def test_get_risk_model(mocker):
model_id = 'WW_TEST_MODEL'
model = RiskModel.from_dict({
"coverage": "Global",
"id": "WW_TEST_MODEL",
"name": "World Wide Medium Term Test Model",
"term": "Medium",
"vendor": "Goldman Sachs",
"universeIdentifier": "gsid",
"version": 4
})
expected_response = RiskModel(coverage='Global',
id='WW_TEST_MODEL',
name='World Wide Medium Term Test Model',
term='Medium',
vendor='Goldman Sachs',
version=4,
universe_identifier='gsid')
# mock GsSession
mocker.patch.object(GsSession.__class__,
'default_value',
return_value=GsSession.get(Environment.QA, 'client_id',
'secret'))
mocker.patch.object(GsSession.current, '_get', return_value=model)
# run test
response = GsRiskModelApi.get_risk_model(model_id)
GsSession.current._get.assert_called_with(
'/risk/models/{id}'.format(id=model_id), cls=RiskModel)
assert response == expected_response
def test_get_risk_models(mocker):
mock_response = {
'results': [
RiskModel.from_dict({
"coverage": "Global",
"id": "WW_TEST_MODEL",
"name": "World Wide Medium Term Test Model",
"term": "Medium",
"vendor": "Goldman Sachs",
"universeIdentifier": "gsid",
"type": "Factor",
"version": 4
}),
RiskModel.from_dict({
"coverage": "Global",
"id": "WW_TEST_MODEL_2",
"name": "World Wide Medium Term Test Model 2",
"term": "Medium",
"vendor": "Goldman Sachs",
"universeIdentifier": "gsid",
"version": 2,
"type": "Thematic"
})
],
'totalResults':
2
}
expected_response = [
RiskModel(coverage='Global',
id='WW_TEST_MODEL',
name='World Wide Medium Term Test Model',
term='Medium',
vendor='Goldman Sachs',
universe_identifier='gsid',
version=4,
type='Factor'),
RiskModel(coverage='Global',
id='WW_TEST_MODEL_2',
name='World Wide Medium Term Test Model 2',
term='Medium',
vendor='Goldman Sachs',
universe_identifier='gsid',
version=2,
type='Thematic')
]
# mock GsSession
mocker.patch.object(GsSession.__class__,
'default_value',
return_value=GsSession.get(Environment.QA, 'client_id',
'secret'))
mocker.patch.object(GsSession.current, '_get', return_value=mock_response)
# run test
response = GsRiskModelApi.get_risk_models()
GsSession.current._get.assert_called_with('/risk/models?', cls=RiskModel)
assert response == expected_response
def test_update_risk_model(mocker):
model = RiskModel.from_dict({
"coverage": "Global",
"id": "WW_TEST_MODEL",
"name": "World Wide Medium Term Test Model",
"term": "Medium",
"vendor": "Goldman Sachs",
"universeIdentifier": "gsid",
"version": 4
})
# mock GsSession
mocker.patch.object(
GsSession.__class__,
'default_value',
return_value=GsSession.get(
Environment.QA,
'client_id',
'secret'))
mocker.patch.object(GsSession.current, '_put', return_value=model)
# run test
response = GsRiskModelApi.update_risk_model(model)
GsSession.current._put.assert_called_with('/risk/models/{id}'.format(id='WW_TEST_MODEL'), model, cls=RiskModel)
assert response == model
def mock_risk_model():
risk_model = RiskModel(coverage=CoverageType.Country, id_='model_id', name='Fake Risk Model',
term=Term.Long, universe_identifier=UniverseIdentifier.gsid, vendor='GS',
version=1.0)
replace = Replacer()
# mock getting risk model entity()
mock = replace('gs_quant.api.gs.risk_models.GsRiskModelApi.get_risk_model', Mock())
mock.return_value = risk_model
actual = Risk_Model(model_id='model_id')
replace.restore()
return actual
def test_covariance():
risk_model = RiskModel(coverage=CoverageType.Country, id_='model_id', name='Fake Risk Model',
term=Term.Long, universe_identifier=UniverseIdentifier.gsid, vendor='GS',
version=1.0)
covariances = [
{
'date': '2020-01-01',
'covariance': 1.01
},
{
'date': '2020-01-02',
'covariance': 1.02
},
{
'date': '2020-01-03',
'covariance': 1.03
},
]
replace = Replacer()
# mock getting risk model factor entity
mock = replace('gs_quant.api.gs.risk_models.GsRiskModelApi.get_risk_model_factor_data', Mock())
mock.return_value = [{
'identifier': 'factor_id',
'type': 'Factor',
'name': "Factor Name"
}]
# mock getting risk model entity()
mock = replace('gs_quant.api.gs.risk_models.GsRiskModelApi.get_risk_model', Mock())
mock.return_value = risk_model
# mock getting risk model dates
mock = replace('gs_quant.api.gs.risk_models.GsRiskModelApi.get_risk_model_dates', Mock())
mock.return_value = ['2020-01-01', '2020-01-02', '2020-01-03']
