def test_FinNumbaNumbaParallel(useSobol):
valueDate = FinDate(1, 1, 2015)
expiryDate = FinDate(1, 7, 2015)
stockPrice = 100
volatility = 0.30
interestRate = 0.05
dividendYield = 0.01
seed = 2021
model = FinModelBlackScholes(volatility)
discountCurve = FinDiscountCurveFlat(valueDate, interestRate)
useSobolInt = int(useSobol)
testCases.header("NUMPATHS", "VALUE_BS", "VALUE_MC", "TIME")
callOption = FinEquityVanillaOption(expiryDate, 100.0,
FinOptionTypes.EUROPEAN_CALL)
value = callOption.value(valueDate, stockPrice, discountCurve,
dividendYield, model)
numPoints = 20
v_exact = [value] * numPoints
numPathsList = np.arange(1, numPoints + 1, 1) * 1000000
NUMBA_ONLY_v = []
NUMBA_ONLY_t = []
print("NUMBA ONLY")
for numPaths in numPathsList:
start = time.time()
valueMC = callOption.valueMC_NUMBA_ONLY(valueDate, stockPrice,
discountCurve, dividendYield,
model, numPaths, seed,
useSobolInt)
end = time.time()
duration = end - start
print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration))
NUMBA_ONLY_v.append(valueMC)
NUMBA_ONLY_t.append(duration)
NUMBA_PARALLEL_v = []
NUMBA_PARALLEL_t = []
print("NUMBA PARALLEL")
for numPaths in numPathsList:
start = time.time()
valueMC = callOption.valueMC_NUMBA_PARALLEL(valueDate, stockPrice,
discountCurve,
dividendYield, model,
numPaths, seed,
useSobolInt)
end = time.time()
duration = end - start
print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration))
NUMBA_PARALLEL_v.append(valueMC)
NUMBA_PARALLEL_t.append(duration)
###########################################################################
import matplotlib.pyplot as plt
if useSobol:
title = "SOBOL: NUMBA VS NUMBA + PARALLEL"
else:
title = "PSEUDORANDOM: NUMBA VS NUMBA + PARALLEL"
plt.figure(figsize=(8, 6))
plt.plot(numPathsList, NUMBA_ONLY_t, 'o-', label="NUMBA ONLY")
plt.plot(numPathsList, NUMBA_PARALLEL_t, 'o-', label="NUMBA PARALLEL")
plt.xlabel("Number of Paths")
plt.ylabel("Wall Time (s)")
plt.legend()
plt.title(title)
plt.figure(figsize=(8, 6))
plt.plot(numPathsList, v_exact, label="EXACT")
plt.plot(numPathsList, NUMBA_ONLY_v, 'o-', label="NUMBA ONLY")
plt.plot(numPathsList, NUMBA_PARALLEL_v, 'o-', label="NUMBA PARALLEL")
plt.xlabel("Number of Paths")
plt.ylabel("Option Value")
plt.legend()
plt.title(title)
def test_FinNumbaNumpySpeed(useSobol):
valueDate = FinDate(1, 1, 2015)
expiryDate = FinDate(1, 7, 2015)
stockPrice = 100
volatility = 0.30
interestRate = 0.05
dividendYield = 0.01
seed = 1999
model = FinModelBlackScholes(volatility)
discountCurve = FinDiscountCurveFlat(valueDate, interestRate)
useSobolInt = int(useSobol)
testCases.header("NUMPATHS", "VALUE_BS", "VALUE_MC", "TIME")
callOption = FinEquityVanillaOption(expiryDate, 100.0,
FinOptionTypes.EUROPEAN_CALL)
value = callOption.value(valueDate, stockPrice, discountCurve,
dividendYield, model)
numPoints = 20
v_exact = [value] * numPoints
###########################################################################
# DO UP TO 100K AS IT IS SLOW
###########################################################################
numPathsList = np.arange(1, numPoints + 1, 1) * 100000
NONUMBA_NONUMPY_v = []
NONUMBA_NONUMPY_t = []
print("PURE PYTHON")
for numPaths in numPathsList:
start = time.time()
valueMC = callOption.valueMC_NONUMBA_NONUMPY(valueDate, stockPrice,
discountCurve,
dividendYield, model,
numPaths, seed,
useSobolInt)
end = time.time()
duration = end - start
print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration))
NONUMBA_NONUMPY_v.append(valueMC)
NONUMBA_NONUMPY_t.append(duration + 1e-10)
NUMPY_ONLY_v = []
NUMPY_ONLY_t = []
print("NUMPY ONLY")
for numPaths in numPathsList:
start = time.time()
valueMC = callOption.valueMC_NUMPY_ONLY(valueDate, stockPrice,
discountCurve, dividendYield,
model, numPaths, seed,
useSobolInt)
end = time.time()
duration = end - start
print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration))
NUMPY_ONLY_v.append(valueMC)
NUMPY_ONLY_t.append(duration + 1e-10)
# speedUp = np.array(NONUMBA_NONUMPY_t)/np.array(NUMPY_ONLY_t)
# print(NUMPY_ONLY_t)
# print(NONUMBA_NONUMPY_t)
# print(speedUp)
if useSobol:
title = "SOBOL: PURE PYTHON VS NUMPY"
else:
title = "PSEUDORANDOM: PURE PYTHON VS NUMPY"
plt.figure(figsize=(8, 6))
plt.plot(numPathsList, NONUMBA_NONUMPY_t, 'o-', label="PURE PYTHON")
