def get_factor_data(self,
start_date: dt.date = None,
end_date: dt.date = None,
identifiers: List[str] = None,
include_performance_curve: bool = None) -> List[Dict]:
""" Retrieve factor data for existing risk model """
start_date = dt.datetime.strptime(
GsRiskModelApi.get_risk_model_dates(self.model.id)[0],
'%Y-%m-%d') if not start_date else start_date
id_to_category_for_date_range = GsRiskModelApi.get_risk_model_data(
model_id=self.model.id,
start_date=start_date,
end_date=end_date,
assets=None,
measures=[Measure.Factor_Id, Measure.Factor_Category],
limit_factors=False,
data_format=None).get('results')
factor_id_to_category = _build_id_to_category(
id_to_category_for_date_range)
factor_data = GsRiskModelApi.get_risk_model_factor_data(
self.model.id, start_date, end_date, identifiers,
include_performance_curve)
for factor in factor_data:
factor['factorCategory'] = factor_id_to_category.get(
factor.get('identifier'), factor.get('name'))
return factor_data
def create(cls,
coverage: Union[CoverageType, str],
id_: str,
name: str,
term: Union[Term, str],
universe_identifier: Union[UniverseIdentifier, str],
vendor: str,
version: float,
entitlements: Union[Entitlements, Dict] = None,
description: str = None):
""" Creates new factor risk model and uploads factor risk model object to Marquee
:param coverage: coverage of risk model asset universe
:param id_: risk model id (cannot be changed)
:param name: risk model name
:param term: horizon term
:param universe_identifier: identifier used in asset universe upload (cannot be changed)
:param vendor: risk model vendor
:param version: version of model
:param entitlements: entitlements associated with risk model
:param description: risk model description
:return: Factor Risk Model object """
new_model = RiskModelBuilder(coverage,
id_,
name,
term,
universe_identifier,
vendor,
version,
entitlements=entitlements,
description=description)
GsRiskModelApi.create_risk_model(new_model)
return FactorRiskModel(id_)
def upload_partial_data(self,
data: RiskModelData,
target_universe_size: float = None):
""" Upload partial risk model data to existing risk model, if repeats in partial upload,
newer posted data will replace existing data on upload day """
GsRiskModelApi.upload_risk_model_data(
self.model.id,
data,
partial_upload=True,
target_universe_size=target_universe_size)
def update(self):
""" Updates factor risk model object on Marquee """
updated_model = RiskModelBuilder(self.coverage,
self.id,
self.name,
self.term,
self.universe_identifier,
self.vendor,
self.version,
description=self.description,
entitlements=self.entitlements)
GsRiskModelApi.update_risk_model(updated_model)
def upload(self):
""" Upload current Factor Risk Model object to Marquee """
new_model = RiskModelBuilder(self.coverage,
self.id,
self.name,
self.term,
self.universe_identifier,
self.vendor,
self.version,
entitlements=self.entitlements,
description=self.description)
GsRiskModelApi.create_risk_model(new_model)
def get_many(cls,
ids: List[str] = None,
terms: List[str] = None,
vendors: List[str] = None,
names: List[str] = None,
coverages: List[str] = None,
limit: int = None):
""" Get a factor risk model from Marquee
:param ids: list of model identifiers in Marquee
:param terms: list of model terms
:param vendors: list of model vendors
:param names: list of model names
:param coverages: list of model coverages
:param limit: limit of number of models in response
:return: Factor Risk Model object
"""
models = GsRiskModelApi.get_risk_models(ids=ids,
terms=terms,
vendors=vendors,
names=names,
coverages=coverages,
limit=limit)
return cls.from_many_targets(models)
def get(cls, model_id: str):
""" Get a risk model from Marquee
:param model_id: risk model id corresponding to Marquee Risk Model
:return: Risk Model object
"""
model = GsRiskModelApi.get_risk_model(model_id)
return cls.from_target(model)
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_model_coverage(mocker):
results = {
"results": [
RiskModelFactor.from_dict({
"model": "AXUS4S",
"businessDate": "2020-11-02"
}),
RiskModelFactor.from_dict({
"model": "AXAU4M",
"businessDate": "2020-11-03"
})
]
}
# mock GsSession
mocker.patch.object(GsSession.__class__,
'default_value',
return_value=GsSession.get(Environment.QA, 'client_id',
'secret'))
mocker.patch.object(GsSession.current, '_post', return_value=results)
# run test
response = GsRiskModelApi.get_risk_model_coverage()
GsSession.current._post.assert_called_with('/risk/models/coverage', {})
assert response == results['results']
def remove_entitlements(self, entitlements: Union[Entitlements, Dict]):
""" Removes entitlements for existing risk model """
entitlements = Entitlements.from_dict(entitlements) if type(
entitlements) == dict else entitlements
model = GsRiskModelApi.get_risk_model(self.__id)
edit_ls = list(model.entitlements.edit)
for edit in entitlements.edit:
