Market prices do not have a Gaussian probability density function
as many traders think. Their probability curve is not bell-shaped.
But trader can create a nearly Gaussian PDF for prices by normalizing
them or creating a normalized indicator such as the relative strength
index and applying the Fisher transform. Such a transformed output
creates the peak swings as relatively rare events.
Fisher transform formula is: y = 0.5 * ln ((1+x)/(1-x))
The sharp turning points of these peak swings clearly and unambiguously
identify price reversals in a timely manner.
as many traders think. Their probability curve is not bell-shaped.
But trader can create a nearly Gaussian PDF for prices by normalizing
them or creating a normalized indicator such as the relative strength
index and applying the Fisher transform. Such a transformed output
creates the peak swings as relatively rare events.
Fisher transform formula is: y = 0.5 * ln ((1+x)/(1-x))
The sharp turning points of these peak swings clearly and unambiguously
identify price reversals in a timely manner.
//////////////////////////////////////////////////////////// // Copyright by HPotter v1.0 01/07/2014 // Market prices do not have a Gaussian probability density function // as many traders think. Their probability curve is not bell-shaped. // But trader can create a nearly Gaussian PDF for prices by normalizing // them or creating a normalized indicator such as the relative strength // index and applying the Fisher transform. Such a transformed output // creates the peak swings as relatively rare events. // Fisher transform formula is: y = 0.5 * ln ((1+x)/(1-x)) // The sharp turning points of these peak swings clearly and unambiguously // identify price reversals in a timely manner. //////////////////////////////////////////////////////////// study(title="Fisher Transform Indicator by Ehlers", shorttitle="Fisher Transform Indicator by Ehlers") Length = input(10, minval=1) xHL2 = hl2 xMaxH = highest(xHL2, Length) xMinL = lowest(xHL2,Length) nValue1 = 0.33 * 2 * ((xHL2 - xMinL) / (xMaxH - xMinL) - 0.5) + 0.67 * nz(nValue1[1]) nValue2 = iff(nValue1 > .99, .999, iff(nValue1 < -.99, -.999, nValue1)) nFish = 0.5 * log((1 + nValue2) / (1 - nValue2)) + 0.5 * nz(nFish[1]) plot(nFish, color=green, title="Fisher") plot(nz(nFish[1]), color=red, title="Trigger")