10/29/2014 Sector Change

After the close, the Sector Model shows XLF with a lead over XLB.  If there is a favorable gap in the morning, I'll make the trade.  Otherwise, I'll recalculate before the close.

This is a result of the confirmed end of QE (bearish for XLB) and a reliance on zero interest rate policy going forward (bullish for XLF).

We could say, "Yeah, but we knew that."  Yes and no.  We all believed this would happen, but the reward on XLB would have been greater with a positive surprise than the risk of a confirmation of what was already anticipated.

In other words, one could lose 3% for being wrong, but gain 7% for being right (in theory).  These are the kinds of bets we all have to make in our investing strategies.

Tim

10/26/2014 The Purpose of the Full Model

                The “Mousetrap” is a method for merging technical and fundamental indicators into a single model.  The concept for each aspect of the model is mean reversion.  On the technical side I measure long term volume-breadth against price-strength in a sector or industry.  On the fundamental side I measure long term growth in cash flow, book value, and earnings against total return and total debt.

                If the debt is low and the price return is cheap compared to long term growth, we can find a relatively safe stock within an industry that is technically primed for a short term reversion toward the mean.

                At a point in which price begins to balance against both technical and fundamental indicators, the stock will become attractive to momentum traders, and I will sell just as demand begins to catch up to supply.

                In this manner I buy stocks when no one wants them, and sell them when everyone wants them.

                The returns for this method are better than 20% annualized, and I have been enjoying this return rate in live trading since 05/31/2011, when I launched the model.

                In April of 2012 I began publishing the trades at www.market-mousetrap.blogspot.com – advertising each trade the night before it was to occur.  There is no ambiguity or hindsight bias in these trades.  I post them before they happen, and publish the running returns, both good and bad.

                During this period I have experimented with some of the fundamental features, and tightened up the technical parameters, but the general trading concept has been the same: buy stocks in low demand sectors and sell when demand begins to pick up.  I sell them well before the top, and in most cases only enjoy the first third of a price move.  But the first third of a price move allows me to unload them with ease (and to hold for longer, if scalability ever required it).

                Measurements are long term in order to avoid the effect of High Frequency Trading (HFT) algorithms on the model.  With a long enough gauge, the HFT effect becomes background noise, and the model will not degrade in the future.  Humans tend to think in terms of weeks and months, logarithmically discounting longer time frames.  HFTs are designed to take advantage of human behavior, and in order to compete with each other they work in ever shortening time frames.  Their goal is a 60% return.

                My goal is a consistent 20% return, leaving me out of their time frames and target return rates.  I don’t compete with them, but I’m happy to pick up the debris they shake loose in their activity.

                Live trading has been consistent with back-tested results:

By the numbers:

	S&P	Sector Model	Days
Total	63.23%	1954.80%	5785
Annualized	3.14%	21.03%

 

                That is, during the 12/23/1998 to present period of combined back-test and live trading, the S&P has given an annualized rate of return of 3.14%, while the Sector Model has returned 21.03%.

                No back-test is possible for the Full Model, but the annualized return rate for the live trade period of 5/31/2011 to the present has produced 21.89% annualized returns, which is consistent with the Sector Model.

                Note that the primary goal of the Full Model is not out-performance per se, but rather scalability.  Containing only 10 stocks with an average holding period of 70 days allows me as a small investor to perform one trade a week.  As the portfolio increases in size, I can increase to as many as 10 trades a day, with 500 logical positions, without even needing to resort to intraday measures. 

                In other words, the Sector Model is fine for a small portfolio, but the Full Model can function with a nearly unlimited portfolio base.

10/26/2014 Hits and Misses

Sector Model	XLB	0.00%
Large Portfolio	Date	Return	Days
SR	6/2/2014	13.32%	145
CFI	6/9/2014	1.23%	138
RRD	7/21/2014	4.82%	96
ESI	8/4/2014	-38.43%	82
BSET	8/11/2014	15.05%	75
STRA	8/18/2014	10.41%	68
PBI	8/25/2014	-8.09%	61
CLF	9/2/2014	-36.10%	53
KFY	9/29/2014	3.72%	26
IQNT	10/6/2014	5.96%	19
(Since 5/31/2011)
S&P	Annualized	11.77%
Sector Model	Annualized	25.90%
Large Portfolio	Annualized	21.89%

 

Rotation: selling RRD; buying EDU.

