This function is an Pine version of the moving average described in
the January, 1998 issue of S&C magazine, p.57, "Smoothing Techniques
for More Accurate Signals", by Tim Tillson. It is translated from the
MetaStock code presented in the article. The function uses a version
of the XAverage, written by me, which allows variables as inputs.
The most popular method of interpreting a moving average is to compare
the relationship between a moving average of the security's price with
the security's price itself (or between several moving averages).
the January, 1998 issue of S&C magazine, p.57, "Smoothing Techniques
for More Accurate Signals", by Tim Tillson. It is translated from the
MetaStock code presented in the article. The function uses a version
of the XAverage, written by me, which allows variables as inputs.
The most popular method of interpreting a moving average is to compare
the relationship between a moving average of the security's price with
the security's price itself (or between several moving averages).
//////////////////////////////////////////////////////////// // Copyright by HPotter v1.0 21/05/2014 // This function is an Pine version of the moving average described in // the January, 1998 issue of S&C magazine, p.57, "Smoothing Techniques // for More Accurate Signals", by Tim Tillson. It is translated from the // MetaStock code presented in the article. The function uses a version // of the XAverage, written by me, which allows variables as inputs. // The most popular method of interpreting a moving average is to compare // the relationship between a moving average of the security's price with // the security's price itself (or between several moving averages). //////////////////////////////////////////////////////////// study(title="T3 3 Averages", shorttitle="T3") Length = input(5, minval=1) hline(0, color=gray, linestyle=line) xPrice = close xe1 = ema(xPrice, Length) xe2 = ema(xe1, Length) xe3 = ema(xe2, Length) xe4 = ema(xe3, Length) xe5 = ema(xe4, Length) xe6 = ema(xe5, Length) b = 0.7 c1 = -b*b*b c2 = 3*b*b+3*b*b*b c3 = -6*b*b-3*b-3*b*b*b c4 = 1+3*b+b*b*b+3*b*b nT3Average = c1 * xe6 + c2 * xe5 + c3 * xe4 + c4 * xe3 nSlope = nT3Average - nT3Average[2] Res1 = nSlope Res2 = nSlope[1] Res3 = nT3Average - nT3Average[1] plot(iff(Res2 > 10 or Res3 > 10,na, Res1), color=blue, title="Slope") plot(iff(Res2 > 10 or Res3 > 10,na, Res2), color=red, title="Slope2") plot(iff(Res2 > 10 or Res3 > 10,na, Res3), color=green, title="Slope1per")
