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I've been working on Dawn Balton Smith's triple moving
average,
which is a five, fifteen, thirty simple moving average based on the
close. Now one characteristic of this set of averages is that when
the averages are equidistant from each other or if they are
clustered, this is supposed to be a strong indication for a trend
reversal.
I'm trying to write a Metastock exploration to find when the
averages are both clustered or equidistant.
So far I have set each average in column A, B, and C respectively
ie. Mov(close,5,s) in column A, Mov(close,15,s) in column B and Mov
(close,30,s) in column C.
In the filters column I have ColB-ColA=ColC-ColB.
This works but the problem is that the averages are calculated to
four decimal places, which is too exact and the exploration
doesn't
come out with enough results. I need to adjust it to get say a 0.5%
margin for error, which would give the averages a couple of ticks
leeway.
Does anyone have any idea how I can loosen up the criteria a bit to
get more results out of the exploration. Any tips would be greatly
appreciated.
Regards, Tom
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