EDU is tripling down on the educational industry, already represented by ESI and STRA – which average together to about a 14% loss.  Misery loves company, as they say.  But the model continues to scream out for that industry, and even ESI is starting to respond.  It’s made great gains in the past ten days.

The Sector Model has also recovered nicely:

 

Both models, then are back above 20% annualized returns since the launch with real money on 05/31/2011.

I did note the other day, however, that there was some whipsawing on the Sector Model.  It switched from XLB to XLI less than five minutes before the close on 10/22.  I BARELY caught the trade.  Steve missed it in his parallel fund, because he trades before 2.

On 10/23 the Sector Model showed XLB just before the close and I switched back.  Then AFTER the close it showed XLF.  I missed .2% on Friday, and Friday the model closed on XLB.

Last week, on the other hand, we both missed a trade that actually worked in our favor by about .65% above what the model itself shows.

So, I’ve slightly outperformed the model (by accident) and Steve has slightly underperformed (also by accident).

No trading can perfectly catch every single whipsaw.  What you want to do is to have a model that works and to get as close to it as possible, which is what we are doing.  Sometimes the hits and misses will work in your favor, and sometimes not.

However, one does want to minimize the “luck” element, and this week I’ll be switching to a real time service to replace the twenty-minute delayed free service I’ve been using.  Steve and I will continue to trade in parallel and if the 3:50 trades with real time do indeed work out better than the 1:50 trades Steve has been making, we’ll nudge the time back to the later trade in his fund.

Either way, it’s been a great year so far for both of us and we are quite pleased.  The tweaks are mostly from a perfectionistic obsession I have with my baby.

Tim

 

 

10/24/2014 Multiple Whipsaws in Sector Model

Two days ago the sector model flipped at the last minute from XLB to XLI.

Yesterday just before the close it flipped back to XLB.

I made both trades, barely.  Steve stayed in XLB.

After the close the call was for XLF, so this morning I'll trade a favorable gap if one is available.

Crazy market right now.

10/19/2014 Why No One Knows What the Market is Really Worth

Sector Model	XLB	1.33%
Large Portfolio	Date	Return	Days
SR	6/2/2014	3.38%	138
CFI	6/9/2014	5.15%	131
RRD	7/21/2014	-1.57%	89
ESI	8/4/2014	-35.78%	75
BSET	8/11/2014	6.45%	68
STRA	8/18/2014	8.95%	61
PBI	8/25/2014	-9.85%	54
CLF	9/2/2014	-42.00%	46
KFY	9/29/2014	0.69%	19
IQNT	10/6/2014	4.59%	12
(Since 5/31/2011)
S&P	Annualized	10.51%
Sector Model	Annualized	23.86%
Large Portfolio	Annualized	20.86%

 

No rotation.

Both the Full Model and the Sector Model have enjoyed a good rally toward the end of the week.  The biggest bounce was in ESI – which is still under water, but not nearly as bad as it was a few days ago.

The Sector Model has now changed to XLB (Materials), after getting a good spike from XLI:

 

 

The great question for now is: what the heck is the market worth?

I don’t know, and I don’t think anyone can truly know.  The reason is QE.

I’ve mentioned this before, but I’ll go into a bit of the math.

When plotting standard deviation channels of historical birth rate data against Shiller’s CAPE ratio, the greatest positive correlation is in the birth rate plus 44 years, and the greatest negative correlation is in the birth rate plus 64 years.

What that means is that people are contributing the most toward their investments in the midst of their working years (and 44 is right in the middle), but that they start drawing from their investments when they retire (hence the negative correlation around age 64).

People in their forties have their basic needs taken care of and start to panic about not having enough for retirement.  People in their sixties don’t know how to budget well and take more than they should before they start selling off assets to live a more manageable lifestyle.

But what IS the true CAPE ratio?  Should it be measured against the Consumer Price Index as Shiller does, or against the M1 measure of money supply as I have argued in this blog?

Here’s Shiller’s CAPE:

 

A CAPE ratio of 24.77 is crash territory.  This is the basis for John Hussman’s continual panic warnings on his own blog.

Now let’s look at an M1 (money supply) adjusted CAPE ratio:

 

A CAPE ratio of 16.57 is rather close to the long term average.

