Running markets without walras and schumpeter

“
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Running Markets without Walras and Schumpeter?
“Chance, which is nothing but the want of art,” John Arbuthnot (1692)1
,
“Stock prices are like “bubbles” held aloft by operational profits, cash flow and debt service,
earnings and distributions, and every so often that are engaged (liked) or disengaged (not liked) at the
price of risk.” - Goetze 2009
“The only reason for making a forecast, is to reduce risk. But we already know that the only no risk
investing, is at the stock price, SP>SF, the price of risk.” - Goetze 2009
“Because we know where we are, we will also know when to buy, when to hold, when to take profits,
and when to sell.” - Goetze 2009
“The “gap” U=SP-SF>0 is an instance of “enduring price arbitrage” and does not depend on the
more common and uninspired micro-arbitrage profits discovered over micro-seconds by overachieving
computers.” - Goetze 2009
“I never discourage anyone from buying a lottery ticket. I don't know the future. But, to win, he or she
needs to buy all the tickets. And that's the price of risk (in a lottery).” - Goetze 2009
Partitioning the DOW 2000 to 2009 – portfolio yielded compounded 29% IRR
Doing the Dow is one thing we've talked about in some detail in recent editions of CassandraNews. In
that rather simple portfolio (there are only thirty stocks, and seven of them are not even of investment
grade for anyone's portfolio) that we crafted in the DOW had an IRR (Internal Rate of Return) of 29%
per year through the years 2000-2009.
In that same period the DOW itself returned essentially, nothing. In fact the DOW lost 40% of the
money investors had placed there in their hope of enjoying earnings and capital security. Moreover
portfolio managers cannot tell us why, markets mumble and stumble! They condition us to buy shares,
they do not make them, mumble, caveat emptor. Not then and still not now can the economists say,
either, it seems! Classical, monetarists, medallists, Salty or Freshie, Bastian, Bayesian, Austrian,
Keynesian, Modern or Texan all with their closed macro over micro models of nuanced terms in
separate languages, Babel, babble, bust! Munch or Lee, murmur, murmel, Alligator Pie, they lost my
money in TTI? It sounds much like a strange recital of, The Walras and the Schumpeter, in all respect
to both those great minds, and to Charles Dodgson’s Lewis Carroll and Alice, but mostly to her great
granddaughters Katie and Dullah, his lessons are always such fun:
Veblen was shining on the exchange board, shining with all his might:
He did his very best but bid curves seemed smooth up and to the right
And this was not so odd, because it was middle of the tranche flight.
The Walras was shining sulkily, because he thought the Veblen
Had just no business to be there as this equilibrium gets done
"It's very rude of him," he said, "To come and spoil my fun!"

“
The pleas were yes as yes could be, their hands were dry as dry.
You could not see a cloud, because no cloud dared in this sky
So bids were flying overhead, here, where the bids do really fly.
The Walras and the Schumpeter were walking close at hand;
They wept like anything to see such quantities of demand
"If these orders only cleared," they said, "it would be grand!"
"If seven maids from seven banks swept it up for half a year.
Do you suppose," the Walrus said, "That they could get it clear?"
"I doubt it," said the Schumpeter, while shedding a bitterest tear.
"O Investors, come and walk with us!" the Walras did beseech.
"A pleasant walk, a pleasant talk, along this shiny prospectus reach:
We can do with more than four, and still can give a hint to each."
The Walras and the Schumpeter talked up a pile or so,
And then they rested on a block priced conveniently low,
As all the little Investors queued with their wallets in a row.
"The time has come," said Walras, "To talk of so many fine things:
Of shoes-and ships-and sealing-wax- of cabbages- tranches and kings
Why the market’s are boiling hot, and these tranches do have wings."
Investors squealed, “We’ve no more cash without margin we will rue.”
"After such kindness, that wouldn’t be such a dismal thing to do!"
"This short is so fine," the Walras said, "Do admire this rising view!”
"It was so kind of you to come! And you are so very nice!"
The Schumpeter said nothing but "Just another short entice,
I wish you were not quite so deaf-- I've had to ask you twice!"
"It seems a shame," the Walrus said, "To play them such a trick,
After we've stretched them out so far, and made them run so quick!"
The Schumpeter muttered, "Their cash is not spread too thick!"
"I’ll weep for you," the Walras said, "I’ll deeply sympathize."
With sobs and tears he sorted, those wallets of the largest size,
Holding his pocket-handkerchief before his streaming eyes.
"O Investors," said the Schumpeter, "we’ve had such a fine run!
Shall we be trotting along again?” But answer came there none.
But this was scarcely odd, because they'd gleaned every one.
As Walras calmy strode along saying ‘Do come quickly, now, run.
There’s some trashing of Veblen to be sure, as I hear Keynes has some

