def testTicksDataWith3StocksInSameSeconds(self):
ticks_data = [None, None, None]
dt1 = datetime.strptime("2014-05-11 19:15:23.009", DataType.DATE_TIME_FORMAT_LONG_MILLISECS)
dt2 = datetime.strptime("2014-05-11 19:15:23.010", DataType.DATE_TIME_FORMAT_LONG_MILLISECS)
tick_series = ticks_data[1]
tick_series, is_replacement = RunHFTModel.append_tick_data_to_series(dt1, 20, tick_series)
tick_series, is_replacement = RunHFTModel.append_tick_data_to_series(dt2, 21, tick_series)
ticks_data[1] = tick_series
expected = [None, np.array([[ 7.35364802e+05, 21]]), None]
self.check_array(expected, ticks_data, 3)
def testTicksDataWith3StocksInSameSeconds(self):
ticks_data = [None, None, None]
dt1 = datetime.strptime("2014-05-11 19:15:23.009",
DataType.DATE_TIME_FORMAT_LONG_MILLISECS)
dt2 = datetime.strptime("2014-05-11 19:15:23.010",
DataType.DATE_TIME_FORMAT_LONG_MILLISECS)
tick_series = ticks_data[1]
tick_series, is_replacement = RunHFTModel.append_tick_data_to_series(
dt1, 20, tick_series)
tick_series, is_replacement = RunHFTModel.append_tick_data_to_series(
dt2, 21, tick_series)
ticks_data[1] = tick_series
expected = [None, np.array([[7.35364802e+05, 21]]), None]
self.check_array(expected, ticks_data, 3)
def testCalculateParamsSTAndLTBetasOn2Stocks(self):
stocks_data = []
test_stock_data1 = StockData(create_stock_contract(self.stock))
test_stock_data1.set_is_storing_long_term()
test_stock_data1.add_historical_data_point(50, self.dt_1)
test_stock_data1.add_historical_data_point(60, self.dt_2)
test_stock_data1.set_finished_storing()
test_stock_data1.set_is_storing_short_term()
test_stock_data1.add_historical_data_point(20, self.dt_1)
test_stock_data1.add_historical_data_point(30, self.dt_2)
stocks_data.append(test_stock_data1)
test_stock_data2 = StockData(self.test_contract)
test_stock_data2.set_is_storing_long_term()
test_stock_data2.add_historical_data_point(10, self.dt_1)
test_stock_data2.add_historical_data_point(12, self.dt_2)
test_stock_data2.set_finished_storing()
test_stock_data2.set_is_storing_short_term()
test_stock_data2.add_historical_data_point(40, self.dt_1)
test_stock_data2.add_historical_data_point(60, self.dt_2)
stocks_data.append(test_stock_data2)
RunHFTModel.calculate_params(stocks_data)
def testCalculateParamsSTAndLTBetasOn2Stocks(self):
stocks_data = []
test_stock_data1 = StockData(create_stock_contract(self.stock))
test_stock_data1.set_is_storing_long_term()
test_stock_data1.add_historical_data_point(50, self.dt_1)
test_stock_data1.add_historical_data_point(60, self.dt_2)
test_stock_data1.set_finished_storing()
test_stock_data1.set_is_storing_short_term()
test_stock_data1.add_historical_data_point(20, self.dt_1)
test_stock_data1.add_historical_data_point(30, self.dt_2)
stocks_data.append(test_stock_data1)
test_stock_data2 = StockData(self.test_contract)
test_stock_data2.set_is_storing_long_term()
test_stock_data2.add_historical_data_point(10, self.dt_1)
test_stock_data2.add_historical_data_point(12, self.dt_2)
test_stock_data2.set_finished_storing()
test_stock_data2.set_is_storing_short_term()
test_stock_data2.add_historical_data_point(40, self.dt_1)
test_stock_data2.add_historical_data_point(60, self.dt_2)
stocks_data.append(test_stock_data2)
RunHFTModel.calculate_params(stocks_data)
def testTruncateTickSeries(self):
