def test_swap_rate():
replace = Replacer()
mock_usd = Currency('MA890', 'USD')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs',
Mock())
xrefs.return_value = [
GsTemporalXRef(dt.date(2019, 1, 1), dt.date(2952, 12, 31),
XRef(bbid='USD', ))
]
identifiers = replace(
'gs_quant.timeseries.measures.GsAssetApi.map_identifiers', Mock())
identifiers.return_value = {'USD-3m': 'MA123'}
replace('gs_quant.timeseries.measures.GsDataApi.get_market_data',
mock_curr)
actual = tm.swap_rate(mock_usd, '1y')
assert_series_equal(
pd.Series([1, 2, 3], index=_index * 3, name='swapRate'), actual)
identifiers = replace(
'gs_quant.timeseries.measures.GsAssetApi.map_identifiers', Mock())
identifiers.return_value = {'USD OIS': 'MA123'}
actual = tm.swap_rate(mock_usd, '1y', BenchmarkType.OIS)
assert_series_equal(
pd.Series([1, 2, 3], index=_index * 3, name='swapRate'), actual)
mock_eur = Currency('MA890', 'EUR')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs',
Mock())
xrefs.return_value = [
GsTemporalXRef(dt.date(2019, 1, 1), dt.date(2952, 12, 31),
XRef(bbid='EUR', ))
]
identifiers = replace(
'gs_quant.timeseries.measures.GsAssetApi.map_identifiers', Mock())
identifiers.return_value = {'EUR-6m': 'MA123'}
actual = tm.swap_rate(mock_eur, '1y')
assert_series_equal(
pd.Series([1, 2, 3], index=_index * 3, name='swapRate'), actual)
mock_sek = Currency('MA890', 'SEK')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs',
Mock())
xrefs.return_value = [
GsTemporalXRef(dt.date(2019, 1, 1), dt.date(2952, 12, 31),
XRef(bbid='SEK', ))
]
identifiers = replace(
'gs_quant.timeseries.measures.GsAssetApi.map_identifiers', Mock())
identifiers.return_value = {'SEK-6m': 'MA123'}
actual = tm.swap_rate(mock_sek, '1y')
assert_series_equal(
pd.Series([1, 2, 3], index=_index * 3, name='swapRate'), actual)
with pytest.raises(NotImplementedError):
tm.swap_rate(..., '1y', real_time=True)
replace.restore()
def test_get_asset_xrefs(mocker):
marquee_id = 'MQA1234567890'
mock_response = {
'xrefs': ({
'startDate': '1952-01-01',
'endDate': '2018-12-31',
'identifiers': {
'ric': '.GSTHHOLD',
'bbid': 'GSTHHOLD',
'cusip': '9EQ24FOLD',
'ticker': 'GSTHHOLD'
}
}, {
'startDate': '2019-01-01',
'endDate': '2952-12-31',
'identifiers': {
'ric': '.GSTHHVIP',
'bbid': 'GSTHHVIP',
'cusip': '9EQ24FPE5',
'ticker': 'GSTHHVIP',
}
})
}
expected_response = (GsTemporalXRef(
dt.date(1952, 1, 1), dt.date(2018, 12, 31),
XRef(
ric='.GSTHHOLD',
bbid='GSTHHOLD',
cusip='9EQ24FOLD',
ticker='GSTHHOLD',
)),
GsTemporalXRef(
dt.date(2019, 1, 1), dt.date(2952, 12, 31),
XRef(
ric='.GSTHHVIP',
bbid='GSTHHVIP',
cusip='9EQ24FPE5',
ticker='GSTHHVIP',
)))
# mock GsSession
mocker.patch.object(GsSession.__class__,
'current',
return_value=GsSession.get(Environment.QA, 'client_id',
'secret'))
mocker.patch.object(GsSession.current, '_get', return_value=mock_response)
# run test
response = GsAssetApi.get_asset_xrefs(marquee_id)
GsSession.current._get.assert_called_with(
'/assets/{id}/xrefs'.format(id=marquee_id))
testfixtures.compare(response, expected_response)
def test_thematic_beta():
replace = Replacer()
# mock getting PTA report
mock = replace('gs_quant.markets.report.ThematicReport.get', Mock())
