Re: News: Demises Part Of Economic Life Cycle

From: John Conover <>
Subject: Re: News: Demises Part Of Economic Life Cycle
Date: 25 Dec 2000 21:16:51 -0000

So, using the immediate past as an tautology/example, the dot-com
"bubble" started in about mid 1995; and one should have moved money
around in one's investment portfolio such that any investments in the
dot-coms would be in those companies with a larger market share, like
Amazon, Yahoo!, etc.

However, when the dot-com industry was 4 years old, (i.e., when 0.5 =
1 / sqrt (4),) the Shannon probability for any of these companies
continuing success would have dropped to 0.5, (meaning that the
oligopoly shake out was starting,) and all investments in the dot-coms
should have been curtailed, (i.e., by about mid 1999, the investment
in the dot-coms would have been decreased to zero.)


BTW, by serendipity, the dot-com "bubble" turned out to be very
typical.  It does not always work out that way-the 1 / sqrt (t)
probability distribution for the duration that companies in an
industrial market has very flat tails; and for that reason, one can
not make money, in the long run, investing in industrial "bubbles."
However, it is the optimal game strategy, (and there are certain
inefficiencies in market "bubbles" that can be exploited by the
initiated,) and the chances of losing in the long run are small.

John Conover writes:
> BTW, there is kind of an interesting side bar to this. It can be
> shown, (using game-theoretic methods,) that the natural evolution of
> industries is to start as a panoply, and evolve into an oligopoly.
> During the transition from panoply to oligopoly, the surviving
> companies seem to be chosen by lottery, and the chances of any given
> company surviving is proportional to its market share-as in the
> so-called "gambler's ruin." (What this means is that a company has a
> chance of winning-or a Shannon Entropy, or probability-of C / M, where
> M is the total market, and C, the market share of the company; the
> duration that the company will be in existence will be proportional to
> CM - C^2.)
> Note that such a scenario will have the characteristics of a Brownian
> fractal-and one can not make money iterating investments in the likes.
> As an industry matures into an oligopoly-the ultimate destiny of any
> industry-it can be shown that none of the companies will be profitable
> in the long run.
>         John
> BTW, note how closely game theory, information theory, probability
> theory, and fractal science are tied together in the above; the
> Shannon probability of a company succeeding, P, is C / M, meaning that
> one should not invest in companies that have less than a 50% market
> share; and when one does, the fraction of one's net wealth to be
> invested would be 2P - 1. The chances of any company lasting t many
> years will be proportional to 1 / sqrt (t), too; and that is another
> Shannon probability that has to be handled with the 2P - 1 scenario.
> John Conover writes:
> >
> > Kind of an interesting perspective on the dot-com shakeout ...
> >
> >       John
> >
> > BTW, the analogy to the car biz is not unique. A similar shakeout
> > occurred for semiconductors, TV sets, Radios, CBs, video games, etc.
> > In these techno-bubbles, only about 1 in 10 survive; and the one that
> > does pays the investors about 10X their initial investment-so its
> > not a wise gamble, (fun, maybe, but not wise,) for an investor, on
> > average, (i.e., one win of 10X and nine losses of 1X, puts one right
> > back where one started-its like betting on a fair tossed coin, in the
> > long run.)
> >
> > So, who makes all the money? The founder's of the companies that
> > survived-who only invested sweat.
> >
> > Although the dot-coms have fallen from favor, the industry
> > has generated more billionaires than any other industry in history.
> >


John Conover,,

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