Machine Learning, Deep Learning, Cryptocurrency Investment, Algorithmic Trading, Neural Networks.
pipdiff_percentage = 0.01 # 1% (0.01) of the asset's price for TP SLTPRatio = 2.0 # pipdiff/Ratio gives SL def mytarget(barsupfront, df1): length = len(df1) high = list(df1['High']) low = list(df1['Low']) close = list(df1['Close']) open_ = list(df1['Open']) # Renamed 'open' to 'open_' to avoid