plt.plot(numPathsList, NUMPY_ONLY_t, 'o-', label="NUMPY ONLY")
plt.xlabel("Number of Paths")
plt.ylabel("Wall Time (s)")
plt.legend()
plt.title(title)
plt.figure(figsize=(8, 6))
plt.plot(numPathsList, v_exact, label="EXACT")
plt.plot(numPathsList, NONUMBA_NONUMPY_v, 'o-', label="PURE PYTHON")
plt.plot(numPathsList, NUMPY_ONLY_v, 'o-', label="NUMPY ONLY")
plt.xlabel("Number of Paths")
plt.ylabel("Option Value")
plt.legend()
plt.title(title)
###########################################################################
# DO UP TO 10 MILLION NOW THAT WE HAVE NUMPY
###########################################################################
numPathsList = np.arange(1, numPoints + 1, 1) * 1000000
NUMPY_ONLY_v = []
NUMPY_ONLY_t = []
print("NUMPY ONLY")
for numPaths in numPathsList:
start = time.time()
valueMC = callOption.valueMC_NUMPY_ONLY(valueDate, stockPrice,
discountCurve, dividendYield,
model, numPaths, seed,
useSobolInt)
end = time.time()
duration = end - start
print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration))
NUMPY_ONLY_v.append(valueMC)
NUMPY_ONLY_t.append(duration)
NUMBA_NUMPY_v = []
NUMBA_NUMPY_t = []
print("NUMBA+NUMPY")
for numPaths in numPathsList:
start = time.time()
valueMC = callOption.valueMC_NUMPY_NUMBA(valueDate, stockPrice,
discountCurve, dividendYield,
model, numPaths, seed,
useSobolInt)
end = time.time()
duration = end - start
print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration))
NUMBA_NUMPY_v.append(valueMC)
NUMBA_NUMPY_t.append(duration)
NUMBA_ONLY_v = []
NUMBA_ONLY_t = []
print("NUMBA ONLY")
for numPaths in numPathsList:
start = time.time()
valueMC = callOption.valueMC_NUMBA_ONLY(valueDate, stockPrice,
discountCurve, dividendYield,
model, numPaths, seed,
useSobolInt)
end = time.time()
duration = end - start
print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration))
NUMBA_ONLY_v.append(valueMC)
NUMBA_ONLY_t.append(duration)
NUMBA_PARALLEL_v = []
NUMBA_PARALLEL_t = []
print("NUMBA PARALLEL")
for numPaths in numPathsList:
start = time.time()
valueMC = callOption.valueMC_NUMBA_PARALLEL(valueDate, stockPrice,
discountCurve,
dividendYield, model,
numPaths, seed,
useSobolInt)
end = time.time()
duration = end - start
print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration))
NUMBA_PARALLEL_v.append(valueMC)
NUMBA_PARALLEL_t.append(duration)
# speedUp = np.array(NUMBA_ONLY_t)/np.array(NUMBA_PARALLEL_t)
# print("PARALLEL:", speedUp)
###########################################################################
# COMPUTED USING NUMSTEPS FROM 1M to 10M
###########################################################################
CPP_t = np.array([
0.075, 0.155, 0.223, 0.313, 0.359, 0.421, 0.495, 0.556, 0.64, 0.702,
0.765, 0.841, 0.923, 0.982, 1.05, 1.125, 1.195, 1.261, 1.333, 1.408
])
CPP_v = np.array([
9.30872, 9.29576, 9.29422, 9.29832, 9.29863, 9.30153, 9.2994, 9.3025,
9.29653, 9.29875, 9.29897, 9.29996, 9.29931, 9.29796, 9.29784, 9.2992,
9.3001, 9.30093, 9.29876, 9.29921
])
if useSobol:
title = "SOBOL: COMPARING OPTIMISATIONS"
else:
title = "PSEUDORANDOM: COMPARING OPTIMISATIONS"
plt.figure(figsize=(8, 6))
plt.plot(numPathsList, NUMPY_ONLY_t, 'o-', label="NUMPY ONLY")
plt.plot(numPathsList, NUMBA_NUMPY_t, 'o-', label="NUMBA + NUMPY")
plt.xlabel("Number of Paths")
plt.ylabel("Wall Time (s)")
plt.legend()
plt.title(title)
###########################################################################
if useSobol:
title = "SOBOL: COMPARING OPTIMISATIONS"
else:
title = "PSEUDORANDOM: COMPARING OPTIMISATIONS"
plt.figure(figsize=(8, 6))
plt.plot(numPathsList, NUMPY_ONLY_t, 'o-', label="NUMPY ONLY")
plt.plot(numPathsList, NUMBA_NUMPY_t, 'o-', label="NUMBA + NUMPY")
plt.plot(numPathsList, NUMBA_ONLY_t, 'o-', label="NUMBA ONLY")
plt.plot(numPathsList, NUMBA_PARALLEL_t, 'o-', label="NUMBA PARALLEL")
if useSobol == False:
plt.plot(numPathsList, CPP_t, 'o-', label="C++")
plt.xlabel("Number of Paths")
plt.ylabel("Wall Time (s)")
plt.legend()
plt.title(title)
###########################################################################
plt.figure(figsize=(8, 6))
plt.plot(numPathsList, v_exact, label="EXACT")
plt.plot(numPathsList, NUMBA_ONLY_v, 'o-', label="NUMBA ONLY")
plt.plot(numPathsList, CPP_v, 'o-', label="C++")
plt.xlabel("Number of Paths")
plt.ylabel("Option Value")
plt.legend()
plt.title(title)