“
Fine champagne, an excellent vintage, Eighteen Seventy Four- it will be such fun.”
Further, while so many listened to the sales pitch going-on for “securing” their savings, in those nine
years, we made only thirteen (13) decisions running that simple portfolio in the DOW, thirteen (13)
decisions to run the first and still open portfolio of five stocks (five buys and eight sells, to take or
protect profits), and fifty-six (56) decisions to run the now closed portfolio (twenty buys and thirty-six
sells) yielding the 29% IRR. We did this all, with abiding only one rule.
The One Rule: It's in our portfolio(s) if, and only if, the stock price, SP>SF, the price
of risk, and otherwise it is not.
It is not such a surprisingly effective rule, really. We found it is based in profoundly useful analysis of firms that
form equities which inhabit and hopefully trade for capital financing in our real markets. Some of those are
making money, in a real and fundamental sense we have observed, and they tend to gain in stock price.
Just, the One Rule: It's in our portfolio(s) if, and only if, the stock price, SP>SF, the price

“
It is not such a surprisingly effective rule, really. The price of risk (SF) is an extension to the equity market
(of cash and stocks) of the Tobin “Separation Theorem”2
which deals with investments in cash and
bonds. The price of risk is also “the least stock price at which a company is likeable”3
and that's a
theorem and the only thing that we know – or anybody knows – about stock prices is that the “price of
risk”, defined in absentia4
in the Capital Assets Pricing Model (CAPM) of Sharpe and Markowitz, is
“the least stock price at which a company is likeable”.
Moreover, the portfolio manager always has lots of time to consider these decisions. Companies that
are in the portfolio above the price of risk, are typically in the portfolio for a long period of time, such
as six months, fifteen months, two years, or more. There's no reason that a portfolio manager should
ever be “surprised”5
.
No surprise, then, that what's true in the Dow, about stock prices and the price of risk, is also true in the
NASDAQ 100. It's a theorem, after all, but one that is practical and has shown how it works.
The DOW (2000-2009) - And Price of Risk Gives You Odds, 2.34:0.98 To Win.
The NASDAQ 100 (2000-2009) - And Price of Risk6
Gives You Odds, 2.57:1.03 To Win.

“
Appendix: X-axis Scale
Since we're having so much fun, the Price Change Volatility Range [-0.5,1.0] is on the y-axis, and, I can tell
you about the x-axis. The Range [-0.5,1.0] or Range [-1.0,0.5] for each Price Risk Region, SP>SF and
SP<SF, respectively, is on the y-axis and simply represents the log-returns observed in each quarter, in
each Price Risk Region. The x-axis is scaled as -½ logab = -½ log(b)/log(a), where “b” is the logarithm
of the product of all the positive returns (SP/SP1, SP>SP1) in any quarter (and the product is therefore
greater than one), and “a” is the logarithm of the product of all the negative returns (SP/SP1, SP<SP1)
in the same quarter (and the product is therefore less than one). The “scale factor” (f=1/2, in this
example), can be used to compress or expand the scale on the x-axis to provide a “spectral analysis” of
the results, locating the “centre of mass” of the price changes, in terms of risk and uncertainty.
Each company is coloured by a different “thread” that joins through (using a cubic spline) all the log-
returns that we obtain for that company in each Price Risk Region and the x-axis scale tends to allocate
“gainers” to the right, and “losers” to the left, using the distribution that is developed in the region, by
the data.

“
We notice that there tend to be more gainers in the “high-priced” low risk tolerance region, the stock
price, SP>SF, the price of risk, and that “gainers” and “losers” are more or less equally distributed in
the “lowpriced” high risk tolerance region, SP<SF. There also tends to be more and better investment
opportunities in the “high-priced” low risk tolerance region, whereas the high risk tolerance region
appears a “trader's delight” rife with sure profits only in micro-arbitrage, agency, and transaction costs.
The NASDAQ 100 (2000-2009) The Spectrum of Risk and Uncertainty
Just, the One Rule: It's in our portfolio(s) if, and only if, the stock price, SP>SF, the price

“
Then, looking at the S&P 500 - (2000-2009) And Price of Risk Gives You Odds, 2.06:1.10 To Win.
Always, just the One Rule: It's in our portfolio(s) if, and only if, the stock price, SP>SF, the price
The models repeat with these results consistently appearing, always portfolios result with that same
tendency demonstrating, the tendency for their achieving a ratio in the order of 2:1, gainers to losers.
There is much more that can be said, but this result is profound and useful, and not consistent with the
foundations from which CAPM comes. Our theory makes a clear and accountable statement about
human behaviour that is at the root of firms’ social role, creating innovation and means for productivity
and with that credit money and wealth, with no need of Walrasian or Shumpeterian equilibrium.