mock.return_value = ThematicReport(id='report_id')
# mock getting thematic exposure
mock = replace('gs_quant.markets.report.ThematicReport.get_thematic_betas',
Mock())
mock.return_value = pd.DataFrame(thematic_data)
# mock getting asset
mock = Stock('MAA0NE9QX2ABETG6', 'Test Asset')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs',
Mock())
xrefs.return_value = [
GsTemporalXRef(datetime.date(2019, 1, 1), datetime.date(2952, 12, 31),
XRef(ticker='basket_ticker', ))
]
replace('gs_quant.markets.securities.SecurityMaster.get_asset',
Mock()).return_value = mock
with DataContext(datetime.date(2020, 7, 12), datetime.date(2020, 7, 15)):
actual = mr.thematic_beta('report_id', 'basket_ticker')
assert all(actual.values == [1, 1, 1, 1])
replace.restore()
def test_swaption_vol():
replace = Replacer()
mock_usd = Currency('MA890', 'USD')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs',
Mock())
xrefs.return_value = [
GsTemporalXRef(dt.date(2019, 1, 1), dt.date(2952, 12, 31),
XRef(bbid='USD', ))
]
identifiers = replace(
'gs_quant.timeseries.measures.GsAssetApi.map_identifiers', Mock())
identifiers.return_value = {'USD-LIBOR-BBA': 'MA123'}
replace('gs_quant.timeseries.measures.GsDataApi.get_market_data',
mock_curr)
actual = tm.swaption_vol(mock_usd, '3m', '1y', 0)
assert_series_equal(
pd.Series([1, 2, 3], index=_index * 3, name='swaptionVol'), actual)
actual = tm.swaption_vol(mock_usd, '3m', '1y', 50)
assert_series_equal(
pd.Series([1, 2, 3], index=_index * 3, name='swaptionVol'), actual)
actual = tm.swaption_vol(mock_usd, '3m', '1y', -50)
assert_series_equal(
pd.Series([1, 2, 3], index=_index * 3, name='swaptionVol'), actual)
with pytest.raises(NotImplementedError):
tm.swaption_vol(..., '3m', '1y', 50, real_time=True)
replace.restore()
def test_vol_fx():
replace = Replacer()
mock = Cross('MAA0NE9QX2ABETG6', 'USD/EUR')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs', Mock())
xrefs.return_value = [GsTemporalXRef(dt.date(2019, 1, 1), dt.date(2952, 12, 31), XRef(bbid='EURUSD', ))]
replace('gs_quant.markets.securities.SecurityMaster.get_asset', mock)
# for different delta strikes
replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', mock_fx)
actual = tm.implied_volatility(mock, '1m', tm.VolReference.DELTA_CALL, 25)
assert_series_equal(pd.Series([5, 1, 2], index=_index * 3, name='impliedVolatility'), actual)
actual = tm.implied_volatility(mock, '1m', tm.VolReference.DELTA_PUT, 25)
assert_series_equal(pd.Series([5, 1, 2], index=_index * 3, name='impliedVolatility'), actual)
actual = tm.implied_volatility(mock, '1m', tm.VolReference.DELTA_NEUTRAL)
assert_series_equal(pd.Series([5, 1, 2], index=_index * 3, name='impliedVolatility'), actual)
actual = tm.implied_volatility(mock, '1m', tm.VolReference.FORWARD, 100)
assert_series_equal(pd.Series([5, 1, 2], index=_index * 3, name='impliedVolatility'), actual)
actual = tm.implied_volatility(mock, '1m', tm.VolReference.SPOT, 100)
assert_series_equal(pd.Series([5, 1, 2], index=_index * 3, name='impliedVolatility'), actual)
# NORMALIZED not supported
with pytest.raises(MqError):
tm.implied_volatility(mock, '1m', tm.VolReference.DELTA_CALL)
with pytest.raises(MqError):
