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From an article made by BNP-Paribas it seems that we can have better representation with Heikin Ashi if we made the following modified Heikin-Ashi candlesticks as follows:
a. haOpen, haHigh and haLow according to Dan Valcu formulas.
b. haClose is calculated first according to the formula (Open+Close)/2+(((Close-Open)/(High-Low))*ABS((Close-Open)/2)), then smoothed with a 2 days (bars) trader adaptive moving average (could be a 3-period T3 moving average or a 2-period Kaufman moving average).
{_T3Average
By Bob Fulks, modified by Alex Matulich 4/2003
The T3 Average is essentially a low-pass filter, as are the
traditional moving average and exponential moving average. The T3
Average, however, exhibits a steeper rolloff, resulting in better
filtering of high-frequency noise while better preserving the
low-frequency components of a time series.
This function is an EasyLanguage version of the algorithm described
in the January 1998 issue of TASC, p57, "Smoothing Techniques for
More Accurate Signals" by Tim Tillson. It is translated from
the MetaStock code presented in the article. The function allows
a variable length as input.
The variable b (also called "Hot") is a damping coefficient. The
suggested value of b is 0.7, but this value slightly amplifies
low-frequency components. b=0.5 seems better for having a flat
response at low frequencies. A smaller value of b will result in
too much attenuation of low frequencies.
The Length parameter is divided by two to make the T3 Average's lag
equivalent to the lag of the traditional moving averages. This way
you can use the T3 Average as a drop-in replacement for Average or
xAverage, and get the same lag but better noise filtering.
The variable "b" is substituted for the variable "a" used in the
article since "a" is a reserved word.
}
{_T3Average
By Bob Fulks, modified by Alex Matulich 4/2003
The T3 Average is essentially a low-pass filter, as are the
traditional moving average and exponential moving average. The T3
Average, however, exhibits a steeper rolloff, resulting in better
filtering of high-frequency noise while better preserving the
low-frequency components of a time series.
This function is an EasyLanguage version of the algorithm described
in the January 1998 issue of TASC, p57, "Smoothing Techniques for
More Accurate Signals" by Tim Tillson. It is translated from
the MetaStock code presented in the article. The function allows
a variable length as input.
The variable b (also called "Hot") is a damping coefficient. The
suggested value of b is 0.7, but this value slightly amplifies
low-frequency components. b=0.5 seems better for having a flat
response at low frequencies. A smaller value of b will result in
too much attenuation of low frequencies.
The Length parameter is divided by two to make the T3 Average's lag
equivalent to the lag of the traditional moving averages. This way
you can use the T3 Average as a drop-in replacement for Average or
xAverage, and get the same lag but better noise filtering.
The variable "b" is substituted for the variable "a" used in the
article since "a" is a reserved word.
}
great indicator very nice work
it wotrks even on trhe 1 minute
can we make a signal when the color turn from red to blue and vice vers
pls see the attached chart of gbp of today
great work guys
great indicator very nice work
it wotrks even on trhe 1 minute
can we make a signal when the color turn from red to blue and vice vers
pls see the attached chart of gbp of today
great work guys
sorry guys i hate to sound stupid but could anyone please explain in simple terms what the indicator is doing. Also Bunder, do you mind giving us a link to the BNP Paribas article. Thanks.
Wahomeron