def test_basket_without_weights():
replace = Replacer()
mock_data = replace('gs_quant.timeseries.backtesting.ts.get_historical_and_last_for_measure', Mock())
mock_data.side_effect = [_mock_spot_data(), _mock_spot_data(), _mock_spot_data(), _mock_spot_data()]
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'},
{'id': 'MA4B66MW5E27UAL9SUX', 'bbid': 'MSFT UW'}]
a_basket = Basket(['AAPL UW', 'MSFT UW'], [0.5, 0.5], RebalFreq.DAILY)
b_basket = Basket(['AAPL UW', 'MSFT UW'])
with DataContext('2021-01-01', '2021-01-06'):
a_price = a_basket.price()
b_price = b_basket.price()
a_vol = a_basket.average_realized_volatility('2d')
b_vol = b_basket.average_realized_volatility('2d')
assert_series_equal(a_price, b_price)
assert_series_equal(a_vol, b_vol)
with pytest.raises(MqValueError):
c_basket = Basket(['AAPL UW'], [])
c_basket.price()
replace.restore()
def test_basket_average_realized_corr():
replace = Replacer()
dates = pd.DatetimeIndex([date(2021, 1, 1), date(2021, 1, 2), date(2021, 1, 3), date(2021, 1, 4), date(2021, 1, 5),
date(2021, 1, 6)])
mock_data = replace('gs_quant.timeseries.backtesting.ts.get_historical_and_last_for_measure', Mock())
mock_data.side_effect = [_mock_spot_data_identical(), _mock_spot_data_corr(),
_mock_spot_data_identical()]
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [
{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'},
{'id': 'MA4B66MW5E27UAL9SUX', 'bbid': 'MSFT UW'},
{'id': 'ID of a dUpLiCaTe AAPL', 'bbid': 'AAPL UW'}
]
a_basket = Basket(['AAPL UW', 'MSFT UW'], [0.1, 0.9], RebalFreq.DAILY)
# Equal series have correlation of 1
with DataContext('2021-01-01', '2021-01-06'):
expected = pd.Series([np.nan, np.nan, 1.0, 1.0, 1.0, 1.0], index=dates)
result = a_basket.average_realized_correlation('2d')
assert_series_equal(result, expected)
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [
{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'},
{'id': 'MA4B66MW5E27UAL9SUX', 'bbid': 'MSFT UW'},
{'id': 'MA4B66MW5E27UANZH2M', 'bbid': 'XLP UP'},
{'id': 'ID of a dUpLiCaTe XLP UP', 'bbid': 'XLP UP'}
]
b_basket = Basket(['AAPL UW', 'MSFT UW', 'XLP UP'], [0.2, 0.3, 0.5], RebalFreq.DAILY)
# Test with two different series
with DataContext('2021-01-01', '2021-01-06'):
result = b_basket.average_realized_correlation('5d')
expected = pd.Series([np.nan, np.nan, np.nan, np.nan, np.nan, 0.26872959922887607], index=dates)
assert_series_equal(result, expected)
# Test correct error being thrown
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [
{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'},
{'id': 'MA4B66MW5E27UAL9SUX', 'bbid': 'MSFT UW'},
{'id': 'MA4B66MW5E27UANZH2M', 'bbid': 'XLP UP'},
{'id': 'ID of a DuPlIcAtE MSFT UW', 'bbid': 'MSFT UW'}
]
with pytest.raises(NotImplementedError):
with DataContext('2021-01-01', '2021-01-09'):
result = b_basket.average_realized_correlation('5d', real_time=True)
replace.restore()
def test_basket_average_realized_vol_intraday():
replace = Replacer()
end_date = date.today() - datetime.timedelta(days=1)
start_date = end_date - datetime.timedelta(days=4)
a = pd.Series([1 for i in range(5)], index=pd.date_range(start_date, end_date))
z = pd.DataFrame({'spot': (a ** 3).tolist()}, index=a.index)
z['assetId'] = 'SPX_MOCK_MQID'
mock_data = replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', Mock())
mock_data.side_effect = [z]
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [{'id': 'SPX_MOCK_MQID', 'bbid': 'SPX'}]
mock_today = replace('gs_quant.timeseries.get_last_for_measure', Mock())
mock_today.side_effect = [pd.DataFrame({'assetId': 'SPX_MOCK_MQID', 'spot': 5001.0},
index=[datetime.datetime.now()])]
a_basket = Basket(['SPX'], [1], RebalFreq.DAILY)
with DataContext(start=start_date, end=date.today()):
avg_vol = a_basket.average_realized_volatility('2d')
assert avg_vol.index[-1].date() == date.today()
replace.restore()
def test_basket_average_implied_vol():
replace = Replacer()
dates = pd.DatetimeIndex([date(2021, 1, 1), date(2021, 1, 2), date(2021, 1, 3), date(2021, 1, 4), date(2021, 1, 5),
date(2021, 1, 6)])