tm.implied_volatility(mock, '1m', tm.VolReference.NORMALIZED, 25)
with pytest.raises(MqError):
tm.implied_volatility(mock, '1m', tm.VolReference.SPOT, 25)
with pytest.raises(MqError):
tm.implied_volatility(mock, '1m', tm.VolReference.FORWARD, 25)
replace.restore()
def query_data(cls, query: Union[DataQuery, MDAPIDataQuery], dataset_id: str = None,
asset_id_type: Union[GsIdType, str] = None) \
-> Union[MDAPIDataBatchResponse, DataQueryResponse, tuple]:
if isinstance(query, MDAPIDataQuery) and query.market_data_coordinates:
# Don't use MDAPIDataBatchResponse for now - it doesn't handle quoting style correctly
results: Union[MDAPIDataBatchResponse, dict] = GsSession.current._post(
'/data/coordinates/query', payload=query)
if isinstance(results, dict):
return results.get('responses', ())
else:
return results.responses if results.responses is not None else ()
elif isinstance(query, DataQuery) and query.where:
where = query.where.as_dict() if isinstance(query.where, FieldFilterMap) else query.where
xref_keys = set(where.keys()).intersection(XRef.properties())
if xref_keys:
# Check that assetId is a symbol dimension of this data set. If not, we need to do a separate query
# to resolve xref pip install dtaidistance--> assetId
if len(xref_keys) > 1:
raise MqValueError('Cannot not specify more than one type of asset identifier')
definition = cls.get_definition(dataset_id)
sd = definition.dimensions.symbolDimensions
if definition.parameters.symbolStrategy == 'MDAPI' or ('assetId' not in sd and 'gsid' not in sd):
xref_type = min(xref_keys)
if asset_id_type is None:
asset_id_type = xref_type
xref_values = where[asset_id_type]
xref_values = (xref_values,) if isinstance(xref_values, str) else xref_values
asset_id_map = GsAssetApi.map_identifiers(xref_type, GsIdType.id, xref_values)
if len(asset_id_map) != len(xref_values):
raise MqValueError('Not all {} were resolved to asset Ids'.format(asset_id_type))
setattr(query.where, xref_type, None)
query.where.assetId = [asset_id_map[x] for x in xref_values]
results: Union[DataQueryResponse, dict] = GsSession.current._post('/data/{}/query'.format(dataset_id),
payload=query)
if isinstance(results, dict):
results = results.get('data', ())
else:
results = results.data if results.data is not None else ()
if asset_id_type not in {GsIdType.id, None}:
asset_ids = tuple(set(filter(None, (r.get('assetId') for r in results))))
if asset_ids:
xref_map = GsAssetApi.map_identifiers(GsIdType.id, asset_id_type, asset_ids)
if len(xref_map) != len(asset_ids):
raise MqValueError('Not all asset Ids were resolved to {}'.format(asset_id_type))
for result in results:
result[asset_id_type] = xref_map[result['assetId']]
return results
def test_skew_fx():
replace = Replacer()
mock = Cross('MAA0NE9QX2ABETG6', 'USD/EUR')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs', Mock())
xrefs.return_value = [GsTemporalXRef(dt.date(2019, 1, 1), dt.date(2952, 12, 31), XRef(bbid='EURUSD', ))]
replace('gs_quant.markets.securities.SecurityMaster.get_asset', mock)
replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', mock_fx)
actual = tm.skew(Cross('MAA0NE9QX2ABETG6', 'USD/EUR'), '1m', None, 25)
assert_series_equal(pd.Series([2.0], index=_index, name='impliedVolatility'), actual)