Next, let’s compare that to CAPE projections based on the ratio of 44 to 64 year olds:

 

I’ve terminated these data sets at the end of 2013, because we have not yet reached the end of 2014.

Aside from the titanic spike of “irrational exuberance” in the Dot Com boom, both CAPE ratios spent most of their time near the demographic forecast.  They only break away from each other during QE.

Those with careful eyes can see that the present “bull” market actually peaked in 2010 and never surpassed it.  The market has only gone “up” against the dollar – which has been diluted by QE.

In simplest terms, the market only looks like it is going up because the dollar is falling against it.

So that brings us to the question of “fair value”.  To calculate this, I am taking my demographic progressions against my M1 adjustments to Shiller’s CAPE ratio from 1974 through today:

 

In the broadest terms, the market can go over a decade without crossing its “fair value” designation.  Long term forecasts are not timing tools.  They are merely sanity checks.  However, it is fair to say that the market is not aggressively over “fair value.”  My M1 adjusted CAPE ratio is only 16.57, which is just a tad higher than the 15.06 CAPE forecasted by the 44/64 year old demographic ratio.

So where does that leave us going forward?

Unfortunately, it’s impossible to tell.  Although “fair value” is a little below today’s price on my rosy M1 deflator, it’s NOT so pristine on Shiller’s native CAPE ratio with the CPI deflator.  Using Shiller’s CAPE against the demographics, “fair value” on the S&P index is 1150.

That’s a long way down.

On the other hand, if you use an M1 deflator instead of CPI, you get “fair value” at 1715.  Still lower than today, but not nearly as frightening.

My guess is that inflation will eventually sync back up with money supply, but until that happens, “fair value” is an unknowable figure.  Or rather, “fair value” is an unusable range of 1150 to 1715.

To be equally unhelpful – but more simplistic – the market tends to hover around one standard deviation below the long term price regression during secular bear markets, and around one standard deviation above the long term regression during secular bull markets.

The demographics will keep us in a secular bear until the end of 2018.  Right now the market’s natural range is between 1935 and 1045, with a typical value around 1420.

However you look at it, we should have exhausted the upward potential for a while.

Nevertheless, QE has moved the goal post.  Even these wildly unhelpful ranges could be well removed from the true direction the market will take.  It could be fairly priced now for all we know, demographics be damned.

Good news?

Well, no – because if the market WERE correctly priced in today’s dollars, then everything else isn’t.  Milk, beer, gas, bread, and port wine cheese will all have to run up to catch it.

The last time we’ve seen anything like this was the seventies, after Nixon bought his re-election through massive treasury manipulation.  Although folks like to compare our current President to Carter, they are a bit premature.  We’re just now ending the equivalent of Nixon’s first term.

The next President will have to bridge the gap between Carter and Reagan.

God help us.

Tim

10/12/2014 Time to Run?

Sector Model	XLI	0.00%
Large Portfolio	Date	Return	Days
SR	6/2/2014	1.19%	132
CFI	6/9/2014	-2.80%	125
RRD	7/21/2014	0.69%	83
ESI	8/4/2014	-67.30%	69
BSET	8/11/2014	5.85%	62
STRA	8/18/2014	-1.92%	55
PBI	8/25/2014	-13.93%	48
CLF	9/2/2014	-51.43%	40
KFY	9/29/2014	-2.57%	13
IQNT	10/6/2014	0.16%	6
(Since 5/31/2011)
S&P	Annualized	10.90%
Sector Model	Annualized	23.64%
Large Portfolio	Annualized	18.36%

 

No rotation.

The question of the hour isn’t where to invest, but whether to invest at all.  My own model has been soundly punished and folks are scared.

Time to run?

Perhaps – but my model is designed to ride it out.  I don’t time; I rotate.

I have more to write this week about market valuations, but for now – just a note that the sector model has shifted to XLI.

Tim

PS – careful eyes will have noticed that I’ve dropped the style model.  My recent losses were the result of trying to combine the sector and style calls in the Full Model selections.  The problem is that I would have to trade one stock per DAY instead of one per week or two.  Ended up getting caught with too many small caps leading into a correction, just as the style model flipped to large caps.  Lesson learned.  Back to the simpler method that worked better to begin with.