"Bill Reid" <hormelfree@[EMAIL PROTECTED]
> wrote in message
news:1L9Ej.45512$cQ1.39493@[EMAIL PROTECTED]
>
>
> So you're day-trading a single "rocket ****p", probably a low-priced
> issue. You've already got a ton of volatility inherent in the stock,
which
> tends to negate any market out-performance of your short-term results
> statistically...
It's a short term system. The idea is to start with a system at
equilibrium
that's been suddenly disturbed. It's the /reaction/ to the disturbance
that's being studied for emergent patterns, in complexity science.
And it's the edge behavior that's interesting, and where universal
patterns are found.
>
> Maybe you should study just a little bit of physics, look up
> the name "Heisenberg", or any type of game theory dealing
> with pari-mutuel payoffs, or poker (your chaotic boundary is
> the result of what in poker is called players "going on tilt").
Here though we're dealing only with far from equilibrium states, and
properties of collective behavior where history matters.
In stock charts an edge state takes the form of a panic sell
or panic buy. Where a small perturbation over time cascades
and begins accelerating and converging on one or the other limits
in possible behavior. As with a genetic algorithm searching
for function limits. It's only a matter of time before the system
slams into its own practical boundaries when the disturbance
is of the proper character. Giving a very reliable bottom or top.
This presents situations where pretty much everyone that
will sell has, or might buy has. The future then is pretty easy
to predict.
When either limit is found, the near future is always obvious
to everyone. System behavior then becomes detached from
system specifics.
So the buyers and sellers, at the edge, suddenly agree and
flock together in a very predictable way. At least until the
energy gathered in the drive from equilibrium is gone.
This is an attempt to use the general properties of self-organized
complex adaptive systems as a guide to determine the
chart variable values which cause /any/ system to seek out and
converge upon it's own limits in possible behavior.
/Uncertainty/ drives systems to the edge and generates
universal behavior. To predict real world systems we must
learn to /quantify/ ...uncertainty. This is what I'm attempting
and will try to show below.
It turns out that when the primary driving variables of
any system are in the range where they give the very /least/
amount of predictability, and all at the same time, the system
begins hill-climbing, evolving and converging towards the edge.
When a variable is within this miminum, it is said to be in the
complex realm. As far from either simple endpoints as
possible, so that one can't tell which extreme dominates.
So that one can't gain any predictive value at all due
to the equal distance from either certain endpoint.
So, the mathematical task to define under what conditions any
system will display universal behavior, is simply to define the
primary system variables, then define the complex range for each.
Then draw the chart from that.
The three primary variables of a chart pattern are of course
price, volume and the transient length. Which is the length
the disturbance driving the system from equilibrium lasts.
Defining the complex realm is highly subjective, as is
complexity science in general. But that isn't an obstacle
to reliability.
All complex dynamic systems can be defined in terms
of their static, dynamic and chaotic attractor behavior.
Pattern/transient length.
The complex realm is simply the time period that's as far from
either extreme as possible as observed in practice.
One extreme as observed in time frames is the day-traders
which operate loosely speaking in /minutes or hours/.
The opposite extreme or limit in time frame is of course
the longs, which operate again loosely in periods of
/months and years/. So a complex time period would
be neither and both, in between.../days or weeks/.
More than a day, less than a month.
Ten to twenty day pattern/transient lengths define the complex
range or pattern length with the least ability to inform the
future.
Initial Price
One extreme is the penny stocks, the other is the blue chips.
Defining where blue chips begin is rather subjective.
But the price which typically reflects stability is sufficient.
Defining the penney stocks is easier of course, let the
lower extreme be the point at which stocks are booted
off the exchange, say $2. And the opposite extreme to
be over $10 or $20 is good enough. These boundaries
are defined much like ****, you know 'em when you
see 'em.
So the disturbance should take place on a stock that is
at the upper range of the complex realm, say $10
or $20. And the distirbance should end near the
lower range of the complex realm, say $5 or $10.
Initial Volume
Again, the high and low extremes are subjective and arbitrary.
Doesn't matter. Complex volume would not be, oh, 20 million
shares a day, or a hundred thousand. But somewhere
in between such obvious extremes.
Those are the necesary initial conditions.
Then comes the disturbance.
It must ...also...be a complex disturbance.
Neither so weak or so strong that it's future
effect is obvious. But it must also be of such
a magnitude so that one can't tell if it will quickly
die off or totally destroy.
The opposite extremes in effect on price of any
disturbance would be of course a price that
changes little over time, or changes all at once
in a single spike down. So, of course, a complex
rate of change of price would be again...in between.
A scale independent 45% degree angle or slope of
minus 1.
Final volume
Again, between little change and too much like
an order of magnitdue. The final volume, when
arriving at the edge, should be roughly double
initial.
Final price.
Again, a complex change in price would be between
no change and zero. While not falling out of the complex
range.
A fall of minus one half, 50%, that stops somewhere in the
lower ****tion of the complex range.
ALL variables, initial, final and total change must
display the maximum amount of ...uncertainty.
They must all be complex. Then and only then
the system behavior becomes universal.
Of course all parameters are loosely defined.
They draw a very recognizable pattern that doesn't
really need much accuracy.
If you've read this far, thanks. If you have chart options
for ...20 days, as with Quote Tracker, then look at the
chart patterns of these four tickers from the last few days.
As you can see, they all meet the parameters rather well.
There are plenty of them every week as you can see below.
Too many I couldn't decide which to play as usual.
Look at bxxx, smbl, rso, novn. (20 day charts)
A child could make ten percent a week.
And they all do the same thing. Independent of company
details, problems or whatever.
Like any nice thunderstorm, the phase change or reversal
is announced when the system finally converges on the edge
with a nice loud clap of thunder (volume spike), followed
by a brief rain-shower. Then the pattern is over. There
is no real predictability beyond that point.
> Nature shows us how to wreck the friggin' SuperDome, after
> the weatherman "predicts" the storm will not hit New Orleans...but
> Lorenz told us 50 years ago why we couldn't predict nature with
> anywhere near 100% accuracy...riiiiiight?!??!!
The weathermen predicted Katrina well enough.
No one listened.
Who needs 100% accuracy. We need to know how to design
systems with the properties of naturally evolving systems.
And let the system find its own way to the ideal.
Science needs to get off the obsesssion on how to
predict based on part properties, on deriving fundamental
law from the simplest the universe has to offer.
And begin writing new fundamental laws based on the
most /complex/ the universe has to offer....life.
The Great Mistake of modern science is to think we can
unravel reality by starting with the simplest, the physical
universe, in order to later understand the most complex
such as life.
It's the other way 'round. Life....Darwin...the abstract properties
of biological evolution show us the fundamental laws of order
governing the entire universe. We can only truly understand
the physical universe through Darwin.
>
> ---
> William Ernest Reid
> Post count: 976
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