def test_oneEventPerEquity(self):
'''
Equities: AMD
Function: went_below(3)
Period: 2008-1-1 -> 2009-12-31
Tests: oneEventPerEquity=True and oneEventPerEquity=False
'''
self.setUpDataAccess()
evtf = EventFinder()
evtf.symbols = ['AMD']
evtf.start_date = datetime(2008, 1, 1)
evtf.end_date = datetime(2009, 12, 31)
evtf.condition = SampleConditions.went_below(3)
evtf.search(oneEventPerEquity=True)
# Test: number of events found = 1
self.assertEqual(evtf.num_events, 1)
# Test: date of the event is 2008-10-27
date1 = evtf.matrix['AMD'][evtf.matrix['AMD'] == 1].index[0].to_pydatetime()
self.assertEqual(date1, datetime(2008,10,27))
# Test: oneEventPerEquity=False
evtf.search(oneEventPerEquity=False)
# Test: number of events found = 2
self.assertEqual(evtf.num_events, 2)
# Test: date of the events
date1 = evtf.matrix['AMD'][evtf.matrix['AMD'] == 1].index[0].to_pydatetime()
date2 = evtf.matrix['AMD'][evtf.matrix['AMD'] == 1].index[1].to_pydatetime()
self.assertEqual(date1, datetime(2008,10,27))
self.assertEqual(date2, datetime(2008,11,11))
def test_window(self):
'''
Two events on two different equities
Tests
-----
1. Expected returns
2. Abnormal returns
3. Cumulative abnormal returns
4. Mean of ER, AR, CAR
'''
# Set Up
self.setUpDataAccess()
evt_fin = EventFinder()
evt_fin.symbols = ['AMD', 'CBG']
evt_fin.start_date = datetime(2008, 1, 1)
evt_fin.end_date = datetime(2009, 12, 31)
evt_fin.condition = SampleConditions.went_below(3)
evt_fin.search()
mul_evt = MultipleEvents()
mul_evt.list = evt_fin.list
mul_evt.market = 'SPY'
mul_evt.lookback_days = 20
mul_evt.lookforward_days = 20
mul_evt.estimation_period = 200
mul_evt.run()
self_dir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
tests = ['MultipleEvents_window_1.csv']
tests = [os.path.join(self_dir, 'docs', test) for test in tests]
for test_file in tests:
# Set up
solution = pd.read_csv(test_file).set_index('index')
# Test 1
sol_er = solution[solution.columns[0:2]]
sol_er.columns = mul_evt.er.columns
sol_er.columns.name = 'Expected return'
self.assertEqual(mul_evt.er, sol_er)
# Test 2
sol_ar = solution[solution.columns[3:5]]
sol_ar.columns = mul_evt.ar.columns
sol_ar.columns.name = 'Abnormal return'
self.assertEqual(mul_evt.ar, sol_ar)
# Test 3
sol_car = solution[solution.columns[6:8]]
sol_car.columns = mul_evt.car.columns
sol_car.columns.name = 'Cum abnormal return'
self.assertEqual(mul_evt.car, sol_car)
# Test 4
self.assertEqual(mul_evt.mean_er, solution['Mean ER'])
self.assertEqual(mul_evt.mean_ar, solution['Mean AR'])
self.assertEqual(mul_evt.mean_car, solution['Mean CAR'])
from datetime import datetime from finance.events import SampleConditions from finance.events import EventFinder # from finance.utils import DataAccess # DataAccess.path = 'data' evtf = EventFinder() evtf.symbols = ['AMD', 'CBG', 'AAPL'] evtf.start_date = datetime(2008, 1, 1) evtf.end_date = datetime(2010, 12, 31) evtf.condition = SampleConditions.went_below(10) evtf.search(useCache=False) print(evtf.num_events) print(evtf.list)
label = self.mean_ar.name
elif which == "er":
y = self.mean_er.values
yerr = self.std_er.values
label = self.mean_er.name
errorfill(x, y, yerr, label=label)
if __name__ == "__main__":
from datetime import datetime
import matplotlib.pyplot as plt
from finance.events import EventFinder
from finance.events import SampleConditions
evtf = EventFinder()
evtf.symbols = ["AMD", "CBG"]
evtf.start_date = datetime(2008, 1, 1)
evtf.end_date = datetime(2009, 12, 31)
evtf.condition = SampleConditions.went_below(3)
evtf.search()
mevt = MultipleEvents()
mevt.list = evtf.list
mevt.market = "SPY"
mevt.lookback_days = 20
mevt.lookforward_days = 20
mevt.estimation_period = 200
mevt.run()
mevt.plot("car")
plt.legend()
label = self.mean_ar.name
elif which == 'er':
y = self.mean_er.values
yerr = self.std_er.values
label = self.mean_er.name
errorfill(x, y, yerr, label=label)
if __name__ == '__main__':
from datetime import datetime
import matplotlib.pyplot as plt
from finance.events import EventFinder
from finance.events import SampleConditions
evtf = EventFinder()
evtf.symbols = ['AMD', 'CBG']
evtf.start_date = datetime(2008, 1, 1)
evtf.end_date = datetime(2009, 12, 31)
evtf.condition = SampleConditions.went_below(3)
evtf.search()
mevt = MultipleEvents()
mevt.list = evtf.list
mevt.market = 'SPY'
mevt.lookback_days = 20
mevt.lookforward_days = 20
mevt.estimation_period = 200
mevt.run()
mevt.plot('car')
plt.legend()
yerr = self.std_ar.values
label = self.mean_ar.name
elif which == 'er':
y = self.mean_er.values
yerr = self.std_er.values
label = self.mean_er.name
errorfill(x, y, yerr, label=label)
if __name__ == '__main__':
from datetime import datetime
import matplotlib.pyplot as plt
from finance.events import EventFinder
from finance.events import SampleConditions
evtf = EventFinder()
evtf.symbols = ['AMD', 'CBG']
evtf.start_date = datetime(2008, 1, 1)
evtf.end_date = datetime(2009, 12, 31)
evtf.condition = SampleConditions.went_below(3)
evtf.search()
mevt = MultipleEvents()
mevt.list = evtf.list
mevt.market = 'SPY'
mevt.lookback_days = 20
mevt.lookforward_days = 20
mevt.estimation_period = 200
mevt.run()
print(mevt.mean_car)
#mevt.plot('car')
from datetime import datetime from finance.events import SampleConditions from finance.events import EventFinder # from finance.utils import DataAccess # DataAccess.path = 'data' evtf = EventFinder() evtf.symbols = ["AMD", "CBG", "AAPL"] evtf.start_date = datetime(2008, 1, 1) evtf.end_date = datetime(2010, 12, 31) evtf.condition = SampleConditions.went_below(10) evtf.search(useCache=False) print(evtf.num_events) print(evtf.list)
from datetime import datetime
from finance.events import SampleConditions
from finance.events import EventFinder
# from finance.utils import DataAccess
# DataAccess.path = 'data'
evtf = EventFinder()
evtf.symbols = ['AMD', 'CBG', 'AAPL']
evtf.start_date = datetime(2008, 1, 1)
evtf.end_date = datetime(2010, 12, 31)
evtf.condition = SampleConditions.went_below(10)
evtf.search(useCache=False)
print("Number of events: {0}".format(evtf.num_events))
print(evtf.list)