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Thank you Jan.
Jim
----- Original Message -----
Sent: Tuesday, December 09, 2008 8:39
AM
Subject: Re: Re: Re:[RT] A note on
Forecasting / Mandelbrot
Here it is
Jan Philipp
----- Original Message -----
Sent: Tuesday, December 09, 2008 7:28
AM
Subject: Re: Re: Re:[RT] A note on
Forecasting / Mandelbrot
Jim,
I am a big fan of Armstrong. Can you provide a
reference to the essay you noted?
Jim
----- Original Message -----
Sent: Tuesday, December 09, 2008 7:23
AM
Subject: RE: Re: Re:[RT] A note on
Forecasting / Mandelbrot
I?m not a
statistician, but what my little accounting mind derived from reading
Mandelbrot was not so much that he envisioned a ?solution? as he saw chaos
that could only be interpreted in fractal generation. What was so
interesting and has been profitable to me in degrees I never thought
possible, was his assault on Black Sholes. His proof via the
frequency of ?long tailed events? in the market entirely laid waste to the
idea that a normal distribution could be applied to the market. And
further, that distantly out of the money options were dangerously
UNDERPRICED. Well, those 9000 contracts $.14-.21 October 38 QQQQ
puts that I purchased in exactly the first 90 minutes of trading on
September 19, 2008 became $8+ intrinsic before they expired in
October. How many bags is that? No, I didn?t hold out for $8
intrinsic, but it was a big number. Mandelbrot, obviously, rules in
my book.
Conversely, when VIX spikes, it?s
not time to buy premium. The majority still rely on Black
Sholes. Who needs ?the solution? when you can see the fallacies on
which others are writing options contracts?
Martin
Armstrong has a very similar view of the non linearity of the market.
He sees multiple cycles converging to provide the ?perfect storm? or
?deadly wave? with chaos ordered by ?self generating? fractals or
?schema?. His latest essay (?It?s Just Time? 10/8/08), which I
believe is authentic, is amazing. I?m into my tenth reading, at
least, of it (err, the early chapters).
Very,
very interesting people. Wish I had a tenth of their insights.
From: realtraders@yahoogroups.com
[mailto:realtraders@yahoogroups.com] On Behalf Of Bob
Pardo at Mindspring
Sent: Tuesday, December 09, 2008 9:50
AM
To: realtraders@yahoogroups.com
Subject:
RE: Re: Re:[RT] A note on Forecasting /
Mandelbrot
I don?t think
?Mandelbrot conclusion has many conditions attached to it? is an
accurate conclusion.
The fractal distribution has qualities that make it
almost totally unlike the distributions used in classical statistics.
However, since it is rather obvious that billions of
dollars have been earned using these ?flawed statistics? and variants
thereof (see D. E. Shaw and Renaissance Technologies) it is also obvious
that the entire matter is amazingly complex.
Since all of these firms are secretive almost to a
paranoid degree, a determination of the actual technologies they employ
will require a major piece of detective work.
As Sergey indicates, the devil is in the
details.
Regards,
Bob Pardo
From: realtraders@yahoogroups.com
[mailto:realtraders@yahoogroups.com] On Behalf Of Stan
Rubenstein
Sent: Monday, December 08, 2008 9:33 PM
To:
realtraders@yahoogroups.com
Subject: Re: Re: Re:[RT] A
note on Forecasting
Is it possible that Mandelbrot conclusion has many
conditions attached to it not spelled
out in your comment that has a bearing on
it?
Also isn't it the "log normal" distribution that's
applicable to financial stock returns
----- Original Message
-----
Sent:
Monday, December 08, 2008 10:03 PM
Subject: Re: Re: Re:[RT] A note on
Forecasting
These are too
general statements about too general subject. The most important is
in details. Here I agree with you.
And I use the
models with a lot of added conditions. The complexity of some model is
not a problem for the kind of research that I
do.
As to
Prediction Company and their technologies, I have some questions
for you as a professional.
What exactly
did you use from Chaos Theory:
1) Non
parametric statistics? If so, how did you use
it?
Information for
those who are not familiar with
it:
Mandelbrot
found that the normal distribution is not working for financial data. It
means that we cannot apply classical statistics for financial
data.
For
example, traditional calculation of profit of
some trading system, or Black-Scholes option pricing
model, are not applicable for the real stock market.
2) R/S
analysis? If so, how did you use it?
Information for
those who are not familiar with
it:
----- Original
Message -----
Sent:
Monday, December 08, 2008 8:15 PM
Subject: [Bulk] Re: Re:[RT] A note on
Forecasting
All trading systems
are based on some assumption about market behavior. In simple form a
trading system says "If A occurs then B follows."An another example If
an oscillator reverses in oversold territory, buy next bar at x
price.We all know that such a system may have remarkable results over
a given time period however in the long run it will fail because it
does not accurately describe the way markets work. Markets can trend
for long periods, yielding many false signals and failed trades.
However, suppose we add another condition to the model that describes
when the extended trend will end. Now we have a model that more
accurately describes how markets work and should prove more reliable
over longer periods. If we add enough conditions to accurately
describe market behavior under a number of market scenarios, then we
have a model that will have consistent returns over time and markets.
