Brad,
I think you’re right about the stationarity stuff. Anyway, I didn’t
want to hold up geostatistics as particularly having any direct relevance to
trading. It has its detractors in any case, who hold it to be the greatest work
of evil since Mein Kampf (miners can also be rather fanatical sometimes!). I just
wanted to point out that statistics is not just practiced by politicians and beardy-weirdy
university types. Real people can use it too…!
As long as they understand it of course, which is another matter
entirely.
I like Ehler’s work a lot but I must say that I’m gutted to
hear he is not a trader and, to boot, rumour that he may not even have a
doctorate. And as for this Fisher guy? But now I’m concerned…I’ve
heard that there were also some Ancient Greek mathematicians who spent more
time philosophising about the area of a circle and the methods of calculating a
mean value than they did trading Soybean futures. So maybe I should ditch the
moving averages too?!
From:
Metastockusers@xxxxxxxxxxxxxxx [mailto:Metastockusers@xxxxxxxxxxxxxxx] On Behalf Of bradulrich33
Sent: Saturday, July 02, 2005 8:39
PM
To: Metastockusers@xxxxxxxxxxxxxxx
Subject: [Metastockusers] Re:
Stationarity and Real World application of statistics
Yes, some peeople seem to think holy grail for some reason when you
mention Dr. Ehlers or signal processing
techniques. I don't ever
remember him saying that. His stuff is meant
to:
1.) Smooth data with less lag time through the use
of filters designed
for signal processing.
2.) Look for and quickly measure cycles in the
data. Sometimes there
are cycles, sometimes there are not.
3.) Transform the very un-gaussian distribution of
price data to a
more gaussian distribution. (TradeStats!!! I
like that term) in order
to make more realistic, but obviously not perfect,
measurments of
statistical extremes. Many people ignore this VERY
important fact when
trying to apply statistics to price data.
Price data has almost the
exact opposite of a gaussian distribution.
All of these are applied to real measured data,
and do not make
assumptions about future data. These are
referred to as causal
filters, as opposed to non-causal filters which
require data from
ahead of the measured point to create the filter.
Only one of Dr. Ehlers techniques, the Sinewave
indicator, attempts to
use a non-causal filter, in this case, he assumes
the the cycle phase
will exist as it does now for another few bars,
and advanced a measure
of this phase in order to make a prediction.
You are right, you cannot assume that the cycle
and phase will stay
the same in the future...You just have to make a
measurement with as
little lag as possible, and sometimes make the
assumption that they
will stay the same, or at least in the general
vicinity.
It seems as though the Stationarity principle can
be applied to cycle
and phase the same as it can to mean and
variance???
There are ways of measuring cycle and phase in
price data the same as
there are ways of measuring mean and variance,
both require a bit of
lag of course, but that does not make them
unusable. In fact, Ehlers'
methods of measuring cycle and phase are very responsive.
Everyone
acknowledges that both are simply measurements of
previous activity,
and not necessarily an indication of future
activity.
I am by no means an expert on the subject, but I
think the idea of
Stationality applies mainly to the ideas in Signal
theory regarding
sampling and reconstruction of signals, which is
not what we are doing
here. We are borrowing some techniques
related to the field to let us
make a more "informed" model, but there
are still many assumptions left.
That being said, there are still limiting
assumptions, and thus
improvements that can be made on top of Ehlers'
stuff given a general
understanding of the reasoning behind his
ideas. Non of these
improvements will come close to the theoretical
holy grail, but they
will remove a few false signals, and they will get
you in a bar-or-two
earlier on some decisions.
People should not look at his techniques as
alternatives to most
others. I have found the best results come
from using his stuff with
many other techniques that make improvements upon
"traditional"
indicators and techniques.
Thanks,
Brad Ulrich
www.thedml.com
tecto put is shortly
--- In Metastockusers@xxxxxxxxxxxxxxx,
"teclogeo" <teclogeo@xxxx> wrote:
> >Engineers agree with Mark Twain: there
are lies, damn lies, and
then there
> is statistics
>
>
>
> Err.sorry, but that is a slightly misplaced
quote. Yes, Mark Twain
said it
> and yes it can be true when statistics are
deliberately used to mislead
> people as in the way politicians regularly
use them. But engineers.?
I know
> you are one, but I would like to venture a
bit of personal
experience that
> may persuade you and others interested in how
statistics are regularly
> applied in a Real World application that you
may not have considered
before
> now. Perhaps that may then help you shed a
more favourable light on
the way
> stats are applied in the world of trading.
>
>
>
> In my previous life I was a geologist working
for a large mining
company. My
> claim to fame in that area is that I was on the
(small) team that was
> responsible for one of the more significant
gold discoveries of
recent years
> (for those interested, the Geita deposit in
Tanzania.now belonging to
> Anglogold-Ashanti). So, the point here is
that I have some experience in
> using statistical modelling.namely in the
practical application of
> "geostatistics".
>
>
>
> Geostats is nothing fancy.it's just the name
given by geologists to the
> practice of determining the size and internal
grade distribution of
an ore
> body using statistical methods. Basically one
has a limited data set of
> samples from drill holes and uses that to
come up with a 3-D model
of the
> ore body and the distribution of metal within
that body.and then to put
> levels of statistical confidence in that model.
