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Just a comment, std dev does not *require* a normal distro. You can
just as well calculate the std dev, using the normal formula, of any
distro, even fat tailed ones. Just like the mean can be used for many
distros, it does not depend on the distro being normal.
Maybe a weighted std dev (like value at risk calcs use) or the GARCH
model (volatility clusters) will address the problem.
Here is a weighted stddev (I think, not tested in MSFL)
Periods:=Input("Periods?",10,9999,30);
DRet:=C/Ref(C,-1)-1;
SqrRet:=DRet*DRet;
sqrt(Mov(SqrRet,Periods,E)-Power(Mov(DRet,Periods,E),2));
which is very similar to RiskMetrics' VAR formulae.
Regards
MG Ferreira
TsaTsa EOD Programmer and trading model builder
http://www.ferra4models.com
http://fun.ferra4models.com
--- In equismetastock@xxxxxxxxxxxxxxx, "TecloGeo" <teclogeo@xxxx> wrote:
> 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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> >
> >
> > _____
> >
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