x = pd.DataFrame({'impliedVolatility': [30.0, 30.2, 29.8, 30.6, 30.1, 30.0]}, index=dates)
x['assetId'] = 'MA4B66MW5E27U9VBB94'
y = pd.DataFrame({'impliedVolatility': [20.0, 20.2, 20.3, 20.6, 21.1, 20.0]}, index=dates)
y['assetId'] = 'MA4B66MW5E27UAL9SUX'
implied_vol = x.append(y)
implied_vol.index.name = 'date'
mock_data = replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', Mock())
mock_data.side_effect = [implied_vol, _mock_spot_data()]
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'},
{'id': 'MA4B66MW5E27UAL9SUX', 'bbid': 'MSFT UW'}]
a_basket = Basket(['AAPL UW', 'MSFT UW'], [0.1, 0.9], RebalFreq.DAILY)
expected = pd.Series([21.0, 21.2, 21.25, 21.6, 22.0, 21.0], index=dates)
actual = a_basket.average_implied_volatility('6m', EdrDataReference.DELTA_CALL, 50)
assert_series_equal(actual, expected)
with pytest.raises(NotImplementedError):
a_basket.average_implied_volatility('6m', EdrDataReference.DELTA_CALL, 50, real_time=True)
replace.restore()
def test_basket_price():
with pytest.raises(MqValueError):
Basket(['AAPL UW'], [0.1, 0.9], RebalFreq.MONTHLY)
dates = pd.DatetimeIndex([date(2021, 1, 1), date(2021, 1, 2), date(2021, 1, 3), date(2021, 1, 4), date(2021, 1, 5),
date(2021, 1, 6)])
dates_feb = pd.DatetimeIndex([date(2021, 2, 1), date(2021, 2, 2), date(2021, 2, 3), date(2021, 2, 4),
date(2021, 2, 5), date(2021, 2, 6)])
replace = Replacer()
mock_data = replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', Mock())
mock_data.side_effect = [_mock_spot_data(), _mock_spot_data_feb()]
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'},
{'id': 'MA4B66MW5E27UAL9SUX', 'bbid': 'MSFT UW'}]
a_basket = Basket(['AAPL UW', 'MSFT UW'], [0.1, 0.9], RebalFreq.MONTHLY)
expected = pd.Series([100.0, 100.1, 100.302, 100.09596, 100.09596, 100.297879], index=dates)
with DataContext('2021-01-01', '2021-01-06'):
actual = a_basket.price()
assert_series_equal(actual, expected)
expected = pd.Series([100.00, 101.50, 100.62, 98.30, 96.30, 94.80], index=dates_feb)
with DataContext('2021-02-01', '2021-02-06'):
actual = a_basket.price()
assert_series_equal(actual, expected)
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'}]
with pytest.raises(MqValueError):
Basket(['AAPL UW', 'ABC'], [0.1, 0.9], RebalFreq.MONTHLY).price()
with pytest.raises(NotImplementedError):
a_basket.price(real_time=True)
replace.restore()
def test_basket_average_realized_vol():
replace = Replacer()
dates = pd.DatetimeIndex([date(2021, 1, 1), date(2021, 1, 2), date(2021, 1, 3), date(2021, 1, 4), date(2021, 1, 5),
date(2021, 1, 6)])
dates_feb = pd.DatetimeIndex([date(2021, 2, 1), date(2021, 2, 2), date(2021, 2, 3), date(2021, 2, 4),
date(2021, 2, 5), date(2021, 2, 6)])
mock_data = replace('gs_quant.timeseries.backtesting.ts.get_historical_and_last_for_measure', Mock())
mock_data.side_effect = [_mock_spot_data(), _mock_spot_data_feb(), _mock_spot_data_feb()]
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'},
{'id': 'MA4B66MW5E27UAL9SUX', 'bbid': 'MSFT UW'}]
a_basket = Basket(['AAPL UW', 'MSFT UW'], [0.1, 0.9], RebalFreq.DAILY)
expected = pd.Series([1.1059, 4.4906, 2.2677, 2.2228], index=dates[2:])
with DataContext('2021-01-01', '2021-01-06'):
actual = a_basket.average_realized_volatility('2d')
assert_series_equal(actual, expected, atol=10e-3)
expected = pd.Series([3.3088, 3.1754, 3.1754], index=dates[3:])
with DataContext('2021-01-01', '2021-01-06'):
actual = a_basket.average_realized_volatility('3d')
assert_series_equal(actual, expected)
mock_data.assert_called_once()
expected = pd.Series([34.81054014068537, 19.98982339010735, 19.08853721611424], index=dates_feb[3:])
with DataContext('2021-02-01', '2021-02-06'):
actual = a_basket.average_realized_volatility('3d')
assert_series_equal(actual, expected)
with pytest.raises(NotImplementedError):
a_basket.average_realized_volatility('2d', real_time=True)
mock_get_last = replace('gs_quant.timeseries.measures.get_last_for_measure', Mock())
mock_get_last.return_value = None
# Test case where ts.get_last_for_measure returns none
with DataContext('2021-02-01', datetime.date.today() + datetime.timedelta(days=2)):
