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Brett,
You asked the same question November 14, 2004 on the Metastockusers
group. Have you been looking all this time?
The standard error bands are built in to Metastock. This comes from
the help file.
When displaying Standard Error Bands, you are prompted to enter the
number of periods in the bands and the number of standard errors
between the bands and the linear regression line (see Standard Error
Bands). Mr. Andersen recommends default values of "21" for the
number of periods, a 3-day simple moving average for the smoothing,
and "2" standard errors. He also notes that very short time frames
tend to produce unreliable results.
MetaStock plots Standard Error Bands on the security's prices or
indicator. These interpretational comments refer to bands on the
security's closing price.
Because the spacing between Standard Error Bands is based on the
standard error of the security, the bands widen when the volatility
around the current trend increases, and contract when volatility
around the current trend decreases.
Since Standard Error Bands are statistically based, other
statistical indicators such as r-squared, Standard Error, Linear
Regression, etc. work well for trade confirmation.
Mr. Andersen notes the following characteristics of Standard Error
Bands.
· Tight bands are an indication of a strong trend.
· Prices tend to bounce between the bands when the bands are
wide.
· Tight bands followed by a widening of the bands may indicate
the exhaustion of a trend and a possible reversal.
· When the bands reverse direction after an exhausted trend,
prices tend to move in the direction of the bands.
· The r-squared indicator works well in combination with
Standard Error Bands. A high r-squared value combined with tight
bands confirms a strong trend. A low r-squared value combined with
wide bands confirms that prices are consolidating.
Hope this helps,
Preston
--- In equismetastock@xxxxxxxxxxxxxxx, Brett Sinclair
<brett_j_sinclair@xxx> wrote:
>
> Is anyone familiar enough with Kirschenbaum bands to code them in
Metastock?
>
> For the curious, their description is as follows:
> 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.
>
>
> They are similar to, but behave quite differently from Bollinger
Bands.
>
> Thanks, Brett
>
>
> [Non-text portions of this message have been removed]
>
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