edit_ls.remove(edit)
admin_ls = list(model.entitlements.admin)
for admin in entitlements.admin:
admin_ls.remove(admin)
query_ls = list(model.entitlements.query)
for query in entitlements.query:
query_ls.remove(query)
upload_ls = list(model.entitlements.upload)
for upload in entitlements.upload:
upload_ls.remove(upload)
view_ls = list(model.entitlements.view)
for view in entitlements.view:
view_ls.remove(view)
execute_ls = list(model.entitlements.execute)
for execute in entitlements.execute:
execute_ls.remove(execute)
removed_entitlements = Entitlements(edit=tuple(edit_ls),
admin=tuple(admin_ls),
query=tuple(query_ls),
upload=tuple(upload_ls),
view=tuple(view_ls),
execute=tuple(execute_ls))
self.entitlements = removed_entitlements
def test_get_risk_model_factors(mocker):
factors = {
'results': [
RiskModelFactor.from_dict({
"type": "Factor",
"identifier": "Factor1"
}),
RiskModelFactor.from_dict({
"type": "Category",
"identifier": "Factor2"
})
],
'totalResults':
2
}
expected_response = [
RiskModelFactor(identifier='Factor1', type='Factor'),
RiskModelFactor(identifier='Factor2', type='Category')
]
# 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=factors)
# run test
response = GsRiskModelApi.get_risk_model_factors(model_id='id')
GsSession.current._get.assert_called_with('/risk/models/id/factors',
cls=RiskModelFactor)
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 __init__(self, model_id: str):
model = GsRiskModelApi.get_risk_model(model_id)
self.__id: str = model.id
self.__name: str = model.name
self.__description: str = model.description
self.__entitlements: Entitlements = model.entitlements if type(model.entitlements) == Entitlements or not \
model.entitlements else Entitlements.from_dict(model.entitlements)
def get_dates(self,
start_date: dt.date = None,
end_date: dt.date = None) -> List:
""" Retrieve risk model dates for existing risk model
:param start_date: list returned including and after start_date
:param end_date: list returned up to and including end_date """
return GsRiskModelApi.get_risk_model_dates(self.id, start_date,
end_date)
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 get_factor_data(self,
start_date: dt.date = None,
end_date: dt.date = None,
identifiers: List[str] = None,
include_performance_curve: bool = None) -> List[Dict]:
""" Retrieve factor data for existing risk model """
return GsRiskModelApi.get_risk_model_factor_data(
self.model.id, start_date, end_date, identifiers,
include_performance_curve)
def __init__(self, model_id: str):
super().__init__(model_id)
model = GsRiskModelApi.get_risk_model(model_id)
self.__coverage: Union[CoverageType, str] = model.coverage
self.__term: Union[Term, str] = model.term
self.__universe_identifier: Union[UniverseIdentifier,
str] = model.universe_identifier
self.__vendor: str = model.vendor
self.__version: float = model.version
def test_get_risk_model_data(mocker):
query = {'startDate': '2020-01-01', 'endDate': '2020-03-03'}
results = {
'results': [{
'date':
'2020-02-05',
'assetData': {
'universe': ['2407966', '2046251', 'USD'],
'specificRisk': [12.09, 45.12, 3.09],
'factorExposure': [{
'1': 0.23,
'2': 0.023
}],
'historicalBeta': [0.12, 0.45, 1.2]
},
'factorData': [{
'factorId': '1',
'factorName': 'USD',
'factorCategory': 'Currency',
'factorCategoryId': 'CUR'
}],
'covarianceMatrix': [[0.089, 0.0123, 0.345]],
'issuerSpecificCovariance': {
'universeId1': ['2407966'],
'universeId2': ['2046251'],
'covariance': [0.03754]
},
'factorPortfolios': {
'universe': ['2407966', '2046251'],
'portfolio': [{
'factorId': 2,
'weights': [0.25, 0.75]
}]
}
}],
'totalResults':
1,
'missingDates': []
}
# mock GsSession
mocker.patch.object(GsSession.__class__,
'default_value',
return_value=GsSession.get(Environment.QA, 'client_id',
'secret'))
mocker.patch.object(GsSession.current, '_post', return_value=results)
# run test
response = GsRiskModelApi.get_risk_model_data(model_id='id',
start_date=dt.date(
2020, 1, 1),
end_date=dt.date(2020, 3, 3))
GsSession.current._post.assert_called_with(
'/risk/models/data/{id}/query'.format(id='id'), query)
assert response == results
def get_issuer_specific_covariance(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
limit_factors: bool = None,
data_format: Format = None) -> Dict:
""" Retrieve issuer specific covariance data for existing risk model """
return GsRiskModelApi.get_risk_model_data(
self.model.id, start_date, end_date, assets,
[Measure.Issuer_Specific_Covariance], limit_factors, data_format)
def save(self):
""" Upload current Risk Model object to Marquee """
model = RiskModelBuilder(
self.coverage,
self.id,
self.name,
self.term,
self.universe_identifier,
self.vendor,
self.version,
type_=self.type,
description=self.description,
entitlements=self.entitlements,
expected_update_time=self.expected_update_time.strftime('%H:%M:%S')
if self.expected_update_time else None)