# mock getting covariances
mock = replace('gs_quant.markets.factor.Factor.get_covariance', Mock())
mock.return_value = covariances
with DataContext(datetime.date(2020, 1, 1), datetime.date(2020, 1, 3)):
actual = mrm.covariance(mock_risk_model(), 'Factor Name', 'Factor Name')
assert all(actual.values == [1.01, 1.02, 1.03])
with pytest.raises(MqValueError):
mrm.covariance(mock_risk_model(), 'Wrong Factor Name', 'Factor Name')
replace.restore()
import datetime
import pytest
from testfixtures import Replacer
from testfixtures.mock import Mock
import gs_quant.timeseries.measures_reports as mr
from gs_quant.data.core import DataContext
from gs_quant.errors import MqValueError
from gs_quant.markets.risk_model import RiskModel as Risk_Model
from gs_quant.target.common import ReportParameters
from gs_quant.target.reports import Report, PositionSourceType, ReportType
from gs_quant.target.risk_models import RiskModel, CoverageType, Term, UniverseIdentifier
risk_model = RiskModel(coverage=CoverageType.Country, id_='model_id', name='Fake Risk Model',
term=Term.Long, universe_identifier=UniverseIdentifier.gsid, vendor='GS',
version=1.0)
factor_risk_report = Report(position_source_id='position source id',
position_source_type=PositionSourceType.Portfolio,
type_=ReportType.Portfolio_Factor_Risk,
id_='report_id',
parameters=ReportParameters(risk_model='risk_model_id'))
ppa_report = Report(position_source_id='position source id',
position_source_type=PositionSourceType.Portfolio,
type_=ReportType.Portfolio_Performance_Analytics,
id_='report_id',
parameters=ReportParameters(risk_model='risk_model_id'))
factor_data = [
import pandas as pd
import pytest
from testfixtures import Replacer
from testfixtures.mock import Mock
import gs_quant.timeseries.measures_risk_models as mrm
from gs_quant.data.core import DataContext
from gs_quant.errors import MqValueError
from gs_quant.models.risk_model import FactorRiskModel as Factor_Risk_Model
from gs_quant.markets.securities import Stock
from gs_quant.target.risk_models import RiskModel, RiskModelCoverage, RiskModelTerm, RiskModelUniverseIdentifier
mock_risk_model_obj = RiskModel(
id_='model_id',
name='Fake Risk Model',
coverage=RiskModelCoverage.Country,
term=RiskModelTerm.Long,
universe_identifier=RiskModelUniverseIdentifier.gsid,
vendor='GS',
version=1.0)
mock_risk_model_data = {
'totalResults':
2,
'missingDates': [],
'results': [{
'date':
'2020-01-01',
'factorData': [
{
'factorId': '1',
'factorCategory': 'Style'
def test_factor_exposure():
risk_model = RiskModel(coverage=CoverageType.Country, id_='model_id', name='Fake Risk Model',
term=Term.Long, universe_identifier=UniverseIdentifier.gsid, vendor='GS',
version=1.0)
risk_model_data = {
'results': [
{
'date': '2020-01-01',
'assetData': {
'factorExposure': [
{
'factor_id': 1.01,
'factor_id_1': 1.23
}
]
}
},
{
'date': '2020-01-02',
'assetData': {
'factorExposure': [
{
'factor_id': 1.02,
'factor_id_1': 1.23
}
]
}
},
{
'date': '2020-01-03',
'assetData': {
'factorExposure': [
{
'factor_id': 1.03,
'factor_id_1': 1.23
}
]
}
}
]
}
replace = Replacer()
# mock getting risk model entity()
mock = replace('gs_quant.api.gs.risk_models.GsRiskModelApi.get_risk_model', Mock())
mock.return_value = risk_model
# mock getting risk model factor entity
mock = replace('gs_quant.api.gs.risk_models.GsRiskModelApi.get_risk_model_factor_data', Mock())
mock.return_value = [{
'identifier': 'factor_id',
'type': 'Factor',
'name': "Factor Name"
}]
# mock getting asset gsid
mock = replace('gs_quant.markets.securities.Asset.get_identifiers', Mock())
mock.return_value = {'GSID': '12345'}
# mock getting risk model dates
mock = replace('gs_quant.api.gs.risk_models.GsRiskModelApi.get_risk_model_dates', Mock())
mock.return_value = ['2020-01-01', '2020-01-02', '2020-01-03']
# mock getting risk model data
mock = replace('gs_quant.markets.risk_model.RiskModel.get_data', Mock())
mock.return_value = risk_model_data
with DataContext(datetime.date(2020, 1, 1), datetime.date(2020, 1, 3)):
actual = mrm.factor_exposure(Stock(id_='id', name='Fake Asset'), 'model_id', 'Factor Name')
assert all(actual.values == [1.01, 1.02, 1.03])
with pytest.raises(MqValueError):
mrm.factor_exposure(Stock(id_='id', name='Fake Asset'), 'model_id', 'Wrong Factor Name')
replace.restore()
