def test_sample_crifImport(self):
csvLocation = 'test/NochKleineresTestportfolio.csv'
# CrifUtil.read_csv should align different formatting styles of the CRIF.
crif = Crif(CRIF.CrifUtil.read_csv(csvLocation, sep=','))
# After the creation the CRIF consists of ArrayLists of Java objects (sensitivitities, scheduleNotionals etc)
print(str(crif.getAllSensitivities()))
print(str(crif.getAllAddonNotionals()))
# The data set used for creating the crif is stored within the crif object:
print(str(crif.asDataFrame.head(20)))
asdf = 1
def test_originalStaysTheSame(self):
Input = CRIF.CrifUtil.read_csv(r'../NochKleineresTestportfolio.csv')
crif = Crif(Input)
simm = Simm()
result = simm.calculateStandard(crif.getAllSensitivities(),
'USD').doubleValue()
tradeIds = crif.Sensitivities.keys()
tradeId = next(iter(tradeIds))
bumpedCrif = BumpedCrif(crif, tradeId, 0.01)
result2 = simm.calculateStandard(crif.getAllSensitivities(),
'USD').doubleValue()
self.assertEqual(result, result2)
def test1(self):
Input = CrifUtil.read_csv(r'../NochKleineresTestportfolio.csv')
crif = Crif(Input)
self.assertEqual('IMLedis_NRW_Bank', crif.Counterparty)
self.assertEqual('collect', crif.direction)
self.assertEqual('EMIR', crif.regulation)
del crif
def test_performance_SA(self):
Input = CRIF.CrifUtil.read_csv(r'../NochKleineresTestportfolio.csv')
tic = time.time()
crif = Crif(Input)
imTree = StandardCalculation.calculate(crif)
imTree = StandaloneAllocation.calculate(imTree)
toc = time.time()
self.assertTrue((toc-tic) < 0.8)
def test_toDataFrameOneLine(self):
OneLineCrif = '''ValuationDate,IMLedis,tradeId,IMModel,productClass,riskType,qualifier,bucket,label1,label2,amount,amountCurrency,amountUSD,EndDate,CollectRegulations,PostRegulations
,IMLedis_NRW_Bank,DZ14788807,SIMM,RatesFX,Risk_IRCurve,EUR,1,10y,Libor3m,1000000,EUR,1000000,,EMIR,'''
Input = CRIF.CrifUtil.read_csv(StringIO(OneLineCrif))
crif = Crif(Input)
imTree = StandardCalculation.calculate(crif)
df = imTree.toDataFrame()
asdf = 1
def test_toDataFrameWithBothAllocations(self):
Input = CRIF.CrifUtil.read_csv(r'..\NochKleineresTestportfolio.csv')
crif = Crif(Input)
imTree = StandardCalculation.calculate(crif)
imTree = StandaloneAllocation.calculate(imTree)
imTree = EulerAllocation.calculate(imTree)
df = imTree.toDataFrame()
asdf = 1
def allocate_im(crif):
if crif is None:
raise PreventUpdate
crif = Crif(pd.read_json(crif))
imTree = StandardCalculation.calculate(crif)
imTree = EulerAllocation.calculate(imTree)
imTree = StandaloneAllocation.calculate(imTree)
imTree = imTree.toDataFrame()
return imTree.to_json()
def test_performance_JPM_komplett(self):
Input = CRIF.CrifUtil.read_csv(r'../NochKleineresTestportfolio.csv')
tic = time.time()
crif = Crif(Input)
imTree = StandardCalculation.calculate(crif)
imTree = EulerAllocation.calculate(imTree)
toc = time.time()
print(toc - tic)
asfd = 1
self.assertTrue((toc - tic) < 20)
def test_both_allocations(self):
Input = CRIF.CrifUtil.read_csv(r'../NochKleineresTestportfolio.csv')
tic = time.time()
crif = Crif(Input)
imTree = StandardCalculation.calculate(crif)
imTree = EulerAllocation.calculate(imTree)
imTree = StandaloneAllocation.calculate(imTree)
toc = time.time()
print(toc - tic)
asfd = 1
self.assertTrue((toc - tic) < 40)
def testJsonCreatorStandardCalculation(self):
OneLineCrif = '''ValuationDate,IMLedis,tradeId,IMModel,productClass,riskType,qualifier,bucket,label1,label2,amount,amountCurrency,amountUSD,EndDate,CollectRegulations,PostRegulations
,IMLedis_NRW_Bank,DZ14788807,SIMM,RatesFX,Risk_IRCurve,EUR,1,10y,Libor3m,1000000,EUR,1000000,,EMIR,'''
Input = CRIF.CrifUtil.read_csv(StringIO(OneLineCrif))
crif = Crif(Input)
imTree = StandardCalculation.calculate(crif)
testJson = imTree.to_json(with_data=True)
self.assertEqual(
testJson,
