dc_ta
Adaptive technical indicators are importants in a non stationary market, the ability to adapt to a situation can boost the efficiency of your strategy. A lot of methods have been proposed to make technical indicators "smarters", the dominant cycle tuned indicators are one of them which are based on J.F.Ehlers theory. Here is a collections of algorithms to calculate dominant cycles. ENJOY!
Library "dc_ta"
bton()
EhlersHoDyDC()
EhlersPhAcDC()
EhlersDuDiDC()
EhlersCycPer()
EhlersCycPer2()
EhlersBPZC()
EhlersAutoPer()
EhlersHoDyDCE()
EhlersPhAcDCE()
EhlersDuDiDCE()
EhlersDFTDC()
EhlersDFTDC2()
Library "dc_ta"
bton()
EhlersHoDyDC()
EhlersPhAcDC()
EhlersDuDiDC()
EhlersCycPer()
EhlersCycPer2()
EhlersBPZC()
EhlersAutoPer()
EhlersHoDyDCE()
EhlersPhAcDCE()
EhlersDuDiDCE()
EhlersDFTDC()
EhlersDFTDC2()
Notes de version:
v2
limiting dominant output range from 1 ~ 34
limiting dominant output range from 1 ~ 34
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