price = df.squeeze()
#print(price.head())
#print(price.index)
Target = Stocker(price, name=sid)
#Target.changepoint_prior_validation(start_date ='2015-12-03',end_date ='2018-12-21',changepoint_priors = [0.3,0.4,0.45,0.5,0.6])
#Target.plot_stock()
#原始參數預測
#model, model_data = Target.create_prophet_model(days=10)
#原始參數回測
#Target.evaluate_prediction()
#Target.changepoint_prior_analysis(changepoint_priors=[0.001, 0.05, 0.1, 0.2])
#Target.changepoint_prior_validation(start_date='2015-01-07', end_date='2018-12-21', changepoint_priors=[0.05,0.1,0.2,0.3,0.4])
#調整參數為0.4
Target.changepoint_prior_scale = 0.1
#Target.changepoint_prior_scale = 0.6
#修改後回測
Target.evaluate_prediction()
#修改後參數預測
Target.predict_future(days=30)
Target.predict_future(days=90)
model, model_data = Target.create_prophet_model(days=60)
#Target.evaluate_prediction(start_date='2017-12-15', end_date='2018-12-17', nshares=1000)
model, model_data = amazon.create_prophet_model(days=90)
amazon.evaluate_prediction()
amazon.changepoint_prior_analysis(changepoint_priors=[0.001, 0.05, 0.1, 0.2])
amazon.changepoint_prior_validation(start_date='2016-01-04',
end_date='2017-01-03',
changepoint_priors=[0.001, 0.05, 0.1, 0.2])
amazon.changepoint_prior_validation(
start_date='2016-01-04',
end_date='2017-01-03',
changepoint_priors=[0.15, 0.2, 0.25, 0.4, 0.5, 0.6])
amazon.changepoint_prior_scale = 0.5
amazon.evaluate_prediction()
amazon.weekly_seasonality = True
amazon.evaluate_prediction()
amazon.changepoint_prior_scale = 0.5
amazon.weekly_seasonality = True
amazon.evaluate_prediction(nshares=1000)
amazon.evaluate_prediction(start_date='2008-01-03',
end_date='2009-01-05',
nshares=1000)
