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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@xxxxxxxxx> 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
--- 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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