def test_var_swap():
idx = pd.date_range(start="2019-01-01", periods=4, freq="D")
data = {'varSwap': [1, 2, 3, 4]}
out = pd.DataFrame(data=data, index=idx)
replace = Replacer()
market_mock = replace(
'gs_quant.timeseries.measures.GsDataApi.get_market_data', Mock())
market_mock.return_value = out
expected = pd.Series([1, 2, 3, 4], name='varSwap', index=idx)
actual = tm.var_swap(Index('MA123', AssetClass.Equity, '123'), '1m')
assert_series_equal(expected, actual)
market_mock.assert_called_once()
market_mock.reset_mock()
market_mock.return_value = pd.DataFrame()
actual = tm.var_swap(Index('MA123', AssetClass.Equity, '123'), '1m')
assert actual.empty
replace.restore()
def test_var_swap_fwd():
# bad input
with pytest.raises(MqError):
tm.var_swap(Index('MA123', AssetClass.Equity, '123'), '1m', 500)
# regular
idx = pd.date_range(start="2019-01-01", periods=4, freq="D")
d1 = {
'varSwap': [1, 2, 3, 4],
'tenor': ['1y'] * 4
}
d2 = {
'varSwap': [1.5, 2.5, 3.5, 4.5],
'tenor': ['13m'] * 4
}
df1 = pd.DataFrame(data=d1, index=idx)
df2 = pd.DataFrame(data=d2, index=idx)
out = pd.concat([df1, df2])
replace = Replacer()
market_mock = replace('gs_quant.timeseries.measures.GsDataApi.get_market_data', Mock())
market_mock.return_value = out
tenors_mock = replace('gs_quant.timeseries.measures._var_swap_tenors', Mock())
tenors_mock.return_value = ['1m', '1y', '13m']
expected = pd.Series([7.5, 8.5, 9.5, 10.5], name='varSwap', index=idx)
actual = tm.var_swap(Index('MA123', AssetClass.Equity, '123'), '1m', '1y')
assert_series_equal(expected, actual)
market_mock.assert_called_once()
# no data
market_mock.return_value = pd.DataFrame()
assert tm.var_swap(Index('MA123', AssetClass.Equity, '123'), '1m', '1y').empty
# no data for a tenor
market_mock.return_value = pd.DataFrame(data=d1, index=idx)
assert tm.var_swap(Index('MA123', AssetClass.Equity, '123'), '1m', '1y').empty
# no such tenors
tenors_mock.return_value = []
assert tm.var_swap(Index('MA123', AssetClass.Equity, '123'), '1m', '1y').empty
# finish
replace.restore()