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This looks to me like another name for Standard Error Bands.
You'll find it in MetaStock's Indicator QuickList.
jose '-)
--- In Metastockusers@xxxxxxxxxxxxxxx, Brett Sinclair
<brett_j_sinclair@xxxx> wrote:
> Hello All --
>
> I would like to have a Metastock Indicator called Kirshenbaum Bands,
which are similar to Bollingert Bands. However, I can't program them.
but have the algorithm.
> Perhaps someone, in the group can do this and contribute the effort.
>
> The algorithm is:
> Kirshenbaum Bands are constructed as follows:
> Calculate a P-Period Exponential Moving Average of the data based on
the close.
> Then, for each bar, calculate the L-Period linear regression line,
using
> today's close as the endpoint of the line.
> (Note: The term "linear regression" is the same as a "least squares"
or
> "best fit" line in some textbooks.)
> Calculate d1, d2, d3, .. dL as the distance from the line to the
close on
> each bar which was used to derive the line.
> That is, di = Distance from Regression Line to each bar's close.
> Calculate the average of the squared errors:
> AE = (d12 + d22 + d32 + .. + dN2) / L
> Standard Error (Se) is the square root of this value:
> Se = square root of AE
> Then, if N = Number of Standard Errors, band width is:
> BW = N * SE
> Add and subtract the band width from the Exponential Moving Average
to arrive
> at today's value for the upper and lower bands.
> Parameters:
> Periods (P):
> The period used in the Exponential Moving Average calculation.
> Linear Regression Periods (L):
> The period used in constructing the lines for Linear Regression.
> Deviations (N):
> Number of deviations used. That is, the Standard Error value can be
> multiplied by a factor to expand the bands.
>
> Thanks in advance,
> Brett
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