“
The methods of CAPM aim themselves at seeming undifferentiated Bayesian domains, those fields
with uncertainty in statements that can be made of them. According to the objectivist view, the rules of
Bayesian statistics are justified and interpreted as an extension of logic. Its value can be seen in
IBM’s“Watson.” By our taking out those firms with greater potential for gain, as we observe through
our theory, we create an effective sort of “Dutch Book” and take it out of the market into our portfolio
as these “likeables” are differentiated from the rest. CAPM can usefully concern itself with the rest.
Then, the S&P - TSX (2000-2009), And Price of Risk Gives You Odds, 2.04:1.01 To Win

“
These results show the margin of risk for these partitioned markets portfolios is never less than 2:1 in
any of the major North American markets that we have studied. These results have profound
implications for mutual fund and pension fund managers.
Implications for Mutual Fund and Pension Fund Managers.
1. An investor, who knows the price of risk, can do it himself or herself, and understand his or her
portfolio, and also yours.
2. A portfolio manager, who doesn't know the price of risk, doesn't know anything about the stock
price. “Good intentions”, “market savvy”, and forty years of doing the same thing, count for
nothing in these markets. One needs to know where we are.
3. A “Growth Fund” buys and sells stocks that don't pay dividends. That's all that one can say if
one doesn't know the price of risk. One can't even call it an “investment” and especially not, an
“investment that favours capital growth by capital gains” if one does not know the price of risk.
4. A mutual or pension fund that has stocks in both the low risk tolerance region, and the high risk
tolerance region, doesn't know what it's doing if it doesn't know the price of risk. Ask your
broker, what's the price of risk? And how is it dealt with?
5. A fund cannot be said to “protect” or “preserve” capital, or to be “conservative”, if it does not
know the price of risk, and cannot calculate the downside exposure i.e. the “gap” U=SP-SF>0.
6. An “Income Fund” buys and sells cash, bonds, and dividend paying stocks. It cannot be said to
protect or preserve capital unless the manager can state the downside risk of the capital
exposure, and has made a provision to protect it.
- Ernst Goetze 2009.
1
The physical laws which govern the system are not known well enough to predict the outcome observed John Arbuthnot, Of the Laws of
Chance, 1692,
2
James Tobin, Liquidity Preference as Behavior Towards Risk, Review of Economic Studies, 1958, and William F. Sharpe, Capital Asset
Prices with and without negative holdings, The Nobel Foundation, 1990, and Harry M. Markowitz, Portfolio Selection, Journal of
Finance, 1952. This work is further informed by Verne H. Atrill, How All Economies Work, Principles and Applications of Objective
Economics, 1979, and Ronald H. Coase, The Firm, the Market and the Law, U of Chicago Press, 1990, and James Tobin, Money and
Finance in the Macro-Economic Process, The Nobel Foundation, 1981. This work is otherwise an original and unpublished work of the
author.
3
E. Goetze, The Price of Risk and Enduring Price Arbitrage in the Capital Markets, 2009. Available from the author.
4
It's well-known that the “market price of risk” cannot be calculated within the equity markets only.
5
Bloomberg – August 6, 2009 - “I’m surprised they’d do it this early,” Brian McGill, senior analyst at Janney Montgomery Scott LLC in
Philadelphia, said of Hyatt’s timing. “While hotel stocks have performed well these last two or three weeks, investors will be sceptical of
the industry’s fundamentals.”, or “It makes me angry, but it also throws up a lot of question marks,” said Ian Nakamoto, director of
research at MacDougall MacDougall & MacTier Inc., which manages about $3 billion, including Manulife and Sun Life. “This is
definitely out of left field.” (regarding Manulife which cut its dividend by 50% even after promising that it wouldn't have to).
6
The Price Change Volatility Range[-0.5,1.0] is on the y-axis. The x-axis is scaled as -½ logab = -½ log(b)/log(a) where b is the
logarithm of the product of all the positive returns (SP/SP1, SP>SP1) in any quarter (and is therefore greater than one), and a is the
logarithm of the product of all the negative returns (SP/SP1, SP<SP1) in the same quarter (and is therefore less than one). The same scale
calculation is used in the Dow charts (with respect to those data).

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