Those levels of
confidence
> determine (usually within industrial
standards) how much more, if any,
> drilling is required to satisfy the *mining
engineers* that what you
have is
> not just a mineral deposit but an ore body
(the former is just metal
in the
> ground, whereas the latter can actually be
mined economically).
>
>
>
> Mining engineers know that this is only a
model. They know that it
is not
> 100% fact (as the only way to determine that
is to actually mine the
thing).
> They know the statistical confidence levels
and therefore they know that
> there are likely to be some errors in the
model. This means that
when the
> miners actually come to take the gold out of
the ground there will
be less
> in some places and (more pleasantly) more in
others. And yet, look
at what
> happens.capital flows, mines get built,
people get employed, dirt gets
> shifted, metal comes out of the ground. And
all that hangs on a few
> statistical inferences made by a bunch of
Neanderthal geologists.
Not bad,
> eh?
>
>
>
> So there is no question of "lying".
To do so would involve not only
gross
> professional negligence on behalf of the
geologist, but it would
mean that
> everything that else that normally follows
would fall apart.usually long
> after all the capital has been spent and the
people have been
employed, i.e.
> when it's far too late. Also, in the case of
deliberate scams like
Bre-X,
> the use of geostatistical "lies"
can affect the whole industry.
>
>
>
> Now, with all that said, you might be
surprised to find that the
principle
> of stationarity is relaxed almost to the
point of irrelevance in
> geostatistics. Nature is a wonderful thing,
but it rarely conforms
to simple
> mathematical models and so, skipping over the
jargon, we basically
find that
> we have to make some pretty sizeable
assumptions and generalisations
when
> coming up with the models. Are we lying when
we "bend the rules" so?
I don't
> think so.we are not agreeing with Mark Twain
at all. He was implying, I
> think, that statistics are determined and
then manipulated for an
ulterior
> motive. That is different from honestly
recognising, discussing and then
> trying to work around the limitations of the
practice.
>
>
>
> All this has direct implications to the world
of trading. I've
already gone
> on too much so I'll only say now that you can
draw two direct parallels
> between geostats and "trading
stats" (Tradstats??!!). One is that
there is a
> known quantity.the drill hole data is dirt
already taken out of the
ground
> and analysed - this compares with the
historical data set in
trading. The
> second is that there is an unknown quantity
that you want to
estimate, or
> model.the very sizeable un-mined bits of the
deposit between the drill
> holes(!) and the future data in trading. The
only problem I can think of
> there is to do with continuity. The drill
hole data is not spatially
> continuous in 3D, whereas the time-series
trading data is. Oh well,
that's
> not relevant.what I'm trying to say is that you
should not confuse
> statistical modelling with any sort of
"holy grail". Perfection does not
> exist when dealing with models, as any
experienced mining engineer
will tell
> you.but that doesn't mean in any way that a
good model will not help in
> getting the job done. And engineering is,
after all, about getting
the job
> done.
>
>
>
> Hope that's helped open your mind a bit?!
>
>
>
>
>
> _____
>
> From: Metastockusers@xxxxxxxxxxxxxxx
[mailto:Metastockusers@xxxxxxxxxxxxxxx]
> On Behalf Of jawjahtek
> Sent: Friday, July 01, 2005 11:07 PM
> To: Metastockusers@xxxxxxxxxxxxxxx
> Subject: [Metastockusers] Re: New Adaptive
Tools for Metastock
>
>
>
> Random question and comment:
>
> 1. Superfragalist, have you tried CSI data
(assuming you use EOD data)?
> There is no such thing as a good data
provider, but at least CSI is
> honest and up front about continually
cleaning their data AND telling
> users what errors were made. If you use
intraday data, I can see how
> you have been hosed. The only option that I
have seen is to match the
> professional set ups: use multiple intraday
suppliers.
>
> 2. While I wish the developers of the new
adaptive tools all of the
> luck in the world, I don't believe that ANY
application of
> Communications (Signal) theory can be
successfully applied to price
> data. In academic terms, these theories
require Stationarity. In
> layman's terms, this means that the theories
require a constant range
> of frequencies (cycle) and phases (time lag).
Unfortunately, historical
> price data tells us nothing about the future
prices' frequency and
> phase.
>
> Statistician's definition of Stationarity: a
statistical name for
> expressing degrees of invariance in the
properties of random functions;
> it refers to the statistical model, and not
to the data. Most commonly
> used to indicate invariance in the mean and
variance, but also in the
> variance of first differences.
>
> I am an Electrical Engineer. Although EEs use
the concept of
> Stationarity, its meaning is slighly
different in engineering.
> Engineers agree with Mark Twain: there are
lies, damn lies, and then
> there is statistics.
>
> I will try the free trial, but I already know
that the holy grail does
> not (and cannot) exist.
>
>
> jawjahtek
>
>
>
>
> --- In Metastockusers@xxxxxxxxxxxxxxx,
"superfragalist" <jackolso@xxxx>
> wrote:
> > Well, I've got all those IVs hung off my
wallet also. Reuters at least
> > cleans their data, which esignal doesn't
do. In fact, esignal can't
> > even adjust for splits.
> >
> > I didn't know netflix had DVDs on
trading. I've just been trading DVDs
> > with them.
> >
>
>
>
>
>
>
> _____
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