All this talk
of standard deviation reminds me of Ehler’s use of the Fisher transform. As
he states - the transform “changes the probability density function (PDF)
of any waveform so the transformed output has an approximately Gaussian PDF”.
The reason that there is huge lag for the st dev on sharp moves is because normal
price behaviour does not fit a nice bell-shaped curve - sharp moves are often in
the “fat tail” territory of the PDF (i.e. the low probability/high
impact events at the extremes) – whereas st dev relies on a purely normal
distribution.
Can these fat
tail events be smoothed with the Fisher transform so that st dev can be applied
more appropriately to a more normal-looking Gaussian PDF? The Fisher transform
has been used to great effect on prices and oscillators…just wondering if
there has been any application of it in the respect of volatility measures? Not
aware that Ehler himself has done any work on volatility…maybe there’s
a good mathematical reason for this?
From:
equismetastock@xxxxxxxxxxxxxxx
[mailto:equismetastock@xxxxxxxxxxxxxxx]
On Behalf Of mgf_za_1999
Sent: Tuesday, May 17, 2005 6:55
AM
To: equismetastock@xxxxxxxxxxxxxxx
Subject: Re: [EquisMetaStock
Group] ATR-based volatility
The following study, which, please note, is very theoretical, looks at
volatility in a lot of markets.
http://www.monep.fr/pub/clive.pdf
Just skip all the math stuff and go to page 60 if
you are interested
in this. There they start tabulating results
of different techniques
and comment on the performance.
Regards
MG Ferreira
TsaTsa EOD Programmer and trading model builder
http://www.ferra4models.com
http://fun.ferra4models.com
--- In equismetastock@xxxxxxxxxxxxxxx,
"dr.torque" <drtorque@xxxx> wrote:
> I think we should define how to measure the
volatility in a specific
market
> based on the volatility characteristics of
that market and what type
of an
> indicator would best fit for measuring that
relevant type of volatility.
>
> Jose's
suggestion of ATR is one of the very best but I suppose we
are not
> looking for average very good solutions
here.. I totally agree that
there
> seem to be some major problems for an average
trader, but we are not
trying
> to be an average trader as well.
>
> maybe we can get to somewhere interesting
brainstorming on this topic..
>
> regards,
>
>
>
> Dr. Torque
>
>
>
>
>
> -----Original Message-----
> From: equismetastock@xxxxxxxxxxxxxxx
[mailto:equismetastock@xxxxxxxxxxxxxxx]
> On Behalf Of Whit
> Sent: Monday, May 16, 2005 1:13 PM
> To: equismetastock@xxxxxxxxxxxxxxx
> Subject: Re: [EquisMetaStock Group] ATR-based
volatility
>
>
> Here is a related idea, picking up on this
interesting theme. That is,
> rather than using Bollinger Bands, which are
based on a StDev
function, you
> can use Keltner Channels, which are based on
ATR. For example, you
can set
> your upper and lower K-Channel bands to be 2 Average True Ranges
(over the
> past 20 bars, say) above and below the
MA. This gives a very nice
measure
> of volitility and is very helpful in
assessing an impulse move out of a
> consolidation. When price penetrates
the K-Channel after a
consolidation,
> you have good odds of an impulse move and
follow through in the
direction of
> the penetration. (I'm sorry i can't
give you the code for this -- I
am a
> Trade Station convert and just beginning to
learn MS code).
>
> Whit
>
> Jose
Silva <josesilva22@xxxx> wrote:
>
> Manuel, Andrew, staying away from
mathematical jargon if possible,
> let's concentrate on what seems to work best
on the markets.
>
> Plot and compare these two indicators below
any volatile chart:
>
> ATR(1);
>
> Stdev(C,2);
>
>
> It may be a subtle difference, but I know
which one I'd prefer.
>
> And introduce Standard deviation to a large
price gap over say, 21
> periods [Stdev(C,21)], and the *increasing
volatility* shown by Std
> Dev *after* the event, is simply wrong.
Compare to Mov(ATR(1),21,E).
>
> Again, from *my own chart observations*, my
view is that the ATR is
> probably the more natural measure of price
volatility.
>
> My observations and thoughts may not be
mathematically correct, but
> that is the way I view volatility in charts -
not as a bunch of
> abstract numbers to be manipulated
mathematically, but rather, data
> points representing mass psychology at work.
>
>
> jose '-)
> http://www.metastocktools.com
<http://www.metastocktools.com/>
>
>
>
> --- In equismetastock@xxxxxxxxxxxxxxx,
"Manuel Cabedo" <manelcabedo@x
> ...> wrote:
> >
> >> From my own chart observations, I
think that the ATR is probably
> >> the best measure of volatility.
> >
> > I don't think so, Jose.
Volatility is a kind of dispersion, and the
> > best measure of dispersion is the
standard deviation. It is a simple
> > question of statistics. With standard
deviation you can do
> > quantitative assertions about the
probability of breaking a channel,
> > for instance, or being exited of an operation
by a stop.
> >
> > Speaking of securities, I particularly
like the standard deviation
> > of daily returns. The distribution of
this quantity is not normal,
> > of course, but you can study it on a
heuristics base.
> >
> > The work of Bollinger is interesting (I
am the translator of his
> > book in Spain) because he always justifies
(or tries to.) his
> > methods from a statistical point of
view. If someone likes his
> > bands, then reading his book is a must.
> >
> > Once more, thank you, Jose. Your contributions to this forum are
> > always highly valuable (including the
one about ATR...).
> >
> >
> > Kind regards.
> >
> > Manuel
>
>
>
>
>
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