a_basket.average_realized_volatility('2d')
replace.restore()
def test_basket_average_realized_vol_wts():
replace = Replacer()
mock_data = replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', Mock())
mock_data.side_effect = [_mock_data_simple()]
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [{'id': 'XLB_MOCK_MQID', 'bbid': 'XLP UP'},
{'id': 'XLC_MOCK_MQID', 'bbid': 'XLC UP'}, {'id': 'SPX_MOCK_MQID', 'bbid': 'SPX'}]
mock_vol = replace('gs_quant.timeseries.backtesting.volatility', Mock())
mock_vol.side_effect = [_mock_vol_simple(), _mock_vol_simple() * 2, _mock_vol_simple() * 3, _mock_vol_simple() * 4]
a_basket = Basket(['XLC UP', 'XLP UP', 'SPX'], [0.2, 0.3, 0.5], RebalFreq.DAILY)
with DataContext(start=date(2021, 9, 1), end=date(2021, 9, 25)):
av_realized_vol = a_basket.average_realized_volatility('2d')
np.testing.assert_approx_equal(av_realized_vol.iloc[0], 1.7)
replace.restore()
def test_basket_average_realized_vol():
replace = Replacer()
dates = pd.DatetimeIndex([date(2021, 1, 1), date(2021, 1, 2), date(2021, 1, 3), date(2021, 1, 4), date(2021, 1, 5),
date(2021, 1, 6)])
dates_feb = pd.DatetimeIndex([date(2021, 2, 1), date(2021, 2, 2), date(2021, 2, 3), date(2021, 2, 4),
date(2021, 2, 5), date(2021, 2, 6)])
mock_data = replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', Mock())
mock_data.side_effect = [_mock_spot_data(), _mock_spot_data_feb()]
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'},
{'id': 'MA4B66MW5E27UAL9SUX', 'bbid': 'MSFT UW'}]
a_basket = Basket(['AAPL UW', 'MSFT UW'], [0.1, 0.9], RebalFreq.DAILY)
expected = pd.Series([1.1225, 4.49, 2.245, 2.245], index=dates[2:])
with DataContext('2021-01-01', '2021-01-06'):
actual = a_basket.average_realized_volatility('2d')
assert_series_equal(actual, expected)
expected = pd.Series([3.304542, 3.174902, 3.174902], index=dates[3:])
with DataContext('2021-01-01', '2021-01-06'):
actual = a_basket.average_realized_volatility('3d')
assert_series_equal(actual, expected)
mock_data.assert_called_once()
expected = pd.Series([34.698082, 19.719302, 18.860533], index=dates_feb[3:])
with DataContext('2021-02-01', '2021-02-06'):
actual = a_basket.average_realized_volatility('3d')
assert_series_equal(actual, expected)
with pytest.raises(NotImplementedError):
a_basket.average_realized_volatility('2d', real_time=True)
replace.restore()
def test_basket_average_implied_vol():
replace = Replacer()
dates = pd.DatetimeIndex([date(2021, 1, 1), date(2021, 1, 2), date(2021, 1, 3), date(2021, 1, 4), date(2021, 1, 5),
date(2021, 1, 6)])
x = pd.DataFrame({'impliedVolatility': [30.0, 30.2, 29.8, 30.6, 30.1, 30.0]}, index=dates)
x['assetId'] = 'MA4B66MW5E27U9VBB94'
y = pd.DataFrame({'impliedVolatility': [20.0, 20.2, 20.3, 20.6, 21.1, 20.0]}, index=dates)
y['assetId'] = 'MA4B66MW5E27UAL9SUX'
implied_vol = x.append(y)
implied_vol.index.name = 'date'
mock_spot = replace('gs_quant.timeseries.backtesting.ts.get_historical_and_last_for_measure', Mock())
mock_spot.side_effect = [implied_vol.rename(columns={'impliedVolatility': 'spot'})]
mock_data = replace('gs_quant.api.utils.ThreadPoolManager.run_async', Mock())
mock_data.return_value = [implied_vol]
mock_asset = replace('gs_quant.timeseries.backtesting.GsAssetApi.get_many_assets_data', Mock())
mock_asset.return_value = [{'id': 'MA4B66MW5E27U9VBB94', 'bbid': 'AAPL UW'},
{'id': 'MA4B66MW5E27UAL9SUX', 'bbid': 'MSFT UW'}]
a_basket = Basket(['AAPL UW', 'MSFT UW'], [0.1, 0.9], RebalFreq.DAILY)
expected = pd.Series([21.0, 21.2, 21.25, 21.6, 22.0, 21.0], index=dates)
actual = a_basket.average_implied_volatility('6m', VolReference.DELTA_CALL, 50)
assert_series_equal(actual, expected)
with pytest.raises(NotImplementedError):
a_basket.average_implied_volatility('6m', VolReference.DELTA_CALL, 50, real_time=True)
mock_data.return_value = [pd.DataFrame(), pd.DataFrame()]
expected = pd.Series(dtype=float)
actual = a_basket.average_implied_volatility('3m', VolReference.FORWARD, 20) # no data for this
assert_series_equal(expected, actual)
replace.restore()