And the statistics will be a realistic expectation of
performance. This , of course, is the dream of all system
builders.
You may make the case
that markets are so dynamic that one can never detail conditions
enough to create a model that will yield reliable performance over all
time frames but I beg to differ. Both Mandelbrot and Peters agree that
markets may be predictable in the short run. I, in fact use the work
of both in my market model. And the Prediction Company certainly
succeeded, did it not?
----- Original
Message -----
Sent: Monday, December 08, 2008 2:23
PM
Subject: Re:[RT] A note on
Forecasting
Static
cycles are not my favorite or special.
The real
question is a fundamental one: how to verify any trading strategy,
based on anything.
10 years
ago I have participated in a big research project. Its purpose was
to test and verify different trading systems based on methods of
technical analysis. Our group has found that the application of
methods of classical statistics to the stock market analysis is
an extremely dangerous thing.
Let me
explain it better on this example.
Let say we
have found a system that provides 70 winning signals from 100. The
university's course of statistics says that this fact is not
occasional with the probability of 99.5% (Chi
Square=20x20/50=400/50=8 => P=99.5%) It means that we
can assume that there is a high possibility that this system will
work well in the future as it does in the present. And somebody
may decide that the Holy Grail is found finally. But - it is not
true. Statistics of the real stock market and the market's logic are
different from this one. If the system works good enough for
100 current examples, it does not mean that it will work the same
for other samples.
Jim, I want
to emphasize that I do not name here the models that we
used for the research. My group tried different things: TA
indicators, risk/money management, arbitrage systems, then different
math models (like Spectrum, autoregression), astro cycles as
well. This problem still presents for all of
them.
I believe
that this problem is described well in these
books:
1) "The (Mis)behavior of Markets" of Benoit
Mandelbrot;
and 2) "Chaos and Order in the Capital Markets: A New
View of Cycles, Prices, and Market Volatility" of Edgar E.
Peters.
In financial analysis, we
have to work with big data samples.
PS. Jim, it
seems to me that you are mixing two different things: fixed (or
static) cycles and dominant cycles. As an example, I would not
believe if somebody states that the 20-days cycle is found that has
worked for 20 years. From another side, if somebody states that
withing the last 100 days the 20-days cycle has been found, it is
quite possible.
Next 100
days there might be some other cycle (27-days, for example). It is
closer to MESA and wavelet analysis, not to normal fixed cycles
analysis.
----- Original
Message -----
Sent: Monday, December 08, 2008 4:27
PM
Subject: [Bulk] Re: [Bulk] [RT] A note on
Forecasting
The inability of
a methodology to return reliable and consistent performance is an
indication that the underlying hypothesis is flawed. For example,
methods based on static cycles or projections based on static
cycles will have inconsistent performance over different stretches
of time because static cycles are not fundamentally correct model
of market activity.
There are
characteristics of market movement and trader psychology that do
not change over time and methods based on these will exhibit
consistent performance. be it 100 or 700
samples.
----- Original
Message -----
Sent: Monday, December 08, 2008 11:52
AM
Subject: Re: [Bulk] [RT] A note on
Forecasting
Actually, the question about financial
statistics is a tricky one. The important things there are not
only win/loss ratios, the intervals where these ratios are
calculated should be considered as well. I have had many cases
when a trading strategy worked very well for a half a year. And
then it died forever.
As an
example, see this intermediate backtesting result for huge
intraday data:
The
system provided 65% good signals (469 win./ 247 los.) during
some perios (several months).
After
that 53% only, and then 59%.
100
trades is not enough to get the reliable statistics (we use at
least 500 trades, in this example 700
trades).
One of
this forum's participants is Robert Pardo, he can comment this
better than me.
-----
Original Message -----
Sent: Monday, December 08, 2008 12:31
PM
Subject: [Bulk] [RT] A note on
Forecasting
My pivot
trading methodology depends on anticipating and trading as
close to the pivot points as
possible. My argument is that trades near the pivot points are
the lowest risk and highest reward points to trade. I operate
my trading as a business - I buy inventory and sell to
capture a minimum profit margin. I have spent most of my
trading career studying the characteristics of markets at
turning points (pivots) and constructing trading tools to
anticipate and trade near those points. These tools deliver
consistent reliability of profitable trades between 70% and
80%.
I document my
trading concepts by forward testing, not computer generated
back testing. In other words I trade the tools in real time
and record the results. For example, my latest application to
the ESZ08 has generated about 78% profitable trades on a five
minute chart over the past 6 weeks.
One of the
issues I have with the people that post forecast on this list
is that they do not provide reliability measures of their
techniques. Failed forecasts are rarely addressed and specific
application details are not provided. Consequently I usually
delete them without consideration - after all - a stopped
clock is right twice a day.
So I
recommend that anyone who posts a forecast provide the
statistics documenting the same performance of technique over
at least 100 applications. For example my techniques are good
within one bar of the forecast 70% to 80% of the time
depending on market. With that information, readers can better
judge the value of the post.
Jim
White
Pivot Research & Trading
Co.
PivotTrader.com
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