8/30/2015 How to Calculate Fair Value of the Secular Market

The recent gyrations of the market have brought back the question of bubbles and market trends.

A “bubble” is an abnormal inflation of a type of investment in proportion to other investments.  The classic is the Tulip mania of the 1630s. More recent episodes are the Nasdaq frenzy of the late 1990s and the housing bubble of the previous decade.

In each case, the investment in question edged out other investments and became inflated in value in relation to its typical place in the market.

I’ve noted many times that quantitative easing has inflated most assets together. Although there are some distortions, the fact remains that the market as a whole is not in a bubble.

To calculate a “bubble” environment I have multiplied the birth rate plus 46 years (i.e. the average age of the American work-force) by the Fred M1 money supply and plotted their current deviation from a 1959 to 2015 regression.  That value gives a current deviation of 0.0721797.

Next, I’ve done the same for the S&P itself during that same time period, with a current deviation of -0.035329.

If we SUBSTITUTE the demographic * money supply deviation for the price deviation we see a fair value for the S&P to be 2250.

I’ve plotted this graphically:

A few points. First, secular bear markets show fair value trailing behind price, while secular bull markets show price trailing behind value.  We certainly DO have an artificial market environment, with price and value tracking in lock-step. Ordinarily this would still be a secular bear, but quantitative easing has camouflaged that fact.

As I’ve argued routinely in previous posts, the market isn’t due for a crash because it actually hasn’t risen in real value. It just looks like it has been going up because of all the M1 money supply expansion. Even Shiller’s CAPE ratio is distorted by the disconnect between inflation and money supply.

The next obvious point of the graph is what a bubble actually looks like.  The 2000 and 2007 peaks are wildly inflated, even on this logarithmic chart. They are spectacularly obvious.

And the final point is that the market is not above fair value.  Instead, it is almost 12% below fair value.

Bear markets are routine.

Crashes are not.

A bear market can come at any time, and the leading / lagging sectors show a preference for defensive sectors right now.  I do expect more correction to follow, even up to a bear – but I do not expect a 1929, 2001, or 2008 style crash.  The worst we could see would be a 1987 type event – annoying, but not disastrous. I would be afraid of too much margin right now, but there is no reason to dump non-leveraged investments.

I don’t time anyway, of course. But even if I were a market timer, I’d leave my non-leveraged investments in place.

Tim

8/30/2015 Why Trump Would Cause Another Great Depression

In the 1928 Presidential cycle we elected an economic hero to the White House.

He was a businessman who cared for the common people, and had proven it in the economic crisis that engulfed Europe in the aftermath of the First World War.  So successful was this hero that Harry Truman used this same giant to be the architect of the Marshall Plan after the Second World War.

He saved Europe from two disasters, and designed the core features of the New Deal for the United States in the onset of the Great Depression.

That man was Herbert Hoover.

In Keynesian economic theory Hoover made one mistake, he raised tariffs instead of devaluing the dollar – but aren’t these two sides of the same coin?  Making other countries less competitive seems little different from making your own country more competitive. The question for us today is if that difference could indeed trigger a new global depression.

Being a run of the mill Reagan-Keynesian, I believe it would indeed trigger a new depression, and the man promising to do just that is Donald Trump.

Trump isn’t alone, philosophically. He errs in a way very common to politicians of both parties: they believe that the way to get more of what you want is to create less of what you don’t want.

They are wrong. Humanity abhors a vacuum, but they are too lazy to automatically fill it. Therefore, the way to get less of what you don’t want is to make more of what you do.

In other words, if you want less abortions, then you want more support for distressed pregnant women and greater understanding of non-lethal forms of birth control.

If you want less carbon intensive sources of power, then you create more of the cheaper kinds of replacements: most notably nuclear power.

The reason for this is that nothing is ever truly a zero-sum game. Less of one thing does not equate to exactly the same amount more of another. More of one thing does not equate to exactly the same amount less of another.

Less money for the super-rich is not exactly the same amount more for the poor.

Less money for China is not exactly the same amount more for the United States.

Even worse – beyond a certain level LESS for China will translate into less for the United States too!

This is similar to what I have written about the Laffer Curve in the past.

Some careful readers are still jarred at a hybrid term I used a few lines back: “Reagan-Keynesian”. At first glance it looks like a contradiction in terms, but Reagan merely used the mirror image of the standard approach.

The standard approach increases taxes in bullish years and increases spending in bearish years.

The Reagan approach decreases spending in bullish years and decreases taxes in bearish years.

The Keynesian model is not just “taxes and spending” but rather a RATIO of the two. The ratio of taxes / spending should be greater in bullish years and smaller in bearish ones. Go too high OR too low and you have less ability to manipulate that ratio. This is why I have argued for the greatest possible amount of taxation, which mathematically and historically is 35% GDP. In our Federal system that would be 20% Federal, 10% State, and 5% Local. Any higher OR lower than these optimal points and you have less total revenue, and therefore less ability to spend or pay down the national debt.

Ultimately Franklin Roosevelt went too high with a maximum tax rate of 94%, and Ronald Reagan went too low with a maximum tax rate of 28%.

How does this relate to trade and tariffs?

