def test_custom_aum():
data = {
'aum': [
101,
102,
103
],
'date': [
'2020-01-01',
'2020-01-02',
'2020-01-03'
]
}
idx = pd.date_range('2020-01-01', freq='D', periods=3)
df = MarketDataResponseFrame(data=data, index=idx)
df.dataset_ids = ('AUM',)
replace = Replacer()
# mock GsPortfolioApi.get_reports()
mock = replace('gs_quant.api.gs.portfolios.GsPortfolioApi.get_custom_aum', Mock())
mock.return_value = df
with DataContext(datetime.date(2020, 1, 1), datetime.date(2019, 1, 3)):
actual = mp.aum('MP1')
assert actual.index.equals(idx)
assert all(actual.values == data['aum'])
replace.restore()
def test_fci():
with pytest.raises(NotImplementedError):
mc.fci('IN', real_time=True)
data = {
'fci': [101, 102, 103],
'realFCI': [100, 99, 98],
'realTWIContribution': [100, 100, 98]
}
idx = pd.date_range('2020-01-01', freq='D', periods=3)
df = MarketDataResponseFrame(data=data, index=idx)
df.dataset_ids = ('FCI', )
replace = Replacer()
mock = replace('gs_quant.timeseries.measures.GsDataApi.get_market_data',
Mock())
mock.return_value = df
with DataContext(datetime.date(2020, 1, 1), datetime.date(2019, 1, 3)):
actual = mc.fci('IN')
assert actual.index.equals(idx)
assert all(actual.values == data['fci'])
mock = replace('gs_quant.timeseries.measures.Dataset.get_data', Mock())
mock.return_value = df
with DataContext(datetime.date(2020, 1, 1), datetime.date(2019, 1, 3)):
actual = mc.fci('IN', mc._FCI_MEASURE.REAL_FCI)
assert actual.index.equals(idx)
assert all(actual.values == data['realFCI'])
with DataContext(datetime.date(2020, 1, 1), datetime.date(2019, 1, 3)):
actual = mc.fci('IN', mc._FCI_MEASURE.REAL_TWI_CONTRIBUTION)
assert actual.index.equals(idx)
assert all(actual.values == data['realTWIContribution'])
replace.restore()
def mock_curr(_cls, _q):
d = {
'swapRate': [1, 2, 3],
}
df = MarketDataResponseFrame(data=d, index=_index * 3)
df.dataset_ids = _test_datasets
return df
def mock_curr(_cls, _q):
d = {
'impliedVolatility': [1, 2, 3],
}
df = MarketDataResponseFrame(data=d, index=_index * 3)
df.dataset_ids = _test_datasets
return df
def mock_df():
d = {
'strikeVol': [5, 1, 2],
}
df = MarketDataResponseFrame(data=d, index=_index * 3)
df.dataset_ids = "FX_VOLATILITY_SWAP"
return df
def test_financial_conditions_index():
data = {
'pnl': [
101,
102,
103
],
'date': [
'2020-01-01',
'2020-01-02',
'2020-01-03'
]
}
idx = pd.date_range('2020-01-01', freq='D', periods=3)
df = MarketDataResponseFrame(data=data, index=idx)
df.dataset_ids = ('PNL',)
replace = Replacer()
# mock PerformanceReport.get_pnl()
mock = replace('gs_quant.markets.report.PerformanceReport.get_pnl', Mock())
mock.return_value = df
# mock GsPortfolioApi.get_reports()
mock = replace('gs_quant.api.gs.portfolios.GsPortfolioApi.get_reports', Mock())
mock.return_value = [Report.from_dict({'id': 'RP1', 'positionSourceType': 'Portfolio', 'positionSourceId': 'MP1',
'type': 'Portfolio Performance Analytics',
'parameters': {'transactionCostModel': 'FIXED'}})]
with DataContext(datetime.date(2020, 1, 1), datetime.date(2019, 1, 3)):
actual = mp.pnl('MP1')
assert actual.index.equals(idx)
assert all(actual.values == data['pnl'])
replace.restore()
def mock_natgas_forward_price(_cls, _q):
d = {
'forwardPrice': [
2.880,
2.844,
2.726,
],
'contract': [
"F21",
"G21",
"H21",
]
}
df = MarketDataResponseFrame(data=d,
index=pd.to_datetime(
[datetime.date(2019, 1, 2)] * 3))
df.dataset_ids = _test_datasets
return df
