def test_adjust_purchase(self):
ohlcs = np.array([
(1216915200, 24.889999389648438, 25.450000762939453,
24.709999084472656, 25.0, 486284.0, 1216462208.0)
], dtype=Day.DTYPE)
dividends = np.array([
(1058313600, 0.0, 0.0, 0.0, 0.11999999731779099),
(1084233600, 0.20000000298023224, 0.0, 0.0, 0.09200000017881393),
(1119225600, 0.5, 0.0, 0.0, 0.10999999940395355),
(1140739200, 0.08589000254869461, 0.0, 0.0, 0.0),
(1150416000, 0.0, 0.0, 0.0, 0.07999999821186066),
(1158796800, 0.0, 0.0, 0.0, 0.18000000715255737),
(1183507200, 0.0, 0.0, 0.0, 0.11999999731779099),
(1217203200, 0.0, 0.0, 0.0, 0.2800000011920929),
(1246579200, 0.30000001192092896, 0.0, 0.0, 0.10000000149011612),
(1268611200, 0.0, 0.12999999523162842, 8.850000381469727, 0.0),
(1277942400, 0.0, 0.0, 0.0, 0.20999999344348907),
(1307664000, 0.0, 0.0, 0.0, 0.28999999165534973)
], dtype=self.dtype)
index = np.array([datetime.datetime.fromtimestamp(v) for v in ohlcs['time']],
dtype=object)
y = DataFrame.from_records(ohlcs, index=index, exclude=['time'])
y['adjclose'] = y['close']
for div in dividends:
d = Dividend(div)
d.adjust(y)
adjclose = y.xs(datetime.datetime(2008, 7, 25))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 17.28))
def test_adjust_divide_or_split(self):
#http://help.yahoo.com/kb/index?locale=en_US&page=content&y=PROD_FIN&id=SLN2311
ohlcs = np.array([
(date2unixtime(datetime.date(2003, 2, 13)), 46.99, 46.99, 46.99,
46.99, 675114.0, 758148608.0),
(date2unixtime(datetime.date(2003, 2, 14)), 48.30, 48.30, 48.30,
48.30, 675114.0, 758148608.0),
(date2unixtime(datetime.date(2003, 2, 18)), 24.96, 24.96, 24.96,
24.96, 675114.0, 758148608.0),
(date2unixtime(datetime.date(2003, 2, 19)), 24.53, 24.53, 24.53,
24.53, 675114.0, 758148608.0),
],
dtype=Day.DTYPE)
dividends = np.array(
[
(date2unixtime(datetime.date(
2003, 2, 18)), 1.0, 0.0, 0.0, 0.0), # Split 2:1
(date2unixtime(datetime.date(
2003, 2, 19)), 0.0, 0.0, 0.0, 0.08), # 0.08 cash dividend
],
dtype=self.dtype)
index = np.array(
[datetime.date.fromtimestamp(v) for v in ohlcs['time']],
dtype=object)
y = DataFrame.from_records(ohlcs, index=index, exclude=['time'])
y['adjclose'] = y['close']
for div in dividends:
d = Dividend(div)
d.adjust(y)
adjclose = y.xs(datetime.date(2003, 2, 13))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 23.42))
adjclose = y.xs(datetime.date(2003, 2, 14))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 24.07))
adjclose = y.xs(datetime.date(2003, 2, 18))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 24.88))
adjclose = y.xs(datetime.date(2003, 2, 19))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 24.53))
def test_adjust_divide_or_split(self):
#http://help.yahoo.com/kb/index?locale=en_US&page=content&y=PROD_FIN&id=SLN2311
ohlcs = np.array([
(date2unixtime(datetime.date(2003, 2, 13)),
46.99, 46.99, 46.99, 46.99, 675114.0, 758148608.0),
(date2unixtime(datetime.date(2003, 2, 14)),
48.30, 48.30, 48.30, 48.30, 675114.0, 758148608.0),
(date2unixtime(datetime.date(2003, 2, 18)),
24.96, 24.96, 24.96, 24.96, 675114.0, 758148608.0),
(date2unixtime(datetime.date(2003, 2, 19)),
24.53, 24.53, 24.53, 24.53, 675114.0, 758148608.0),
], dtype=Day.DTYPE)
dividends = np.array([
(date2unixtime(datetime.date(2003, 2, 18)),
1.0, 0.0, 0.0, 0.0), # Split 2:1
(date2unixtime(datetime.date(2003, 2, 19)),
0.0, 0.0, 0.0, 0.08), # 0.08 cash dividend
], dtype=self.dtype)
