def covariance(self,
factor,
start_date: date = DataContext.current.start_date,
end_date: date = DataContext.current.end_date) -> Dict:
""" Retrieve a Dictionary of date->covariance values between this factor and another for a date range """
covariance_data_raw = GsDataApi.execute_query(
'RISK_MODEL_COVARIANCE_MATRIX',
DataQuery(
where={"riskModel": self.risk_model_id, "factorId": self.id},
start_date=start_date,
end_date=end_date
)
).get('data', [])
date_to_matrix_order = factor.__matrix_order(start_date, end_date)
covariance_data = {}
for data in covariance_data_raw:
date = data['date']
if date_to_matrix_order.get(date):
matrix_order_on_date = date_to_matrix_order[date]
covariance_data[date] = data[matrix_order_on_date]
return covariance_data
def returns(
self,
start_date: date = DataContext.current.start_date,
end_date: date = DataContext.current.end_date,
format: ReturnFormat = ReturnFormat.DATA_FRAME
) -> Union[Dict, pd.DataFrame]:
""" Retrieve a Dataframe or Dictionary of date->factor return values for a date range """
appendage = self.__get_dataset_trial_appendage()
data_query_results = GsDataApi.execute_query(
f'RISK_MODEL_FACTOR{appendage}',
DataQuery(where={
"riskModel": self.risk_model_id,
"factorId": self.id
},
fields=['return'],
start_date=start_date,
end_date=end_date)).get('data', [])
return_data = {
factor_data['date']: factor_data['return']
for factor_data in data_query_results if factor_data.get('return')
}
if format == ReturnFormat.DATA_FRAME:
return pd.DataFrame.from_dict(return_data,
orient='index',
columns=['return'])
return return_data
def covariance(
self,
factor,
start_date: date = DataContext.current.start_date,
end_date: date = DataContext.current.end_date,
format: ReturnFormat = ReturnFormat.DATA_FRAME
) -> Union[Dict, pd.DataFrame]:
""" Retrieve a Dataframe or Dictionary of date->covariance values between this factor and another for a date
range """
covariance_data_raw = GsDataApi.execute_query(
'RISK_MODEL_COVARIANCE_MATRIX',
DataQuery(where={
"riskModel": self.risk_model_id,
"factorId": self.id
},
start_date=start_date,
end_date=end_date)).get('data', [])
date_to_matrix_order = factor.__matrix_order(start_date, end_date)
covariance_data = {}
for data in covariance_data_raw:
date = data['date']
if date_to_matrix_order.get(date):
matrix_order_on_date = date_to_matrix_order[date]
covariance_data[date] = data[matrix_order_on_date]
if format == ReturnFormat.DATA_FRAME:
return pd.DataFrame.from_dict(covariance_data,
orient='index',
columns=['covariance'])
return covariance_data
def __matrix_order(self, start_date: date, end_date: date) -> Dict:
""" Retrieve Dictionary of date->matrix_order for the factor in the covariance matrix """
query_results = GsDataApi.execute_query(
'RISK_MODEL_COVARIANCE_MATRIX',
DataQuery(
where={"riskModel": self.risk_model_id, "factorId": self.id},
fields=['matrixOrder'],
start_date=start_date,
end_date=end_date
)
).get('data', [])
return {data['date']: str(data['matrixOrder']) for data in query_results}
def get_covariance(self, factor, start_date: date, end_date: date) -> List:
""" Retrieve a list of covariances between this factor and another for a range of dates """
covariance_data = []
# Collect matrix order for requested factor on all available dates
query = DataQuery(where={
"riskModel": self.risk_model_id,
"factorId": factor.factor.identifier
},
start_date=start_date,
end_date=end_date)
factor_covariances = GsDataApi.execute_query(
'RISK_MODEL_COVARIANCE_MATRIX', query).get('data', [])
matrix_order_map = {
data['date']: data['matrixOrder']
for data in factor_covariances
}
# Collect covariances at relevant matrix order on all available dates
query = DataQuery(where={
"riskModel": self.risk_model_id,
"factorId": self.factor.identifier
},
start_date=start_date,
end_date=end_date)
factor_covariances = GsDataApi.execute_query(
'RISK_MODEL_COVARIANCE_MATRIX', query).get('data', [])
for data in factor_covariances:
date = data['date']
if matrix_order_map.get(date):
covariance_data.append({
'date':
date,
'covariance':
data[str(matrix_order_map[date])]
})
return covariance_data