def testFinGBMProcess():
numAssets = 3
numPaths = 5
numTimeSteps = 1
t = 1.0
mus = 0.03 * np.ones(numAssets)
stockPrices = 100.0 * np.ones(numAssets)
volatilities = 0.2 * np.ones(numAssets)
rho = 0.8
corrMatrix = corrMatrixGenerator(rho, numAssets)
seed = 1912
_ = getPathsAssets(numAssets, numPaths, numTimeSteps, t, mus, stockPrices,
volatilities, corrMatrix, seed)
def test_FinCDSBasket():
tradeDate = FinDate(2007, 3, 1)
stepInDate = tradeDate.addDays(1)
valuationDate = tradeDate.addDays(1)
liborCurve = buildLiborCurve(tradeDate)
basketMaturity = FinDate(2011, 12, 20)
cdsIndex = FinCDSIndexPortfolio()
##########################################################################
testCases.banner(
"===================================================================")
testCases.banner(
"====================== INHOMOGENEOUS CURVE =========================="
)
testCases.banner(
"===================================================================")
numCredits = 5
spd3Y = 0.0012
spd5Y = 0.0025
spd7Y = 0.0034
spd10Y = 0.0046
testCases.header("LABELS", "VALUE")
if 1 == 0:
issuerCurves = loadHomogeneousSpreadCurves(valuationDate, liborCurve,
spd3Y, spd5Y, spd7Y, spd10Y,
numCredits)
else:
issuerCurves = loadHeterogeneousSpreadCurves(valuationDate, liborCurve)
issuerCurves = issuerCurves[0:numCredits]
intrinsicSpd = cdsIndex.intrinsicSpread(
valuationDate, stepInDate, basketMaturity, issuerCurves) * 10000.0
testCases.print("INTRINSIC SPD BASKET MATURITY", intrinsicSpd)
totalSpd = cdsIndex.totalSpread(valuationDate, stepInDate, basketMaturity,
issuerCurves) * 10000.0
testCases.print("SUMMED UP SPD BASKET MATURITY", totalSpd)
minSpd = cdsIndex.minSpread(valuationDate, stepInDate, basketMaturity,
issuerCurves) * 10000.0
testCases.print("MINIMUM SPD BASKET MATURITY", minSpd)
maxSpd = cdsIndex.maxSpread(valuationDate, stepInDate, basketMaturity,
issuerCurves) * 10000.0
testCases.print("MAXIMUM SPD BASKET MATURITY", maxSpd)
seed = 1967
basket = FinCDSBasket(valuationDate, basketMaturity)
testCases.banner(
"===================================================================")
testCases.banner(
"======================= GAUSSIAN COPULA ===========================")
testCases.banner(
"===================================================================")
testCases.header("TIME", "Trials", "RHO", "NTD", "SPRD", "SPRD_HOMO")
for ntd in range(1, numCredits + 1):
for beta in [0.0, 0.5]:
rho = beta * beta
betaVector = np.ones(numCredits) * beta
corrMatrix = corrMatrixGenerator(rho, numCredits)
for numTrials in [1000]: # [1000,5000,10000,20000,50000,100000]:
start = time.time()
v1 = basket.valueGaussian_MC(valuationDate, ntd, issuerCurves,
corrMatrix, liborCurve, numTrials,
seed)
v2 = basket.value1FGaussian_Homo(valuationDate, ntd,
issuerCurves, betaVector,
liborCurve)
end = time.time()
period = (end - start)
testCases.print(period, numTrials, rho, ntd, v1[2] * 10000,
v2[3] * 10000)
testCases.banner(
"===================================================================")
testCases.banner(
"==================== STUDENT'S-T CONVERGENCE ======================")
testCases.banner(
"===================================================================")
testCases.header("TIME", "TRIALS", "RHO", "DOF", "NTD", "SPRD")
for beta in [0.0, 0.5]:
rho = beta**2
corrMatrix = corrMatrixGenerator(rho, numCredits)
for ntd in range(1, numCredits + 1):
for doF in [3, 10]:
start = time.time()
v = basket.valueStudentT_MC(valuationDate, ntd, issuerCurves,
corrMatrix, doF, liborCurve,
numTrials, seed)
end = time.time()
period = (end - start)
testCases.print(period, numTrials, rho, doF, ntd, v[2] * 10000)
start = time.time()
v = basket.valueGaussian_MC(valuationDate, ntd, issuerCurves,
corrMatrix, liborCurve, numTrials,
seed)
end = time.time()
period = (end - start)
testCases.print(period, numTrials, rho, "GC", ntd, v[2] * 10000)
testCases.banner(
"===================================================================")
testCases.banner(
"=================== STUDENT'S T WITH DOF = 5 ======================")
testCases.banner(
"===================================================================")
doF = 5
testCases.header("TIME", "NUMTRIALS", "RHO", "NTD", "SPD")
for beta in [0.0, 0.5]:
rho = beta**2
corrMatrix = corrMatrixGenerator(rho, numCredits)
for ntd in range(1, numCredits + 1):
for numTrials in [1000]:
start = time.time()
v = basket.valueStudentT_MC(valuationDate, ntd, issuerCurves,
corrMatrix, doF, liborCurve,
numTrials, seed)
end = time.time()
period = (end - start)
testCases.print(period, numTrials, rho, ntd, v[2] * 10000)