replace.restore()
def test_basis():
replace = Replacer()
mock_jpyusd = Cross('MA890', 'USD/JPY')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs', Mock())
xrefs.return_value = [GsTemporalXRef(dt.date(2019, 1, 1), dt.date(2952, 12, 31), XRef(bbid='JPYUSD', ))]
identifiers = replace('gs_quant.timeseries.measures.GsAssetApi.map_identifiers', Mock())
identifiers.return_value = {'USD-3m/JPY-3m': 'MA123'}
replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', mock_cross)
actual = tm.basis(mock_jpyusd, '1y')
assert_series_equal(pd.Series([1, 2, 3], index=_index * 3, name='basis'), actual)
with pytest.raises(NotImplementedError):
tm.basis(..., '1y', real_time=True)
replace.restore()
def test_zc_inflation_swap_rate():
replace = Replacer()
mock_gbp = Currency('MA890', 'GBP')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs', Mock())
xrefs.return_value = [GsTemporalXRef(dt.date(2019, 1, 1), dt.date(2952, 12, 31), XRef(bbid='GBP', ))]
identifiers = replace('gs_quant.timeseries.measures.GsAssetApi.map_identifiers', Mock())
identifiers.return_value = {'CPI-UKRPI': 'MA123'}
replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', mock_curr)
actual = tm.zc_inflation_swap_rate(mock_gbp, '1y')
assert_series_equal(pd.Series([1, 2, 3], index=_index * 3, name='inflationSwapRate'), actual)
with pytest.raises(NotImplementedError):
tm.zc_inflation_swap_rate(..., '1y', real_time=True)
replace.restore()
def test_vol_forecast():
replace = Replacer()
mock = Cross('MAA0NE9QX2ABETG6', 'USD/EUR')
xrefs = replace('gs_quant.timeseries.measures.GsAssetApi.get_asset_xrefs', Mock())
xrefs.return_value = [GsTemporalXRef(dt.date(2019, 1, 1), dt.date(2952, 12, 31), XRef(bbid='EURUSD', ))]
replace('gs_quant.markets.securities.SecurityMaster.get_asset', mock)
replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', mock_fx)
actual = tm.forecast(mock, '1y')
assert_series_equal(pd.Series([1.1, 1.1, 1.1], index=_index * 3, name='forecast'), actual)
actual = tm.forecast(mock, '3m')
assert_series_equal(pd.Series([1.1, 1.1, 1.1], index=_index * 3, name='forecast'), actual)
with pytest.raises(NotImplementedError):
tm.forecast(mock, '1y', real_time=True)
replace.restore()
# Helper mock value constants
asset_1 = {'name': 'asset 1', 'id': 'id1', 'bbid': 'bbid1'}
asset_2 = {'name': 'asset 2', 'id': 'id2', 'bbid': 'bbid2'}
assets_data = [asset_1, asset_2]
base_user = {
'name': 'First Last',
'email': '*****@*****.**',
'company': 'Company A'
}
cb_response = CustomBasketsResponse('done', 'R1234567890', 'MA1234567890')
gs_asset = GsAsset(asset_class=AssetClass.Equity,
type_=AssetType.Custom_Basket,
name='Test Basket',
id_='MA1234567890',
entitlements=TargetEntitlements(admin=['guid:user_abc']),
xref=XRef(ticker='GSMBXXXX'))
initial_price = {'price': 100}
mqid = 'MA1234567890'
name = 'Test Basket'
positions = [
Position('bbid1', asset_id='id1', quantity=100),
Position('bbid2', asset_id='id2', quantity=200)
]
positions_weighted = positions = [
Position('bbid1', asset_id='id1', weight=0.4),
Position('bbid2', asset_id='id2', weight=0.6)
]
position_set = PositionSet(positions, divisor=1000)
report = Report(mqid,
'asset',
'Basket Create',
