def structured_calc(mocker, priceable: Priceable, measure: risk.RiskMeasure):
set_session()
values = {
'$type': 'RiskVector',
'asset': [0.01, 0.015],
'points': [
{'type': 'IR', 'asset': 'USD', 'class_': 'Swap', 'point': '1y'},
{'type': 'IR', 'asset': 'USD', 'class_': 'Swap', 'point': '2y'}
]
}
mocker.return_value = [[[[values]]]]
expected = risk.sort_risk(pd.DataFrame([
{'mkt_type': 'IR', 'mkt_asset': 'USD', 'mkt_class': 'Swap', 'mkt_point': '1y', 'value': 0.01},
{'mkt_type': 'IR', 'mkt_asset': 'USD', 'mkt_class': 'Swap', 'mkt_point': '2y', 'value': 0.015}
]))
current = PricingContext.current
result = priceable.calc(measure)
assert result.raw_value.equals(expected)
risk_requests = (risk.RiskRequest(
positions=(RiskPosition(instrument=priceable, quantity=1),),
measures=(measure,),
pricing_and_market_data_as_of=(PricingDateAndMarketDataAsOf(pricing_date=current.pricing_date,
market=current.market),),
parameters=RiskRequestParameters(raw_results=True),
wait_for_results=True),)
mocker.assert_called_with(risk_requests)
def structured_calc(mocker, priceable: Priceable, measure: risk.RiskMeasure):
set_session()
values = [{
'marketDataType': 'IR',
'assetId': 'USD',
'pointClass': 'Swap',
'point': '1y',
'value': 0.01
}, {
'marketDataType': 'IR',
'assetId': 'USD',
'pointClass': 'Swap',
'point': '2y',
'value': 0.015
}]
mocker.return_value = [[values]]
result = priceable.calc(measure)
expected = risk.sort_risk(pd.DataFrame(values))
assert result.equals(expected)
risk_request = risk.RiskRequest(
positions=(risk.RiskPosition(priceable, 1), ),
measures=(measure, ),
pricing_location=PricingContext.current.market_data_location,
pricing_and_market_data_as_of=PricingContext.current.
_pricing_market_data_as_of,
parameters=RiskRequestParameters(),
wait_for_results=True)
mocker.assert_called_with(risk_request)
def __df_from_coordinate_data(cls, data: Iterable[dict]) -> pd.DataFrame:
from gs_quant.risk import sort_risk
df = sort_risk(pd.DataFrame.from_records(data))
index_field = next((f for f in ('time', 'date') if f in df.columns),
None)
if index_field:
df = df.set_index(pd.DatetimeIndex(df.loc[:, index_field].values))
return df
def test_coordinate_last(mocker):
data = {
'responses': [{
'data': [{
'marketDataType': 'Prime',
'marketDataAsset': '335320934',
'field': 'price',
'price': 1.0141,
'time': '2019-01-20T01:08:00Z'
}]
}, {
'data': [{
'marketDataType': 'IR',
'marketDataAsset': 'USD',
'pointClass': 'Swap',
'marketDataPoint': ('2Y', ),
'quotingStyle': 'ATMRate',
'ATMRate': 0.02592,
'time': '2019-01-20T01:09:45Z'
}]
}]
}
expected_result = sort_risk(
pd.DataFrame([{
'field': 'price',
'marketDataAsset': '335320934',
'marketDataType': 'Prime',
'value': 1.0141
}, {
'quotingStyle': 'ATMRate',
'marketDataAsset': 'USD',
'marketDataType': 'IR',
'marketDataPoint': ('2Y', ),
'pointClass': 'Swap',
'value': 0.02592
}]))
# mock GsSession
mocker.patch.object(GsSession.__class__,
'current',
return_value=GsSession.get(Environment.QA, 'client_id',
'secret'))
mocker.patch.object(GsSession.current, '_post', return_value=data)
result = GsDataApi.coordinates_last(coordinates=test_coordinates,
as_of=dt.datetime(2019, 1, 2, 1, 10),
as_dataframe=True)
result.sort_index(axis=1, inplace=True)
expected_result.sort_index(axis=1, inplace=True)
assert result.equals(expected_result)
def test_coordinates_data(mocker):
bond_data = [{
'marketDataType': 'Prime',
'marketDataAsset': '335320934',
'field': 'price',
'price': 1.0139,
'time': pd.to_datetime('2019-01-20T01:03:00Z')
}, {
'marketDataType': 'Prime',
'marketDataAsset': '335320934',
'field': 'price',
'price': 1.0141,
'time': pd.to_datetime('2019-01-20T01:08:00Z')
}]
swap_data = [{
'marketDataType': 'IR',
'marketDataAsset': 'USD',
'pointClass': 'Swap',
'marketDataPoint': ('2Y', ),
'quotingStyle': 'ATMRate',
'ATMRate': 0.02592,
'time': pd.to_datetime('2019-01-20T01:09:45Z')
}]
bond_expected_result = [{
'marketDataType': 'Prime',
'marketDataAsset': '335320934',
'field': 'price',
'value': 1.0139,
'time': pd.to_datetime('2019-01-20T01:03:00Z')
}, {
'marketDataType': 'Prime',
'marketDataAsset': '335320934',
'field': 'price',
'value': 1.0141,
'time': pd.to_datetime('2019-01-20T01:08:00Z')
}]
swap_expected_result = [{
'marketDataType': 'IR',
'marketDataAsset': 'USD',
'pointClass': 'Swap',
'marketDataPoint': ('2Y', ),
'quotingStyle': 'ATMRate',
'value': 0.02592,
'time': pd.to_datetime('2019-01-20T01:09:45Z')
}]
bond_expected_df = sort_risk(pd.DataFrame(bond_expected_result))
bond_expected_df = bond_expected_df.set_index(
pd.DatetimeIndex(bond_expected_df.time.values))
swap_expected_df = sort_risk(pd.DataFrame(swap_expected_result))
swap_expected_df = swap_expected_df.set_index(
pd.DatetimeIndex(swap_expected_df.time.values))
# mock GsSession
mocker.patch.object(GsSession.__class__,
'current',
return_value=GsSession.get(Environment.QA, 'client_id',
'secret'))
mocker.patch.object(GsSession.current,
'_post',
side_effect=[{
'responses': [{
'data': bond_data
}]
}, {
'responses': [{
'data': bond_data
}, {
'data': swap_data
}]
}])
coord_data_result = GsDataApi.coordinates_data(
coordinates=test_coordinates[0],
start=dt.datetime(2019, 1, 2, 1, 0),
end=dt.datetime(2019, 1, 2, 1, 10))
assert_frame_equal(coord_data_result, bond_expected_df)
coords_data_result = GsDataApi.coordinates_data(
coordinates=test_coordinates,
start=dt.datetime(2019, 1, 2, 1, 0),
end=dt.datetime(2019, 1, 2, 1, 10),
as_multiple_dataframes=True)
assert len(coords_data_result) == 2
assert_frame_equal(coords_data_result[0], bond_expected_df)
assert_frame_equal(coords_data_result[1], swap_expected_df)
