def testRunOverTimeFrame(self):
"""test for generating the delivery date"""
seq, days = run_over_time_frame()
self.assertEqual('2013-01-16', seq[0])
self.assertEqual('2013-02-13', seq[1])
self.assertEqual('2013-03-20', seq[2])
self.assertEqual('2013-04-17', seq[3])
self.assertEqual('2013-05-22', seq[4])
self.assertEqual('2013-06-19', seq[5])
self.assertEqual('2013-07-17', seq[6])
self.assertEqual('2013-08-21', seq[7])
self.assertEqual('2013-09-18', seq[8])
self.assertEqual('2013-10-16', seq[9])
self.assertEqual('2013-11-20', seq[10])
self.assertEqual('2013-12-18', seq[11])
self.assertEqual('2019-08-21', seq[79])
self.assertEqual('2019-09-18', seq[80])
self.assertEqual('2019-10-16', seq[81])
self.assertEqual('2019-11-20', seq[82])
self.assertEqual('2019-12-18', seq[83])
self.assertEqual('2020-01-22', seq[84])
self.assertEqual('2020-02-19', seq[85])
self.assertEqual('2020-03-18', seq[86])
self.assertEqual('2020-04-15', seq[87])
self.assertEqual('2020-05-20', seq[88])
self.assertEqual('2020-06-17', seq[89])
self.assertEqual('2020-07-22', seq[90])
self.assertEqual('2020-08-19', seq[91])
self.assertEqual('2020-09-16', seq[92])
self.assertEqual('2020-10-21', seq[93])
self.assertEqual('2020-11-18', seq[94])
self.assertEqual('2020-12-16', seq[95])
def testDeliveryDates(self):
""""""
delivery_dates, schedul_days = run_over_time_frame()
flist = filter_delivery_dates(delivery_dates, '2020-09-10')
np.testing.assert_array_equal(['2019-09-18', '2019-10-16',
'2019-11-20', '2019-12-18',
'2020-01-22', '2020-02-19',
'2020-03-18', '2020-04-15',
'2020-05-20', '2020-06-17',
'2020-07-22', '2020-08-19'], flist)
flist2 = shift_delivery_dates(delivery_dates, flist, -1)
np.testing.assert_array_equal(['2019-08-21', '2019-09-18', '2019-10-16',
'2019-11-20', '2019-12-18',
'2020-01-22', '2020-02-19',
'2020-03-18', '2020-04-15',
'2020-05-20', '2020-06-17',
'2020-07-22'], flist2)
flist3 = shift_delivery_dates(delivery_dates, flist2, -1)
np.testing.assert_array_equal(['2019-07-17', '2019-08-21',
'2019-09-18', '2019-10-16',
'2019-11-20', '2019-12-18',
'2020-01-22', '2020-02-19',
'2020-03-18', '2020-04-15',
'2020-05-20', '2020-06-17'], flist3)
flist4 = shift_delivery_dates(delivery_dates, flist, -2)
np.testing.assert_array_equal(flist4, flist3)
def testCombineAll(self):
""""""
self.assertEqual((True, '2020-08-19'), is_futures_file('2020-08-19.csv'))
self.assertEqual((True, '2020-09-16'), is_futures_file('2020-09-16.csv'))
self.assertEqual((True, '2020-08-19'), is_futures_file('./data/2020-08-19.csv'))
self.assertEqual((False, None), is_futures_file('VIX.csv'))
delivery_dates, schedule_days = run_over_time_frame()
info = combine_all(delivery_dates, TEST_DATA_ROOT)
self.assertEqual((211, 12), info.shape)
np.testing.assert_array_equal([28.775, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], info.loc['2020-09-10'])
np.testing.assert_array_equal([21.71, 26.225, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], info.loc['2020-08-19'])
np.testing.assert_array_equal([28.775, 30.275, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], info.loc['2020-07-23'])
np.testing.assert_array_equal([0, 27.25, 29.125, 0, 0, 0, 0, 0, 0, 0, 0, 0], info.loc['2020-07-22'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 17.175, 17.475, 0, 0, 0], info.loc['2020-01-17'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 18.6, 19.1, 0, 0], info.loc['2019-12-12'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 19.075, 19.2, 0, 0], info.loc['2019-12-09'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 18.75, 0, 0, 0], info.loc['2019-11-25'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], info.loc['2013-01-16'])
