Merhaba ;
bir önceki sorumda ayrı pencereki indikatörlerden kastım fiyat grafiği üzerinde gösterim yapmayıp kendi pencerisnii ayrı açan indikatörlerden bahsediyorum
örneğin indikatör içindeki çizgilerin keişimiyle emir vermesini sağlayan formülünün linkini bu soruya benzer soru altında paylaşmıssınız ama orda fiyat grafiği üzerinde ekleme yapan most indikatöründe anlatıyor bizim halledemediğimiz taraf ise ayrı pencerede açan örneğin stochasticSlow gibi indikatörlerin içindeki K ve D çizgisine ben vermidiğiniz örnekte gösterdiği gibi K çizgisi D çizgisini yukarı kesince al emir göndersin seçeneğini seçtiğim zaman çizgilerin kesişimiyle emir göndermek yerine iki çizgininde kafasını yukarı kırmasını bekliyor
yani K çizgisi yukarı kırmış 1. koşul sağlanmış ama D çizgiside yukarı kırma koşulunu bekliyor bu sorunu nasıl halledebilirim
<img alt="" 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