index = np.array([datetime.datetime.fromtimestamp(v) for v in ohlcs['time']],
dtype=object)
y = DataFrame.from_records(ohlcs, index=index, exclude=['time'])
y['adjclose'] = y['close']
for div in dividends:
d = Dividend(div)
d.adjust(y)
adjclose = y.xs(datetime.datetime(2003, 2, 13))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 23.42))
adjclose = y.xs(datetime.datetime(2003, 2, 14))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 24.07))
adjclose = y.xs(datetime.datetime(2003, 2, 18))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 24.88))
adjclose = y.xs(datetime.datetime(2003, 2, 19))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 24.53))
def test_adjust_divide_and_split(self):
ohlcs = np.array([
(1277222400, 20.739999771118164, 21.139999389648438, 20.68000030517578,
20.860000610351562, 506320.0, 1058136640.0),
(1277308800, 13.5, 13.880000114440918, 13.5,
13.609999656677246, 372504.0, 509364896.0),
(1277740800, 12.869999885559082, 12.970000267028809, 12.0,
12.010000228881836, 785225.0, 971340736.0)
], dtype=Day.DTYPE)
dividends = np.array([
(1062028800, 0.0, 0.0, 0.0, 0.003700000001117587),
(1086912000, 0.0, 0.0, 0.0, 0.10999999940395355),
(1121385600, 0.0, 0.0, 0.0, 0.05000000074505806),
(1151971200, 0.0, 0.0, 0.0, 0.11999999731779099),
(1179705600, 0.0, 0.0, 0.0, 0.20000000298023224),
(1208995200, 1.0, 0.0, 0.0, 0.5),
(1244678400, 0.0, 0.0, 0.0, 0.5),
(1277337600, 0.5, 0.0, 0.0, 0.5),
(1308182400, 0.0, 0.0, 0.0, 0.5)
], dtype=self.dtype)
index = np.array([datetime.datetime.fromtimestamp(v) for v in ohlcs['time']],
dtype=object)
y = DataFrame.from_records(ohlcs, index=index, exclude=['time'])
y['adjclose'] = y['close']
for div in dividends:
d = Dividend(div)
d.adjust(y)
adjclose = y.xs(datetime.datetime(2010, 6, 29))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 11.51))
adjclose = y.xs(datetime.datetime(2010, 6, 24))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 13.11))
adjclose = y.xs(datetime.datetime(2010, 6, 24))['adjclose']
self.assertTrue(self.floatEqual(adjclose, 13.07))
ROOT_PATH = os.path.join(os.path.realpath(os.path.dirname(__file__)), '..')
sys.path[0:0] = [ROOT_PATH]
from cStringIO import StringIO
from pandas import DataFrame
from datafeed.client import Client
from datafeed.dividend import Dividend
client = Client()
symbol = 'SH600036'
y = client.get_day(symbol, 1000)
dividends = client.get_dividend(symbol)
index = np.array([datetime.date.fromtimestamp(v) for v in y['time']],
dtype=object)
y = DataFrame.from_records(y, index=index, exclude=['time'])
print dividends
for div in dividends:
d = Dividend(div)
d.adjust(y)
day = '20080725'
print datetime.datetime.fromtimestamp(client.get_day(symbol, day)['time'])
d1 = client.get_day(symbol, day)
print d1
sys.path[0:0] = [ROOT_PATH]
from cStringIO import StringIO
from pandas import DataFrame
from datafeed.client import Client
from datafeed.dividend import Dividend
client = Client()
symbol = 'SH600036'
y = client.get_day(symbol, 1000)
dividends = client.get_dividend(symbol)
index = np.array([datetime.date.fromtimestamp(v) for v in y['time']],
dtype=object)
y = DataFrame.from_records(y, index=index, exclude=['time'])
print dividends
for div in dividends:
d = Dividend(div)
d.adjust(y)
day = '20080725'
print datetime.datetime.fromtimestamp(client.get_day(symbol, day)['time'])
d1 = client.get_day(symbol, day)
print d1