np.testing.assert_array_equal([14.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], info.loc['2013-01-15'])
np.testing.assert_array_equal([15.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], info.loc['2013-01-02'])
delta_p = analyze_diff_percent(info)
np.testing.assert_array_equal(
[np.nan, -1, np.nan, np.nan, np.nan, np.nan,
np.nan, np.nan, np.nan, np.nan, np.nan, np.nan], delta_p.loc['2020-09-10'])
np.testing.assert_array_almost_equal(
[np.nan, (26.225 - 21.71) / 21.71, -1, np.nan, np.nan, np.nan,
np.nan, np.nan, np.nan, np.nan, np.nan, np.nan], delta_p.loc['2020-08-19'])
np.testing.assert_array_almost_equal(
[np.nan, (30.275 - 28.775) / 28.775, -1, np.nan, np.nan, np.nan,
np.nan, np.nan, np.nan, np.nan, np.nan, np.nan], delta_p.loc['2020-07-23'])
np.testing.assert_array_almost_equal(
[np.nan, np.inf, (29.125 - 27.25) / 27.25, -1, np.nan, np.nan,
np.nan, np.nan, np.nan, np.nan, np.nan, np.nan], delta_p.loc['2020-07-22'])
def testNotificationMsg(self):
""""""
delivery_dates, schedule_days = run_over_time_frame()
mgr = VIXDataManager(delivery_dates)
df = mgr.combine_all()
rets_v = mgr.analyze()
gvz = GVZDataManager()
rets_g = gvz.analyze()
ovx = OVXDataManager()
rets_o = ovx.analyze()
params = mk_notification_params(df, delivery_dates, rets_v, rets_g, rets_o)
msg = mk_notification(**params)
print(msg)
def do_timeout(self):
""""""
logger.info('start schedule task. ')
delivery_dates, schedule_days = run_over_time_frame()
self._last_day = get_last_day(self._update_hour)
self._day_index = datetime.strftime(self._last_day, DATE_FORMAT)
if not is_business_day(self._last_day, schedule_days):
logger.info('last day is not a business day. ')
return self.clear_and_return_true()
vdm = VIXDataManager(delivery_dates)
vdm.download_raw_data(self._day_vix_downloaded)
df = vdm.combine_all()
rets_vix = vdm.analyze()
if rets_vix['vix_diff'].index[-1] != self._day_index or \
self._day_index not in rets_vix['vix'].index:
# vix diff is not pulled, retry 5 minutes later
logger.info(
f"last_day: {self._last_day}, index: {self._day_index}, vix_index: {rets_vix['vix'].index[-1]}, vix_diff_index: {rets_vix['vix_diff'].index[-1]}"
)
logger.info("vix info download failed. ")
return False
elif df.iloc[-1][0] <= 1 or df.iloc[-1][1] <= 1:
logger.info(
f'vix info download failed due to vix 0 or 1 is zero. ')
return False
self._day_vix_downloaded = True
# gvz futures are delisted
gvzm = GVZDataManager([])
gvzm.download_raw_data(self._day_gvz_downloaded)
rets_gvzm = gvzm.analyze()
if self._day_index not in rets_gvzm['gvz'].index:
logger.info("gvz info download failed. ")
return False
self._day_gvz_downloaded = True
# ovx futures are delisted
ovxm = OVXDataManager([])
ovxm.download_raw_data(self._day_ovx_downloaded)
rets_ovxm = ovxm.analyze()
if self._day_index not in rets_ovxm['ovx'].index:
logger.info("ovx info download failed. ")
return False
self._day_ovx_downloaded = True
params = mk_notification_params(df, delivery_dates, rets_vix,
rets_gvzm, rets_ovxm)
title, msg = mk_notification(**params)
if self._push_msg:
send_md_msg(title, msg)
logger.info('schedule task done. ')
return self.clear_and_return_true()
def testTermStucture(self):
"""for mask test"""
delivery_dates, schedule_days = run_over_time_frame()
futures_0916 = load_futures_by_csv(os.path.join(TEST_DATA_ROOT, '2020-09-16.csv'))
term1 = generate_term_structure(
delivery_dates, futures_0916, '2020-09-10')
self.assertEqual((191, 12), term1.shape)
np.testing.assert_array_equal([28.775, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], term1.loc['2020-09-10'])
np.testing.assert_array_equal([0, 26.225, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], term1.loc['2020-08-19'])
