def benchmark():
from time import clock, time
da = DataAccess('./data')
da.empty_dirs(delete=False)
print ('Directory empty: Download and save 5 stocks')
t1, t2 = clock(), time()
symbols = ["AAPL","GLD","GOOG","SPY","XOM"]
start_date = datetime(2008, 1, 1)
end_date = datetime(2009, 12, 31)
fields = "Close"
da.get_data(symbols, start_date, end_date, fields)
t1_f, t2_f = clock(), time()
print (" ", t1_f - t1, t2_f - t2)
print ('Load 5 stocks from .csv')
t1, t2 = clock(), time()
symbols = ["AAPL","GLD","GOOG","SPY","XOM"]
start_date = datetime(2008, 1, 1)
end_date = datetime(2009, 12, 31)
fields = "Close"
da.get_data(symbols, start_date, end_date, fields, useCache=False)
t1_f, t2_f = clock(), time()
print (" ", t1_f - t1, t2_f - t2)
print ('Load 5 stocks from serialized')
t1, t2 = clock(), time()
symbols = ["AAPL","GLD","GOOG","SPY","XOM"]
start_date = datetime(2008, 1, 1)
end_date = datetime(2009, 12, 31)
fields = "Close"
da.get_data(symbols, start_date, end_date, fields, useCache=True)
t1_f, t2_f = clock(), time()
print (" ", t1_f - t1, t2_f - t2)
def delete_data():
self_dir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
DataAccess.path = os.path.join(self_dir, 'data')
data_access = DataAccess()
data_access.empty_dirs()
def delete_data():
self_dir = os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe())))
DataAccess.path = os.path.join(self_dir, 'data')
data_access = DataAccess()
data_access.empty_dirs()
class PastEventTest(unittest.TestCase):
def setUp0(self):
self.da = DataAccess("./data")
self.da.empty_dirs()
self.setUp1()
def setUp1(self):
self.evt = PastEvent("./data")
self.evt.symbol = "AAPL"
self.evt.market = "^gspc"
self.evt.lookback_days = 10
self.evt.lookforward_days = 10
self.evt.estimation_period = 252
self.evt.date = datetime(2009, 1, 5)
self.evt.run()
def suite(self):
suite = unittest.TestSuite()
suite.addTest(PastEventTest("test_success"))
return suite
def test_success(self):
self.setUp1()
# Test: Series names
self.assertEquals(self.evt.er.name, "Expected Return")
self.assertEquals(self.evt.ar.name, "Abnormal Return")
self.assertEquals(self.evt.car.name, "Cumulative Abnormal Return")
self.assertEquals(self.evt.t_test.name, "t test")
self.assertEquals(self.evt.prob.name, "Probability")
# Test: Index values
self.assertEquals(self.evt.er.index[0].to_pydatetime(), datetime(2008, 12, 18))
self.assertEquals(self.evt.er.index[-1].to_pydatetime(), datetime(2009, 1, 20))
# Test: Values
ans_er = [
"-0.0212234",
"0.00230225",
"-0.0184308",
"-0.0100507",
"0.00507867",
"0.00466393",
"-0.0043450",
"0.02326106",
"0.01325643",
"0.03029057",
"-0.0051219",
"0.00706623",
"-0.0298596",
"0.00275149",
"-0.0213603",
"-0.0225914",
"0.00115150",
"-0.0332277",
"0.00073280",
"0.00681676",
"-0.0521229",
]
ans_ar = [
"0.02416528",
"0.00412824",
"-0.0288732",
"0.01746335",
"-0.0206124",
"0.00435256",
"0.01375131",
"-0.0269885",
"-0.0241298",
"0.03294819",
"0.04736761",
"-0.0235995",
"0.00827612",
"0.01576086",
"-0.0014955",
"0.00142864",
"-0.0118479",
"0.00608256",
"-0.0235514",
"-0.0193999",
"0.00188397",
]
ans_car = [
"0.02416528",
"0.02829353",
"-0.0005797",
"0.01688362",
"-0.0037288",
"0.00062375",
"0.01437507",
"-0.0126134",
"-0.0367432",
"-0.0037950",
"0.04357256",
"0.01997299",
"0.02824911",
"0.04400998",
"0.04251447",
"0.04394312",
"0.03209521",
"0.03817778",
"0.01462634",
"-0.0047736",
"-0.0028896",
]
ans_t_test = [
"0.93826998",
"1.09855833",
"-0.0225090",
"0.65554389",
"-0.1447789",
"0.02421877",
"0.55814377",
"-0.4897438",
"-1.4266368",
"-0.1473509",
"1.69180043",
"0.77549544",
"1.09683395",
"1.70878414",
"1.65071766",
"1.70618799",
"1.24616708",
"1.48233614",
"0.56789979",
"-0.1853454",
"-0.1121960",
]
ans_prob = [
"0.82594716",
"0.86401961",
"0.49102096",
"0.74394118",
"0.44244271",
"0.50966094",
"0.71162689",
"0.31215756",
"0.07684230",
"0.44142751",
"0.95465798",
"0.78097652",
"0.86364300",
"0.95625452",
"0.95060188",
"0.95601345",
"0.89364846",
"0.93087456",
"0.71494849",
"0.42647903",
"0.45533397",
]
self.assertEquals([str(x)[0:10] for x in self.evt.er.values.tolist()], ans_er)
self.assertEquals([str(x)[0:10] for x in self.evt.ar.values.tolist()], ans_ar)
self.assertEquals([str(x)[0:10] for x in self.evt.car.values.tolist()], ans_car)
self.assertEquals([str(x)[0:10] for x in self.evt.t_test.values.tolist()], ans_t_test)
self.assertEquals([str(x)[0:10] for x in self.evt.prob.values.tolist()], ans_prob)
# Test: Compare results of equal events
evt2 = PastEvent("./data")
evt2.symbol = "AAPL"
evt2.market = "^gspc"
evt2.lookback_days = 10
evt2.lookforward_days = 10
evt2.estimation_period = 252
evt2.date = datetime(2009, 1, 5)
evt2.run()
self.assertListEqual(
[str(x)[0:10] for x in self.evt.er.values.tolist()], [str(x)[0:10] for x in evt2.er.values.tolist()]
)
self.assertEqual(
[str(x)[0:10] for x in self.evt.ar.values.tolist()], [str(x)[0:10] for x in evt2.ar.values.tolist()]
)
self.assertListEqual(
[str(x)[0:10] for x in self.evt.car.values.tolist()], [str(x)[0:10] for x in evt2.car.values.tolist()]
)
self.assertListEqual(
[str(x)[0:10] for x in self.evt.t_test.values.tolist()], [str(x)[0:10] for x in evt2.t_test.values.tolist()]
)
self.assertListEqual(
[str(x)[0:10] for x in self.evt.prob.values.tolist()], [str(x)[0:10] for x in evt2.prob.values.tolist()]
)