Hello !
I'd like to know how to load 2 kind of data such as 'stocks' and 'index' in order to work with Multi-backtesting_ml.
def load_data(period):
stocks = qndata.stocks.load_ndx_data(tail=period)
index = qndata.index.load_data(tail=period)
return stocks, index
weights = qnbt.backtest_ml(
load_data = load_data,
train = train_model,
predict = predict_weights,
train_period = 15 *365, # the data length for training in calendar days
retrain_interval = 1 *365, # how often we have to retrain models (calendar days)
retrain_interval_after_submit = 1, # how often retrain models after submission during evaluation (calendar days)
predict_each_day = False, # Is it necessary to call prediction for every day during backtesting?
# Set it to True if you suspect that get_features is looking forward.
competition_type = "stocks_nasdaq100", # competition type
lookback_period = 365, # how many calendar days are needed by the predict function to generate the output
start_date = "2006-01-01", # backtest start date
analyze = True,
build_plots = True # do you need the chart?
)
What should I do ?
Best regards,