It relates conceptually, because a tariff is an attempted tax on a foreign trade partner. We humans are perfectly happy to tax someone else, while ignoring that this might hurt us in the process.

Too high taxes on “the rich” means less jobs for “the poor” – making them even poorer.

Too high taxes on “the foreigners” means less jobs for “American workers” – making them even poorer.

And while we are at it, we have the same issue with immigration.  I’ve pointed out in the past that 50 million aborted babies have created a demographic hole in our economy. The ages of these murdered Americans since 1973 would range from 42 to 0, for an average of 21 years old: just the age of people entering the workforce. If you murder people who would be ENTERING the workforce just as baby boomers are RETIRING from the workforce, then you have a huge gap of people able to PAY for those retirees.

The original great depression was caused by the demographic hole of the First World War and the Spanish Flu epidemic. It was exacerbated by a DECELERATION in economic activity by the Smoot-Hawley tariff disaster.

We are facing a similar economic hole in this country, caused by Roe vs. Wade and solved by human replacements – that is, all of those immigrants (legal and illegal).  We NEED those immigrants to make us more competitive and we NEED lower trade barriers to allow that force of available workers to make us more prosperous as a nation.

On both counts, Trump is the exact opposite of what we need. Is he a successful businessman?  Yes.  So was Herbert Hoover.

Tim

8/28/2015 Trade Notice

The Full Model sold NOV and bought JCOM with a 2% favorable gap.

8/27/2015 Sector Change

There was no favorable gap this morning, and the Sector Model sold XLU and bought XLE before the close.

8/26/2015 Sector Change

After the close, the Sector Model changed back to XLE, and I will trade in the morning if there is a favorable gap.

The configurations are back into a market top:

8/25/2015 Market Configuration

The latest gyrations have moved the sector configurations back into a bearish stance:

I was hopeful that the move back over the weekend to a market top would give us a potential for a rally late in the week, but that is less likely now.

Volume and breadth are clearly favoring the more defensive sectors, as reflected in the Sector Model's move into XLU before the close.

8/25/2015 Sector Change

The Sector Model sold XLE and bought XLU before the close.

8/24/2015 Precisely Normal

Sector Model	XLE	-7.25%
Full Model	Date	Return	Days
PWR	3/9/2015	-18.60%	168
CBI	4/2/2015	-10.22%	144
MTZ	4/9/2015	-20.24%	137
DRQ	5/15/2015	-25.82%	101
RES	5/19/2015	-31.84%	97
NOV	6/23/2015	-24.31%	62
INT	7/7/2015	-18.73%	48
FFIC	8/3/2015	-1.83%	21
BT	8/11/2015	-6.28%	13
TM	8/12/2015	-7.72%	12
(Since 5/31/2011)
S&P	Annualized	9.44%
Sector Model	Annualized	19.22%
Full Model	Annualized	11.71%
S&P	Total	46.51%
Sector Model	Total	110.44%
Full Model	Total	59.81%
Sector Model	Advantage	9.77%
Full Model	Advantage	2.27%
	Previous	2015
S&P	53.06%	-4.27%
Sector Model	142.84%	-13.34%
Full Model	101.13%	-20.55%

As I wrote on 7/5/2015, we have entered a bear market configuration.

That said, bears don’t normally go straight down – and they don’t always reach a full bear close of 20%.

Right now we are 10% down from the most recent high on the DOW.  If we stop before 20%, we will only have a “correction.”

What does this mean?

If you are a market timer, you may or may not be too late.

If you are not a market timer, this means nothing at all.

Painful?  Absolutely!  Meaningful?  No.  If you are not a market timer, this is an annoying interlude in a long term plan.

The Sector Model is now slightly above the long term trend.  It has had an annoying year to date, but the long term trend couldn’t possibly be more normal.

And the good news is that the sector configurations have backed up to a market top configuration.  The start of the week could be appalling, but the market should rally soon.

We are now BACK into a market top configuration.

I just got back from vacation.  It was an expensive time away, but I wouldn’t have made any changes even if I were home the whole time.

Tim

8/12/2015 Trade Notice

The Full Model sold SPN and bought TM with a 2% favorable gap.

8/11/2015 Trade Notice

The Full Model sold AHC and bought BT with a 1.5% favorable gap.

8/9/2015 The Tortoise and the Hare

Sector Model	XLE	-2.10%
Full Model	Date	Return	Days
PWR	3/9/2015	-16.55%	153
CBI	4/2/2015	9.36%	129
MTZ	4/9/2015	-14.60%	122
DRQ	5/15/2015	-23.49%	86
RES	5/19/2015	-18.65%	82
SPN	5/28/2015	-27.85%	73
NOV	6/23/2015	-19.18%	47
INT	7/7/2015	-14.67%	33
AHC	7/28/2015	12.42%	12
FFIC	8/3/2015	-1.73%	6
(Since 5/31/2011)
S&P	Annualized	10.93%
Sector Model	Annualized	20.98%
Full Model	Annualized	13.54%
S&P	Total	54.44%
Sector Model	Total	122.15%
Full Model	Total	70.26%
Sector Model	Advantage	10.05%
Full Model	Advantage	2.61%
	Previous	2015
S&P	53.06%	0.91%
Sector Model	142.84%	-8.52%
Full Model	101.13%	-15.35%

Now we come to the time for wondering just what the point can be when after four years of effort the Full Model has collapsed so spectacularly that it is nearly as bad as the S&P.  To make matters worse, taxes will eat away any alpha that was left, leaving a simple holding of SPY superior to many hours of effort.