r'''{"Total 51000000": {"children": [{"SIMM-P 51000000": {"children": [{"RatesFX 51000000": {"children": [{"Interest Rate 51000000": {"children": [{"Delta 51000000": {"children": [{"EUR 51000000": {"data": {"rowNumber": 5, "Level": 6, "levelName": "Bucket", "ExposureAmount": 51000000.0, "manifestation": "EUR", "identifier": "SIMM-P_RatesFX_Interest Rate_Delta_EUR"}}}], "data": {"rowNumber": 4, "Level": 5, "levelName": "Sensitivity Type", "ExposureAmount": 51000000.0, "manifestation": "Delta", "identifier": "SIMM-P_RatesFX_Interest Rate_Delta"}}}], "data": {"rowNumber": 3, "Level": 4, "levelName": "Risk Class", "ExposureAmount": 51000000.0, "manifestation": "Interest Rate", "identifier": "SIMM-P_RatesFX_Interest Rate"}}}], "data": {"rowNumber": 2, "Level": 3, "levelName": "Silo", "ExposureAmount": 51000000.0, "manifestation": "RatesFX", "identifier": "SIMM-P_RatesFX"}}}], "data": {"rowNumber": 1, "Level": 2, "levelName": "ImModel", "ExposureAmount": 51000000.0, "manifestation": "SIMM-P", "identifier": "SIMM-P"}}}], "data": {"rowNumber": 0, "Level": 1, "levelName": "Total", "ExposureAmount": 51000000.0, "manifestation": "Total", "identifier": ""}}}'''
)
def __init__(self, CRIFsdataframe):
CRIFs = CRIFsdataframe[[
'IMLedis', 'CollectRegulations', 'PostRegulations'
]].drop_duplicates()
for row in CRIFs.itertuples():
identifier = tuple([row[1], row[2], row[3]])
CrifFrame = CRIFsdataframe[
(CRIFsdataframe.IMLedis == row[1])
& (CRIFsdataframe.CollectRegulations == row[2])
& (CRIFsdataframe.PostRegulations == row[3])]
thisCrif = Crif(CrifFrame)
self[str(thisCrif)] = thisCrif
def test_bumpWorked(self):
eps = 0.1
tradeId = 'DZ14788807'
Input = CRIF.CrifUtil.read_csv(r'../NochKleineresTestportfolio.csv')
crif = Crif(Input)
simm = Simm()
bumpedCrif = BumpedCrif(crif, tradeId, eps)
InputManBump = pd.read_csv(
r'../NochKleineresTestportfolioManualBump.csv')
manuelCrif = Crif(InputManBump)
resultAutoBumped = simm.calculateStandard(
bumpedCrif.getAllSensitivities(), 'USD').doubleValue()
resultManBumped = simm.calculateStandard(
manuelCrif.getAllSensitivities(), 'USD').doubleValue()
resultOrig = simm.calculateStandard(crif.getAllSensitivities(),
'USD').doubleValue()
autoSensis = bumpedCrif.Sensitivities[tradeId]
manuellSensis = manuelCrif.Sensitivities[tradeId]
for i in range(0, autoSensis.size()):
self.assertAlmostEqual(getSensitivityAmount(autoSensis.get(i)),
getSensitivityAmount(manuellSensis.get(i)),
places=5)
self.assertAlmostEqual(resultAutoBumped, resultManBumped, places=3)
self.assertNotAlmostEqual(resultOrig, resultManBumped, places=0)
self.assertNotAlmostEqual(resultOrig, resultAutoBumped, places=0)
def test5(self):
Input = CrifUtil.read_csv(r'../testIR11asCRIF.csv')
crif1 = Crif(Input)
crif2 = Crif(Input)
self.assertEqual(
31773442304,
round(
Simm.calculateStandard(crif1.getAllSensitivities(),
'USD').doubleValue()))
self.assertEqual(
31773442304,
round(
Simm.calculateStandard(crif2.getAllSensitivities(),
'USD').doubleValue()))
def test_calculate_initial_margin(self):
# To streamline it is only possible to create an IM Tree from which the Overall Initial Margin may be extracted
# afterwards.
# The structure of the IM Tree has been adopted from the open source acadiasoft engine.
csvLocation = 'test/NochKleineresTestportfolio.csv'
crif = Crif(CRIF.CrifUtil.read_csv(csvLocation, sep=','))
# call StandardCalculation.calculate(crif) to calculate the Initial Margin and create an IM Tree
imTree = StandardCalculation.calculate(crif)
imTree = EulerAllocation.calculate(imTree)
imTree = StandaloneAllocation.calculate(imTree)
# The resulting IM Tree can be displayed relatively conveniently with print
print(imTree)
# Alternatively it may be transformed into a DataFrame to simplify analysis of the result in Python
imTree_asDataFrame = imTree.toDataFrame()
print(imTree_asDataFrame.head(10))
print(imTree_asDataFrame.columns)
# If you want to analyse further outside of python you can save the imTree as a .csv File
imTree.printToCsv('./ExampleTreeAsCsv.csv')
# Finally, you can extract the overall Initial Margin as follows:
im = imTree.getMargin()
print('The initial Margin of ' + str(crif) + ' is ' +
'{:,.2f}'.format(im) + ' USD.')
# By default the calculationCurrency and the currency in which the margin is returned is USD
asdf = 1
def calculate_IM(crif):
if crif is None:
raise PreventUpdate
crif = Crif(pd.read_json(crif))
imTree = StandardCalculation.calculate(crif)
return imTree.toDataFrame().to_json()
def test3(self):
Input = CrifUtil.read_csv(r'../NochKleineresTestportfolio.csv')
crif = Crif(Input)
self.assertEqual(True, crif.asDataFrame.equals(Input))
del crif
def test_toDataFrameMultiLine(self):
Input = CRIF.CrifUtil.read_csv(r'..\NochKleineresTestportfolio.csv')
crif = Crif(Input)
imTree = StandardCalculation.calculate(crif)
df = imTree.toDataFrame()
