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In 2006, Armstrong had been in prison 7 years? If he had had
the money in 2000 it would have been a snap to pay the Clinton administration
$50M or so for a pardon (even though there hadn’t been a conviction) ala Mark
Rich et al. Seems like something else must be going on here because there hasn’t
been a conviction of substance…. and were there one the max single conviction
would only bring 5 years (most Fed multiple white collar convictions from what
I’ve seen run concurrently except in Enron) with 4 years minimum active. And
contempt of court running more than the active portion of an assumed
conviction? Hmmm Someone’s mad enough he will never get out of prison.
** using new investor funds to repay earlier investors, leaving
the losers with losses of about $700 million**
Sounds like Social Security “trust” funds; the ultimate Ponzi
Scheme.
Jim
From:
realtraders@xxxxxxxxxxxxxxx [mailto:realtraders@xxxxxxxxxxxxxxx] On Behalf
Of Howard Bernstein
Sent: Tuesday, December 09, 2008 12:29 PM
To: realtraders@xxxxxxxxxxxxxxx
Subject: Re: [RT] A note on Forecasting / Mandelbrot
MARTIN
ARMSTRONG PLEADS GUILTY IN
MULTI-BILLION-DOLLAR PRINCETON ECONOMICS SCHEME
By Stephanie
Ayres
24 April 2007
New York, New York
The US
Attorney's office in New York announced on August 17, 2006 that Martin A. Armstrong, a former currency
trader and head of the now-defunct Princeton Economics International, pleaded
guilty to conspiracy to commit securities fraud, commodities fraud and wire
fraud in connection with a large-scale international ponzi scheme operated in
the 1990s.
Armstrong
sold some $3 billion of worthless promissory notes called Princeton Notes
between 1992 and 1999, using new investor funds to repay earlier investors,
leaving the losers with losses of about $700 million when the scheme collapsed.
In January 2002 Republic Securities, a New York broker-dealer which had allowed
Armstrong to
maintain accounts for use in his scheme, pleaded guilty to criminal charges of
conspiracy and securities fraud and was sentenced to pay about $569 million of
restitution.
I see that they have given him a pencil and paper to write. I wonder
when he gets out of prison?
-----Original Message-----
From: JHP <jan4123@xxxxxxxxxxxxx>
To: realtraders@xxxxxxxxxxxxxxx
Sent: Tue, 9 Dec 2008 11:39 am
Subject: Re: Re: Re:[RT] A note on Forecasting / Mandelbrot
-----
Original Message -----
Sent: Tuesday, December
09, 2008 7:28 AM
Subject: Re: Re: Re:[RT] A
note on Forecasting / Mandelbrot
I
am a big fan of Armstrong. Can you provide a reference to the essay you noted?
-----
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=2 0the 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 inte
resting people. Wish I had a tenth of their insights.
From: realtraders@xxxxxxxxxxxxxxx [mailto:realtraders@yahoogroups.com] 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.
From: realtraders@xxxxxxxxxxxxxxx [mailto:realtraders@yahoogroups.com] 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 the20kind 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 Me ssage -----
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 O rder 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./
div>
----- 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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