def get_specific_risk(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
limit_factors: bool = None,
data_format: Format = None) -> Dict:
""" Retrieve specific risk data for existing risk model """
return GsRiskModelApi.get_risk_model_data(self.model.id, start_date,
end_date, assets,
[Measure.Specific_Risk],
limit_factors, data_format)
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)
def get_factor_portfolios(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
data_format: Format = None) -> Dict:
""" Retrieve factor portfolios 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.Factor_Portfolios],
limit_factors=False,
data_format=data_format)
def get_issuer_specific_covariance(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
data_format: Format = None) -> Dict:
""" Retrieve issuer specific covariance 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.Issuer_Specific_Covariance],
limit_factors=False,
data_format=data_format)
def get_residual_variance(self,
start_date: dt.date,
end_date: dt.date,
assets: DataAssetsRequest = None,
data_format: Format = None) -> Dict:
""" Retrieve residual variance 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.Residual_Variance, Measure.Asset_Universe],
limit_factors=False,
data_format=data_format)
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(model_id=self.model.id,
start_date=start_date,
end_date=end_date,
assets=assets,
measures=measures,
limit_factors=limit_factors,
data_format=data_format)
def get_specific_risk(self,
start_date: dt.date,
end_date: dt.date = None,
assets: DataAssetsRequest = None,
data_format: Format = None) -> Dict:
""" Retrieve specific risk data for existing risk model """
results = GsRiskModelApi.get_risk_model_data(
model_id=self.model.id,
start_date=start_date,
end_date=end_date,
assets=assets,
measures=[Measure.Specific_Risk, Measure.Asset_Universe],
limit_factors=False,
data_format=data_format).get('results')
return _build_asset_data_map(results, assets, 'specificRisk')
def get_factor_returns(self,
start_date: dt.date,
end_date: dt.date,
data_format: Format = None) -> Dict:
""" Retrieve factor return 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=None,
measures=[
Measure.Factor_Return,
Measure.Factor_Name,
Measure.Factor_Id
],
limit_factors=False,
data_format=data_format)
def get_covariance_matrix(self,
start_date: dt.date,
end_date: dt.date = None,
data_format: Format = None) -> Dict:
""" Retrieve covariance matrix 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=None,
measures=[
Measure.Covariance_Matrix, Measure.Factor_Name,
Measure.Factor_Id
],
limit_factors=False,
data_format=data_format).get('results')
def get_factor_returns_by_id(self,
start_date: dt.date,
end_date: dt.date = None,
data_format: Format = None) -> Dict:
""" Retrieve factor return data for existing risk model """
results = GsRiskModelApi.get_risk_model_data(
model_id=self.model.id,
start_date=start_date,
end_date=end_date,
assets=None,
measures=[
Measure.Factor_Return, Measure.Factor_Name, Measure.Factor_Id
],
limit_factors=False,
data_format=data_format).get('results')
factor_data = self.get_factor_data(start_date, end_date)
return _build_factor_data_map(factor_data, results, 'id')
def get_universe_factor_exposure(self,
start_date: dt.date,
end_date: dt.date = None,
assets: DataAssetsRequest = None,
data_format: Format = None) -> Dict:
""" Retrieve universe factor exposure data for existing risk model """
results = GsRiskModelApi.get_risk_model_data(
model_id=self.model.id,
start_date=start_date,
end_date=end_date,
assets=assets,
measures=[
Measure.Universe_Factor_Exposure, Measure.Asset_Universe
],
limit_factors=False,
data_format=data_format).get('results')
return _build_asset_data_map(results, assets, 'factorExposure')
def get_asset_universe(self,
start_date: dt.date,
end_date: dt.date = None,
assets: DataAssetsRequest = None,
data_format: Format = None) -> List:
""" Retrieve asset universe data for existing risk model """
if not assets.universe and not end_date:
end_date = start_date
results = GsRiskModelApi.get_risk_model_data(
model_id=self.model.id,
start_date=start_date,
end_date=end_date,
assets=assets,
measures=[Measure.Asset_Universe],
limit_factors=False,
data_format=data_format).get('results')
return [{
'date': data.get('date'),
'universe': data.get('assetData').get('universe')
} for data in results]
def get_residual_variance(self,
start_date: dt.date,
end_date: dt.date = None,
assets: DataAssetsRequest = None,
data_format: Format = None) -> Dict:
""" Retrieve residual variance data for existing risk model """
if not assets:
assets = DataAssetsRequest(UniverseIdentifier.gsid, [])
if assets.identifier != UniverseIdentifier.gsid:
raise ValueError(
'Cannot query residual variance by identifiers other than gsid'
)
results = GsRiskModelApi.get_risk_model_data(
model_id=self.model.id,
start_date=start_date,
end_date=end_date,
assets=assets,
measures=[Measure.Residual_Variance, Measure.Asset_Universe],
limit_factors=False,
data_format=data_format).get('results')
return _build_asset_data_map(results, assets, 'residualVariance')
