setting_constants_CombPurgedKfoldCV.py

# Set data source
data = data_ohlcv
data_index = data.index

# Select train data
X = data.drop(['label_barrier'], axis = 1)
X.drop(X.tail(t_final).index,inplace = True)

# Select test data
y = data[['label_barrier']]
y.reindex(data_index)
y = y[:-t_final]
y = y.squeeze()

# Prediction and evalution times
t1_ = data.index

# recall that we are holding our position for 10 days
# normally t1 is important is there events such as stop losses, or take profit events
# Recall t_final from before! This is the maximum of a box!!

# prediction time is moment of observationxticklabels
prediction_times = pd.Series(t1_[:-t_final], index = X.index)

# evaluation time is moment of evaluation event
evaluation_times = pd.Series(t1_[t_final:], index = X.index)