read more about our service and to subscribe.

Best regards and good trading!

 


 

Adam Oliensis

Author: Adam Oliensis

Adam Oliensis,
Editor The Agile Trader

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