np.testing.assert_array_equal([0, 30.275, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], term1.loc['2020-07-23'])
np.testing.assert_array_equal([0, 0, 29.125, 0, 0, 0, 0, 0, 0, 0, 0, 0], term1.loc['2020-07-22'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 17.475, 0, 0, 0], term1.loc['2020-01-17'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 0, 19.1, 0, 0], term1.loc['2019-12-12'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 0, 19.2, 0, 0], term1.loc['2019-12-09'])
# boundary test for deliver date
futures_0819 = load_futures_by_csv(os.path.join(TEST_DATA_ROOT, '2020-08-19.csv'))
term2 = generate_term_structure(
delivery_dates, futures_0819, '2020-08-19')
np.testing.assert_array_equal([21.71, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], term2.loc['2020-08-19'])
np.testing.assert_array_equal([28.775, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], term2.loc['2020-07-23'])
np.testing.assert_array_equal([0, 27.25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], term2.loc['2020-07-22'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 17.175, 0, 0, 0, 0], term2.loc['2020-01-17'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 18.6, 0, 0, 0], term2.loc['2019-12-12'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 19.075, 0, 0, 0], term2.loc['2019-12-09'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 18.75, 0, 0, 0], term2.loc['2019-11-25'])
# test for combine
term3 = combine_data(term1, term2)
np.testing.assert_array_equal([28.775, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], term3.loc['2020-09-10'])
np.testing.assert_array_equal([21.71, 26.225, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], term3.loc['2020-08-19'])
np.testing.assert_array_equal([28.775, 30.275, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], term3.loc['2020-07-23'])
np.testing.assert_array_equal([0, 27.25, 29.125, 0, 0, 0, 0, 0, 0, 0, 0, 0], term3.loc['2020-07-22'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 17.175, 17.475, 0, 0, 0], term3.loc['2020-01-17'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 18.6, 19.1, 0, 0], term3.loc['2019-12-12'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 19.075, 19.2, 0, 0], term3.loc['2019-12-09'])
np.testing.assert_array_equal([0, 0, 0, 0, 0, 0, 0, 0, 18.75, 0, 0, 0], term3.loc['2019-11-25'])
futures_0116 = load_futures_by_csv(os.path.join(TEST_DATA_ROOT, '2013-01-16.csv'))
term4 = generate_term_structure(delivery_dates, futures_0116, '2013-01-16')
np.testing.assert_array_equal([0], term4.loc['2013-01-16'])
np.testing.assert_array_equal([14.2], term4.loc['2013-01-15'])
np.testing.assert_array_equal([15.6], term4.loc['2013-01-02'])
futures_0116 = load_futures_by_csv(os.path.join(TEST_DATA_ROOT, '2012-01-16.csv'))
term5 = generate_term_structure(delivery_dates, futures_0116, '2012-01-16')
self.assertEqual(None, term5)
def get_vix_info(last_date):
# query data from the data manager
# param last_date is for lru_cache only
delivery_dates, schedule_days = run_over_time_frame()
vdm = VIXDataManager(delivery_dates)
df = vdm.combine_all(24)
rets_vix = vdm.analyze()
gvzm = GVZDataManager([])
rets_gvzm = gvzm.analyze()
ovxm = OVXDataManager([])
rets_ovxm = ovxm.analyze()
vix_diff = rets_vix['vix_diff'][[1]]
vix_diff.rename({1: 'diff'}, axis=1, inplace=True)
df_gvz = rets_gvzm['gvz'][[CLOSE_PRICE_NAME]]
df_gvz.rename({CLOSE_PRICE_NAME: 'gvz'}, axis=1, inplace=True)
df_ovx = rets_ovxm['ovx'][[CLOSE_PRICE_NAME]]
df_ovx.rename({CLOSE_PRICE_NAME: 'ovx'}, axis=1, inplace=True)
df = df.join(vix_diff)
df = df.join(df_gvz)
df = df.join(df_ovx)
return df, delivery_dates