import matplotlib.pyplot as plt
import statsmodels.api as sm
qb = QuantBook()
# spy = qb.AddEquity("gs")
# h1 = qb.History(qb.Securities.Keys, timedelta(days=4000), Resolution.Daily)
# h1

ES = qb.AddFuture('ES')
ES.SetFilter(timedelta(0), timedelta(60))

# history = qb.History(qb.Securities.Keys, 360, Resolution.Daily)
future_history = qb.GetFutureHistory(ES.Symbol, datetime(2020, 1,22),datetime(2020,1,23))
                                                                                 
sp500 = future_history.GetAllData()
future_history.GetExpiryDates()
# sp500.dropna(inplace = True)

# Indicator Analysis
# bbdf = qb.Indicator(BollingerBands(30, 2), spy.Symbol, 360, Resolution.Daily)
# bbdf.drop('standarddeviation', 1).plot(figsize= (16,10))

 

[datetime.datetime(2020, 3, 20, 0, 0),
datetime.datetime(2020, 6, 19, 0, 0),
datetime.datetime(2020, 9, 18, 0, 0),
datetime.datetime(2020, 12, 18, 0, 0),
datetime.datetime(2021, 3, 19, 0, 0)]
 
 

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