test_stock_data1 = StockData(create_stock_contract(self.stock))
test_stock_data1.set_is_storing_short_term()
test_stock_data1.add_historical_data_point(50, "20140511 19:15:24")
test_stock_data1.add_historical_data_point(60, "20140511 19:15:25")
test_stock_data1.add_historical_data_point(70, "20140511 19:15:26")
test_stock_data1.add_historical_data_point(80, "20140511 19:15:27")
test_stock_data1.add_historical_data_point(90, "20140511 19:15:28")
test_stock_data1.add_historical_data_point(100, "20140511 19:15:29")
test_stock_data1.set_finished_storing()
length = 5
chart_ds = test_stock_data1.get_historical_short_term_chart_data_set()
tick_series = chart_ds.get_prices()
new_tick_series = RunHFTModel.truncate_tick_series(tick_series, length)
expected = [60, 70, 80, 90, 100]
self.check_array(expected, new_tick_series)
def testTruncateTickSeries(self):
test_stock_data1 = StockData(create_stock_contract(self.stock))
test_stock_data1.set_is_storing_short_term()
test_stock_data1.add_historical_data_point(50, "20140511 19:15:24")
test_stock_data1.add_historical_data_point(60, "20140511 19:15:25")
test_stock_data1.add_historical_data_point(70, "20140511 19:15:26")
test_stock_data1.add_historical_data_point(80, "20140511 19:15:27")
test_stock_data1.add_historical_data_point(90, "20140511 19:15:28")
test_stock_data1.add_historical_data_point(100, "20140511 19:15:29")
test_stock_data1.set_finished_storing()
length = 5
chart_ds = test_stock_data1.get_historical_short_term_chart_data_set()
tick_series = chart_ds.get_prices()
new_tick_series = RunHFTModel.truncate_tick_series(tick_series, length)
expected = [60, 70, 80, 90, 100]
self.check_array(expected, new_tick_series)
def testAIsOverBought(self):
fairPrices = [50, 40 ,30]
result = RunHFTModel.get_is_overbought_or_oversold(fairPrices)
expected = True, False
self.assertEqual(expected, result)
def testAIsOverSold(self):
fairPrices = [50, 60 ,70]
result = RunHFTModel.get_is_overbought_or_oversold(fairPrices)
expected = False, True
self.assertEqual(expected, result)
def testAIsNeitherOverboughtOrOversold(self):
fairPrices = [50, 60 ,30]
result = RunHFTModel.get_is_overbought_or_oversold(fairPrices)
expected = False, False
self.assertEqual(expected, result)
def testBridgeBootstrap(self):
# Store historical ticks
test_stock_data1 = StockData(create_stock_contract(self.stock))
test_stock_data1.set_is_storing_short_term()
test_stock_data1.add_historical_data_point(50, "20140511 19:15:24")
test_stock_data1.add_historical_data_point(60, "20140511 19:15:25")
test_stock_data1.set_finished_storing()
stocks_data = [test_stock_data1]
# Store incoming ticks
p1 = 20
p2 = 21
p3 = 22
p4 = 23
p5 = 24
dt1 = datetime.strptime("2014-05-11 19:15:23", DataType.DATE_TIME_FORMAT_LONG)
dt2 = datetime.strptime("2014-05-11 19:15:24", DataType.DATE_TIME_FORMAT_LONG)
dt3 = datetime.strptime("2014-05-11 19:15:25", DataType.DATE_TIME_FORMAT_LONG)
dt4 = datetime.strptime("2014-05-11 19:15:26", DataType.DATE_TIME_FORMAT_LONG)
dt5 = datetime.strptime("2014-05-11 19:15:27", DataType.DATE_TIME_FORMAT_LONG)
tick_1 = np.array([dates.date2num(dt1), p1])
tick_2 = np.array([dates.date2num(dt2), p2])
tick_3 = np.array([dates.date2num(dt3), p3])
tick_4 = np.array([dates.date2num(dt4), p4])
tick_5 = np.array([dates.date2num(dt5), p5])
