!pip install quandl
!pip install fbprophet
!pip install plotly
from stocker import Stocker
# MSFT Stocker Initialized. Data covers 1986-03-13 to 2018-01-16.
microsoft = Stocker('MSFT')
MSFT Stocker Initialized. Data covers 1986-03-13 00:00:00 to 2018-03-27 00:00:00.
# Stock is an attribute of the microsoft object
stock_history = microsoft.stock
stock_history.head()
# A method (function) requires parentheses
microsoft.plot_stock()
Maximum Adj. Close = 96.77 on 2018-03-12 00:00:00.
Minimum Adj. Close = 0.06 on 1986-03-24 00:00:00.
Current Adj. Close = 89.47 on 2018-03-27 00:00:00.
microsoft.plot_stock(start_date = '2000-01-03', end_date = '2018-01-16', stats = ['Daily Change', 'Adj. Volume'], plot_type='pct')
Maximum Daily Change = 2.08 on 2008-10-13 00:00:00.
Minimum Daily Change = -3.34 on 2017-12-04 00:00:00.
Current Daily Change = -5.47 on 2018-03-27 00:00:00.
Maximum Adj. Volume = 591052200.00 on 2006-04-28 00:00:00.
Minimum Adj. Volume = 7425503.00 on 2017-11-24 00:00:00.
Current Adj. Volume = 53704562.00 on 2018-03-27 00:00:00.
microsoft.buy_and_hold(start_date='1986-03-13', end_date='2018-01-16', nshares=100)
MSFT Total buy and hold profit from 1986-03-13 to 2018-01-16 for 100 shares = $8829.11
model, model_data = microsoft.create_prophet_model()
model.plot_components(model_data)
plt.show()
print(microsoft.weekly_seasonality)
microsoft.weekly_seasonality = True
print(microsoft.weekly_seasonality)
False
True
microsoft.changepoint_date_analysis()
Changepoints sorted by slope rate of change (2nd derivative):
Date Adj. Close delta
410 2016-09-08 55.811396 -1.378093
338 2016-05-26 50.113453 1.116720
217 2015-12-02 52.572008 -0.882359
458 2016-11-15 57.589819 0.603127
48 2015-04-02 37.612590 0.442776
microsoft.changepoint_date_analysis(search = 'Microsoft profit')
Top Related Queries:
query value
0 microsoft non profit 100
1 microsoft office 60
2 apple profit 40
3 microsoft 365 40
4 apple 35
Rising Related Queries:
query value
0 apple stock 170
1 microsoft 365 130
2 apple profit 50
microsoft.changepoint_date_analysis(search = 'Microsoft Office')
Top Related Queries:
query value
0 microsoft office download 100
1 microsoft office 2010 90
2 office 2010 85
3 microsoft office 2013 75
4 office 2013 70
Rising Related Queries:
query value
0 microsoft office 2016 key 80300
1 office 2016 73200
2 download microsoft office 2016 72150
3 microsoft office 2016 mac 69350
4 microsoft office 2016 67650
model, future = microsoft.create_prophet_model(days=180)
Predicted Price on 2018-07-21 = $102.40