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 thematic_beta(report_id: str,
basket_ticker: str,
*,
source: str = None,
real_time: bool = False,
request_id: Optional[str] = None) -> pd.Series:
"""
Thematic beta values of a portfolio to a requested GS thematic flagship basket
:param report_id: portfolio thematic analytics report id
:param basket_ticker: ticker for thematic basket
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:param request_id: server request id
:return: Timeseries of daily thematic beta of portfolio to requested flagship basket
"""
thematic_report = ThematicReport.get(report_id)
asset = SecurityMaster.get_asset(basket_ticker, AssetIdentifier.TICKER)
df = thematic_report.get_thematic_betas(
start_date=DataContext.current.start_date,
end_date=DataContext.current.end_date,
basket_ids=[asset.get_marquee_id()])
if not df.empty:
df.set_index('date', inplace=True)
df.index = pd.to_datetime(df.index)
return _extract_series_from_df(df, QueryType.THEMATIC_BETA)
def get_thematic_report(self) -> ThematicReport:
if self.positioned_entity_type in [EntityType.PORTFOLIO, EntityType.ASSET]:
position_source_type = self.positioned_entity_type.value.capitalize()
reports = GsReportApi.get_reports(limit=100,
position_source_type=position_source_type,
position_source_id=self.id,
report_type=f'{position_source_type} Thematic Analytics')
if len(reports) == 0:
raise MqError(f'This {position_source_type} has no thematic analytics report.')
return ThematicReport.from_target(reports[0])
raise NotImplementedError
position_source_id='PORTFOLIOID',
report_type=ReportType.Portfolio_Factor_Risk,
status=ReportStatus.done
)
fake_ppa = PerformanceReport(report_id='PPAID',
position_source_type=PositionSourceType.Portfolio,
position_source_id='PORTFOLIOID',
report_type=ReportType.Portfolio_Performance_Analytics,
parameters=None,
status=ReportStatus.done
)
fake_pta = ThematicReport(report_id='PTAID',
position_source_type=PositionSourceType.Portfolio,
position_source_id='PORTFOLIOID',
report_type=ReportType.Portfolio_Thematic_Analytics,
parameters=None,
status=ReportStatus.done
)
factor_risk_results = [
{
'date': '2021-01-02',
'factor': 'factor1',
'pnl': 123,
'proportionOfRisk': 100,
'exposure': 200,
'annualRisk': 3928,
'dailyRisk': 202
},
{
