I searched for a efs study for this indicator and couldn't find it. It is available for Metastock, Neuroshell, Omnitrader,and Tradestation though. I would love to see it coded if someone is up to it.
Here is a description...
Paul Kirshenbaum, a money manager and mathematician with a Ph.D. in economics from NYU, submitted this rather unique trading band which is “de-trended.” The Kirshenbaum Bands are similar to Bollinger bands in usage, however are widely considered to be superior.
Kirshenbaum Bands are similar to Bollinger Bands (see BOL-C) in that they measure market volatility. However, rather than use standard deviation of a moving average for band width, they use the standard error of linear regression lines of the close. This has the effect of measuring volatility around the current trend, instead of measuring volatility for changes in trend.
Construction:
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. Mr. Kirshenbaum recommends a value of 1.75.
Trading System:
This system trades when the price moves outside the K-Bands with the close inside the band.
KBA-C: Kirshenbaum Bands
Kirshenbaum Bands yield excellent volatility bands. Compare this systems with the Bollinger Bands. Use Kirshenbaum bands to measure volatility around a trend, and Bollinger Bands to measure changes in trend.
Here is a description...
Paul Kirshenbaum, a money manager and mathematician with a Ph.D. in economics from NYU, submitted this rather unique trading band which is “de-trended.” The Kirshenbaum Bands are similar to Bollinger bands in usage, however are widely considered to be superior.
Kirshenbaum Bands are similar to Bollinger Bands (see BOL-C) in that they measure market volatility. However, rather than use standard deviation of a moving average for band width, they use the standard error of linear regression lines of the close. This has the effect of measuring volatility around the current trend, instead of measuring volatility for changes in trend.
Construction:
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. Mr. Kirshenbaum recommends a value of 1.75.
Trading System:
This system trades when the price moves outside the K-Bands with the close inside the band.
KBA-C: Kirshenbaum Bands
Kirshenbaum Bands yield excellent volatility bands. Compare this systems with the Bollinger Bands. Use Kirshenbaum bands to measure volatility around a trend, and Bollinger Bands to measure changes in trend.
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