The Sector Model, of course, continues to tick away without much care in the world, even after itself losing over 8% so far this year:

An annoying year, but most profitable overall.

And yet, even here there is a problem: the Sector Model trades short term. With capital gains rates at 43.80%, the NET return rate for the Sector Model would be 20.98% * (1-43.8%) = 11.79%.

In other words, you might as well have just held SPY and forgot about the entire exercise.

That’s what IRAs are designed to solve (and yes, I run this in an IRA). The delayed capital gains tax is collected at long term rates after many years of compounded returns.

IRA accounts are fine for these short term versions of the model. But neither will work for a taxable account.

Nevertheless, there is a factor that can be used to full advantage if measured correctly: an adaptive long term holding period.

That is, the Full Model has a secondary holding period based on the collapse of Effective Annualized Capital Gains rates.

Here’s a table to show how that works:

< Year	Annualized Rate	Base Rate
1	43.80%	43.80%
2	11.27%	23.80%
3	7.38%	23.80%
4	5.48%	23.80%
5	4.36%	23.80%
6	3.62%	23.80%
7	3.10%	23.80%
8	2.70%	23.80%
9	2.40%	23.80%
10	2.16%	23.80%
11	1.96%	23.80%
12	1.80%	23.80%
13	1.66%	23.80%
14	1.54%	23.80%
15	1.43%	23.80%
16	1.34%	23.80%
17	1.26%	23.80%
18	1.19%	23.80%
19	1.13%	23.80%
20	1.07%	23.80%

We all know that the short term rate is higher than the long term rate.  What we do NOT usually calculate is the fact that the effect of a capital gain tax can be greatly reduced against compound returns if we can hold onto a stock for a number of years.

This becomes an Effective Tax Rate as seen in the following chart:

That’s all well and good, if one can pull it off.  But who can pick long term outperforming stocks?

Well, Warren Buffett, for one.  He’s not much of a trader.  He waits for a stock to create significant long term value and then holds on – often for decades at a time.

Once we reach a holding period of greater than 5 years, the Effective Tax rate is less than 5%.

I’ve not only tracked the returns of the Full Model from the time I’ve bought and sold each stock – but I’ve also continued to track those sold stocks as if I were still holding them.

The annualized return RATES in the following graph are calculated in two ways: first without tax, and second with tax.

The top line is the return rate in an IRA account of each stock since I began tracking live trades on 5/31/2011; all 189 of them.

As time lengthens, the Effective Tax Rate falls closer and closer to zero, until the taxed account is almost as good as an IRA account.

The ideal holding period for a stock in an IRA account is about 99 calendar days.

The ideal holding period for a stock in a taxed account is about 1525 days (so far).  I’ve not yet found the maximum point.

Now, this is an interesting graph, since we can see that the return rate gradually decays from 99 days until a bottom around 886 days.

After that two things happen:

1)      About 10% of the stocks cease to exist (either through purchase or bankruptcy).

2)      The remaining stocks recover aggressively.

In Haugen’s studies, “value” companies tend to under-perform “growth” companies for about five years, but the stocks associated with those companies have been too aggressively discounted.

The market is very accurate in identifying which companies will do better than others in the next few years, but the market is NOT very accurate at pricing those discrepancies beyond three years.

Investors tend to hyperbolically discount time as it fades further into the future. The difference between two and four years is treated the same as the distance between one and two years.

Logarithmically, those two are equal, but time does not progress logarithmically – it progresses linearly. 

To put this simply, investors will price correctly from one to two years, but price two to four years as if it were two to three years. I’ve shown this kind of perception error in the following table.

Reality	Perception	$100.00
1	1	$105.00
2	2	$110.25
3	4	$115.76
4	8	$121.55
5	16	$127.63

The actual “value” of a company after 5 years is discounted as if it were 16 years in the future. What may seem to be a moderate 5% growth rate is perceived as if it were closer to 1% because of the logarithmic perception of time.

This is how value stocks can become growth stocks. Earnings will begin to surprise and traders will over react in buying the stock as if it had miraculously made 16 years’ worth of growth in only 5 years.

We are always trying to pull a rabbit out of the hat, but if Aesop’s Fable is to be believed, we’d be better off trying to pull a tortoise out of our hat instead.

By the end of this year I will either convert the Full Model into a long term holding period, or else add a long term version.  I haven’t decided yet.  But four and a half years of data has confirmed something that Benjamin Graham argued many decades ago: in the short term the market is a voting machine; but in the long term it is a weighing machine. Good companies are worth buying and holding for the long term.

The key is to find out which companies, and for how long.

We aren’t exactly there yet – but we are close enough to begin the final version of the Full Model – a version that is infinitely patient, and infinitely scalable.

Tim