This is an implementation of John Ehlers’ Adaptive Stochastic, as described in his book Rocket Science for Traders: Digital Signal Processing Applications (2001-07-20).
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// Adaptive Stochastic // Rocket Science for Traders: Digital Signal Processing Applications // 2001-07-20 John F. Ehlers Price = (high+low)/2 CycPart = .5 If BarIndex > 5 then Smooth = (4*Price + 3*Price[1] + 2*Price[2] + Price[3]) / 10 Detrender = (.0962*Smooth + .5769*Smooth[2] - .5769*Smooth[4] - .0962*Smooth[6])*(.075*Period[1] + .54) // Compute InPhase and Quadrature components Q1 = (.0962*Detrender + .5769*Detrender[2] - .5769*Detrender[4] - .0962*Detrender[6])*(.075*Period[1] + .54) I1 = Detrender[3] // Advance the phase of I1 and Q1 by 90 degrees j1 = (.0962*I1 + .5769*I1[2] - .5769*I1[4] - .0962*I1[6])*(.075*Period[1] + .54) jQ = (.0962*Q1 + .5769*Q1[2] - .5769*Q1[4] - .0962*Q1[6])*(.075*Period[1] + .54) // Phasor addition for 3 bar averaging I2 = I1 - jQ Q2 = Q1 + j1 // Smooth the I and Q components before applying the discriminator I2 = .2*I2 + .8*I2[1] Q2 = .2*Q2 + .8*Q2[1] // Homodyne Discriminator Re = I2*I2[1] + Q2*Q2[1] Im = I2*Q2[1] - Q2*I2[1] Re = .2*Re + .8*Re[1] Im = .2*Im + .8*Im[1] If Im <> 0 and Re <> 0 then Period = 360/ATAN(Im/Re) Endif If Period > 1.5*Period[1] then Period = 1.5*Period[1] Endif If Period < .67*Period[1] then Period = .67*Period[1] Endif If Period < 6 then Period = 6 Endif If Period > 50 then Period = 50 Endif Period = .2*Period + .8*Period[1] SmoothPeriod = .33*Period + .67*SmoothPeriod[1] HH = High LL = Low For count = 0 to ROUND(CycPart*SmoothPeriod) - 1 do If High[count] > HH then HH = High[count] Endif If Low[count] < LL then LL = Low[count] Endif Next If HH - LL <> 0 then Stoc = (Close - LL) / (HH - LL) Endif Endif Return Stoc as "Stochastic" |
The attached screenshot shows George Lane’s Stochastic (black) and John Ehlers’ Adaptive Stochastic (red).
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