# Create test ticks data.
tick_series = np.array(tick_1)
tick_series = np.vstack([tick_series, tick_2])
tick_series = np.vstack([tick_series, tick_3])
tick_series = np.vstack([tick_series, tick_4])
tick_series = np.vstack([tick_series, tick_5])
ticks_data = [tick_series]
# Bridge ticks and retrieve results
end_time = datetime.strptime("2014-05-11 19:15:35", DataType.DATE_TIME_FORMAT_LONG)
RunHFTModel.bridge_historical_and_present_ticks(stocks_data, ticks_data, end_time)
chart_ds = stocks_data[0].get_historical_short_term_chart_data_set()
# Test for prices
result_prices = chart_ds.get_prices()
expected_prices = [50, 60, 23, 24,
24, 24, 24, 24,
24, 24, 24, 24]
self.check_array(expected_prices, result_prices)
# Test date labels
expected_datelabels = ['20140511 19:15:24'
, '20140511 19:15:25'
, '20140511 19:15:26'
, '20140511 19:15:27'
, '20140511 19:15:28'
, '20140511 19:15:29'
, '20140511 19:15:30'
, '20140511 19:15:31'
, '20140511 19:15:32'
, '20140511 19:15:33'
, '20140511 19:15:34'
, '20140511 19:15:35'
]
result_datelabels = chart_ds.get_dates_labels()
self.check_array(expected_datelabels, result_datelabels)
def testAIsOverBought(self):
fairPrices = [50, 40, 30]
result = RunHFTModel.get_is_overbought_or_oversold(fairPrices)
expected = True, False
self.assertEqual(expected, result)
def testAIsOverSold(self):
fairPrices = [50, 60, 70]
result = RunHFTModel.get_is_overbought_or_oversold(fairPrices)
expected = False, True
self.assertEqual(expected, result)
def testAIsNeitherOverboughtOrOversold(self):
fairPrices = [50, 60, 30]
result = RunHFTModel.get_is_overbought_or_oversold(fairPrices)
expected = False, False
self.assertEqual(expected, result)
def testBridgeBootstrap(self):
# Store historical ticks
test_stock_data1 = StockData(create_stock_contract(self.stock))
test_stock_data1.set_is_storing_short_term()
test_stock_data1.add_historical_data_point(50, "20140511 19:15:24")
test_stock_data1.add_historical_data_point(60, "20140511 19:15:25")
test_stock_data1.set_finished_storing()
stocks_data = [test_stock_data1]
# Store incoming ticks
p1 = 20
p2 = 21
p3 = 22
p4 = 23
p5 = 24
dt1 = datetime.strptime("2014-05-11 19:15:23",
DataType.DATE_TIME_FORMAT_LONG)
dt2 = datetime.strptime("2014-05-11 19:15:24",
DataType.DATE_TIME_FORMAT_LONG)
dt3 = datetime.strptime("2014-05-11 19:15:25",
DataType.DATE_TIME_FORMAT_LONG)
dt4 = datetime.strptime("2014-05-11 19:15:26",
DataType.DATE_TIME_FORMAT_LONG)
dt5 = datetime.strptime("2014-05-11 19:15:27",
DataType.DATE_TIME_FORMAT_LONG)
tick_1 = np.array([dates.date2num(dt1), p1])
tick_2 = np.array([dates.date2num(dt2), p2])
tick_3 = np.array([dates.date2num(dt3), p3])
tick_4 = np.array([dates.date2num(dt4), p4])
tick_5 = np.array([dates.date2num(dt5), p5])
# Create test ticks data.
tick_series = np.array(tick_1)
tick_series = np.vstack([tick_series, tick_2])
tick_series = np.vstack([tick_series, tick_3])
tick_series = np.vstack([tick_series, tick_4])
tick_series = np.vstack([tick_series, tick_5])
ticks_data = [tick_series]
# Bridge ticks and retrieve results
end_time = datetime.strptime("2014-05-11 19:15:35",
DataType.DATE_TIME_FORMAT_LONG)
RunHFTModel.bridge_historical_and_present_ticks(
stocks_data, ticks_data, end_time)
chart_ds = stocks_data[0].get_historical_short_term_chart_data_set()
# Test for prices
result_prices = chart_ds.get_prices()
expected_prices = [50, 60, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24]
self.check_array(expected_prices, result_prices)
# Test date labels
expected_datelabels = [
'20140511 19:15:24', '20140511 19:15:25', '20140511 19:15:26',
'20140511 19:15:27', '20140511 19:15:28', '20140511 19:15:29',
'20140511 19:15:30', '20140511 19:15:31', '20140511 19:15:32',
'20140511 19:15:33', '20140511 19:15:34', '20140511 19:15:35'
]
result_datelabels = chart_ds.get_dates_labels()
self.check_array(expected_datelabels, result_datelabels)
