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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@xxxxxxxxxxxxxxx [mailto:realtraders@xxxxxxxxxxxxxxx] On Behalf
Of Bob Pardo at Mindspring
Sent: Tuesday, December 09, 2008 9:50 AM
To: realtraders@xxxxxxxxxxxxxxx
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@xxxxxxxxxxxxxxx [mailto:realtraders@xxxxxxxxxxxxxxx] On Behalf
Of Stan Rubenstein
Sent: Monday, December 08, 2008 9:33 PM
To: realtraders@xxxxxxxxxxxxxxx
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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