print(key)
print(future_contract.to_dict()[key])
print('\n')
futures_position_value = get_pricing(future_contract, start_date = '2017-01-01', end_date = '2018-01-01', fields = 'price')
futures_position_value.name = futures_position_value.name.symbol
futures_position_value.plot()
plt.title('NG Futures Price')
plt.xlabel('Date')
plt.ylabel('Price');
# ## Historical Data
print history.__doc__
# In[88]:
ngf18 = future_contract
ngf18_data = history(ngf18,
fields=['price', 'open_price', 'high', 'low', 'close_price', 'volume', 'contract'],
frequency='daily',
start_date='2017-06-01',
end_date='2017-08-01')
ngf18_data.head()
# Notice the 4th of July!
ngf18_data['volume'].plot(kind='bar')
# ## Comparison of Different Maturity Dates
ng_contracts = symbols(['NGF17', 'NGG17', 'NGH17', 'NGJ17', 'NGK17', 'NGM17'])
ng_consecutive_contract_volume = history(ng_contracts,
fields='volume',
frequency='daily',
start_date='2016-01-01',
end_date='2017-08-01')
ng_consecutive_contract_volume.plot()
ng_consecutive_contract_volume.plot(xlim=['2016-10-01','2017-08-01'])
# Trading activity jumps from one contract to the next. Transitions happen just prior to the delivery date of each contract.
]
Prices = []
Correlation = []
Order = []
# In[ ]:
#Pulls data for all futures listed above and curve fits them via Math filter we created
for x in FutureTicker:
y = continuous_future(x, roll='volume')
y = history(y,
fields='price',
frequency='daily',
start='2018-10-21',
end='2018-10-21')
x = pd.Series(
scipy.signal.savgol_filter(y, 31, 2, 0, 1.0, -1, 'interp', 0.0))
Prices.append(x)
# In[40]:
#Finds every possible Correlation between futures
for i in range(0, len(FutureTicker) - 1):
for x in range(i + 1, len(FutureTicker)):
Correlation.append((Prices[i].corr(Prices[x])))
from quantopian.research.experimental import continuous_future
import scipy
import numpy
numpy.arange
import matplotlib.pyplot as plt
# In[3]:
WTI = continuous_future( 'CL', roll = 'volume' ) #Crude Oil Futures
WTI = history(
WTI,
fields='price',
frequency='daily',
start='2008-08-31',
end='2018-08-31'
)
Corn = continuous_future( 'CN' , roll = 'volume') #Corn Futures
Corn = history(
Corn,
fields='price',
frequency='daily',
start='2008-08-31',
end='2018-08-31'
)
"""
SAMPLE COMMODODITIES, INDEX, CURRENCY (FOREX) FUTURES ARE ALL AVAILABLE ON QUANTOPIAN
"""
future_contract = symbols('NGF20') # NG (Natural Gas) F (January Future) 20 (2020)
for key in future_contract.to_dict():
print("{} -> {}".format(key, future_contract.to_dict()[key]))
futures_position_value = get_pricing(future_contract, start_date='2017-01-01', end_date='2018-01-01')
futures_position_value.name = futures_position_value.name.symbol
futures_position_value.plot()
# NOW, LET'S GET SOME HISTORICAL DATA
ngf20 = future_contract # RESET A NEW SHORTER VARIABLE :')
ngf20_data = history(ngf20, fields=['price', 'open_price', 'high', 'low', 'close_price', 'volume', 'contract'],
frequency='daily', start_date='2017-06-01', end_date='2017-08-01')
ngf20_data.head(); ngf20_data.plot() # WORK WITH THIS DATAFRAME HOWEVER
# F - January, G - February, ...
ng_contracts = symbols(['NGF18', 'NGG18', 'NGH18', 'NGJ18', 'NGK18', 'NGM18'])
# FIRST, WORKING WITH CONSECUTIVE FUTURES
ng_consecutive_contract_volume = history(ng_contracts, fields='volume', frequency='daily',
start_date='2017-08-01', end_date='2017-08-01')
ng_consecutive_contract_volume.plot() # ANOTHER DATAFRAME :)
# VOLUME BEING TRADED INCREASES FUTURE'S PRICE AS IT ALSO INCREASES
# BUT ALSO, AS THE FUTURE'S MATURITY DATE APPROACHES, IT'S PRICE BEGINS TO REDUCE GRADUALLY
# NOW, WORKING WITH CONTINUOUS FUTURES
ng_continuous = continuous_future('NG', offset=0, roll='volume', adjustment='mul') # / 'add' / 'nul'
ng_continuous_active = history(ng_continuous, fields=['contract', 'price', 'volume'],
frequency='daily', start_date='2018-10-01', end_date='2019-08-01')
from quantopian.research.experimental import continuous_future
import scipy
import numpy
numpy.arange
import matplotlib.pyplot as plt
# In[11]:
WTI = continuous_future( 'CL', roll = 'volume' ) #Crude Oil Futures
WTI = history(
WTI,
fields='price',
frequency='daily',
start='2014-04-01',
end='2015-01-29'
)
Corn = continuous_future( 'CN' , roll = 'volume') #Corn Futures
Corn = history(
Corn,
fields='price',
frequency='daily',
start='2014-10-01',
end='2015-05-29'
)
Corn2 = continuous_future( 'CN' , roll = 'volume') #Corn Futures