def tests():
sigma1 = 0.01
sigma2 = 0.008
beta1 = 0.5
beta2 = 0.1
rho = 0.4
dt = 0.001
T = 0.5
t = 0
T1 = 0.25
T2 = 1
Q0 = 0.03
R0 = 0.0
S = 1
numPath = 1000
port = FXHedgePort(t, T, T1, T2)
evor = RateEvolver(sigma1, sigma2, beta1, beta2, rho, dt, Q0, port)
print evor.__str__()
#print "dQ = ", evor.dQ_vec()
print "QT = ", evor.GetQ()
calculator = FXFwdCalculator()
fairK = calculator.calFairStrike(S, Q0, R0, t, T)
print "fairK = ", fairK
print "One path value = ", calculator.calVal(S, evor.GetQ()[0], R0, t, T, fairK)
MCEng1 = MCHedgeEngine(evor, port)
unHedged, triHedged, factorHedged = MCEng1.runMC(numPath, S, R0)
print "triN1 =", MCEng1.triN1, "triN2 =", MCEng1.triN2
print "UnHedged PNL mean is", unHedged.mean(), "sd is", unHedged.std()
print "TriHedged PNL mean is", triHedged.mean(), "sd is", triHedged.std()
print "FactorHedged PNL mean is", factorHedged.mean(), "sd is", factorHedged.std()
def wrapForOneT(T, numPath):
'''
Wrapper for a tenor, T
'''
sigma1 = 0.01
sigma2 = 0.008
beta1 = 0.5
beta2 = 0.1
rho = -0.4
dt = 0.001
t = 0.0
T1 = 0.25
T2 = 1.0
Q0 = 0.03
R0 = 0.0
S = 1.0
port = FXHedgePort(t, T, T1, T2)
evor = RateEvolver(sigma1, sigma2, beta1, beta2, rho, dt, Q0, port)
MCEng1 = MCHedgeEngine(evor, port)
print "T =", T
MCEng1.comparePerformance(numPath, S, R0)