try:
GsRiskModelApi.create_risk_model(model)
except MqRequestError:
GsRiskModelApi.update_risk_model(model)
def get_universe_factor_exposure(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
limit_factors: bool = None,
data_format: Format = None) -> Dict:
""" Retrieve universe factor exposure data for existing risk model """
return GsRiskModelApi.get_risk_model_data(
self.model.id, start_date, end_date, assets,
[Measure.Universe_Factor_Exposure], limit_factors, data_format)
def get_calendar(self, start_date: dt.date = None, end_date: dt.date = None) -> RiskModelCalendar:
""" Get risk model calendar for existing risk model between start and end date
:param start_date: list returned including and after start_date
:param end_date: list returned up to and including end_date """
calendar = GsRiskModelApi.get_risk_model_calendar(self.id)
if not start_date and not end_date:
return calendar
start_idx = get_closest_date_index(start_date, calendar.business_dates, 'after') if start_date else 0
end_idx = get_closest_date_index(end_date, calendar.business_dates, 'before') if end_date else len(
calendar.business_dates)
return RiskModelCalendar(calendar.business_dates[start_idx:end_idx + 1])
def get_data(self,
measures: List[Measure],
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
limit_factors: bool = None,
data_format: Format = None) -> Dict:
""" Retrieve data for multiple measures for existing risk model """
return GsRiskModelApi.get_risk_model_data(self.model.id, start_date,
end_date, assets, measures,
limit_factors, data_format)
def get_total_risk(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
limit_factors: bool = None,
data_format: Format = None) -> Dict:
""" Retrieve total risk data for existing risk model """
return GsRiskModelApi.get_risk_model_data(self.model.id, start_date,
end_date, assets,
[Measure.Total_Risk],
limit_factors, data_format)
def get_historical_beta(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
limit_factors: bool = None,
data_format: Format = None) -> Dict:
""" Retrieve historical beta data for existing risk model """
return GsRiskModelApi.get_risk_model_data(self.model.id, start_date,
end_date, assets,
[Measure.Historical_Beta],
limit_factors, data_format)
def get_residual_variance(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
limit_factors: bool = None,
data_format: Format = None) -> Dict:
""" Retrieve residual variance data for existing risk model """
return GsRiskModelApi.get_risk_model_data(self.model.id, start_date,
end_date, assets,
[Measure.Residual_Variance],
limit_factors, data_format)
def get_factor_portfolios(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
limit_factors: bool = None,
data_format: Format = None) -> Dict:
""" Retrieve factor portfolios data for existing risk model """
return GsRiskModelApi.get_risk_model_data(self.model.id, start_date,
end_date, assets,
[Measure.Factor_Portfolios],
limit_factors, data_format)
def get_covariance_matrix(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
limit_factors: bool = None,
data_format: Format = None) -> Dict:
""" Retrieve covariance matrix data for existing risk model """
return GsRiskModelApi.get_risk_model_data(self.model.id, start_date,
end_date, assets,
[Measure.Covariance_Matrix],
limit_factors, data_format)
def test_upload_risk_model_data(mocker):
risk_model_data = {
'date':
'2020-02-05',
'assetData': {
'universe': ['2407966', '2046251', 'USD'],
'specificRisk': [12.09, 45.12, 3.09],
'factorExposure': [{
'1': 0.23,
'2': 0.023
}],
'historicalBeta': [0.12, 0.45, 1.2]
},
'factorData': [{
'factorId': '1',
'factorName': 'USD',
'factorCategory': 'Currency',
'factorCategoryId': 'CUR'
}],
'covarianceMatrix': [[0.089, 0.0123, 0.345]],
'issuerSpecificCovariance': {
'universeId1': ['2407966'],
'universeId2': ['2046251'],
'covariance': [0.03754]
},
'factorPortfolios': {
'universe': ['2407966', '2046251'],
'portfolio': [{
'factorId': 2,
'weights': [0.25, 0.75]
}]
}
}
# mock GsSession
mocker.patch.object(GsSession.__class__,
'default_value',
return_value=GsSession.get(Environment.QA, 'client_id',
'secret'))
mocker.patch.object(GsSession.current,
'_post',
return_value=risk_model_data)
# run test
response = GsRiskModelApi.upload_risk_model_data(
model_id='id', model_data=risk_model_data)
GsSession.current._post.assert_called_with(
'/risk/models/data/{id}'.format(id='id'),
risk_model_data,
cls=RiskModelData)
assert response == risk_model_data
def get_historical_beta(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
data_format: Format = None) -> Dict:
""" Retrieve historical beta data for existing risk model """
return GsRiskModelApi.get_risk_model_data(
model_id=self.model.id,
start_date=start_date,
end_date=end_date,
assets=assets,
measures=[Measure.Historical_Beta, Measure.Asset_Universe],
limit_factors=False,
data_format=data_format)
