def lsqQ(para):
ois = OIS(trim_start = startdate, trim_end = enddate)
Affine = VasicekAffine(x, para, datelist)
myCDS = CDS(ois.interpolationois(), datelist, Affine.calQ(), recovery)
diff = np.subtract(brz_cds,myCDS.MTM())
return diff
def lsqR(para):
ois = OIS(trim_start = startdate, trim_end = enddate)
Affine = VasicekAffine(x, para, datelist)
diff = np.subtract(ois.interpolationois(),Affine.calR())
return diff
def lsqR(para):
ois = OIS(trim_start = startdate, trim_end = enddate)
Affine = VasicekAffine(x, para, datelist)
diff = np.subtract(ois.interpolationois(),Affine.calR())
return diff
def lsqQ(para):
ois = OIS(trim_start = startdate, trim_end = enddate)
Affine = VasicekAffine(x, para, datelist)
myCDS = CDS(ois.interpolationois(), datelist, Affine.calQ(), recovery)
diff = np.subtract(brz_cds,myCDS.MTM())
__author__ = 'Yule Jin'
import datetime
import numpy as np
from MonteCarloSimulators.Vasicek.VasicekAffine import VasicekAffine
from Products.Credit.CDS.CDS import CDS
from Products.Rates.Bond.Bond import bond
#CashFlow Dates
x = [0.1, 0.005, 0.03, 0.03]
y = [3, 0.05, 0.09, 0.08]
#t_series = np.round(np.arange(0,1.001,0.25)*365)
t_series = np.round(np.arange(0, 365.001 * 30 + 6.001, 1))
start = datetime.datetime(2005, 1, 10)
base = datetime.datetime.today()
datelist = [start + datetime.timedelta(days=x) for x in t_series]
datelist = [x.date() for x in datelist]
Affine = VasicekAffine(x, y, datelist)
#print("Q is ", Affine.calQ())
print("r is ", Affine.calR())
QQ = Affine.calQ().values
VBond = bond(Affine.calR().values, 0.08, datelist, Affine.calQ().values, 0.4)
VCDS = CDS(Affine.calR().values, datelist, Affine.calQ().values, 0.4)
print('Risky Bond Price = ', str(1000 * VBond.pv().sum()))
print('Riskless Bond Price = ', str(1000 * VBond.riskless().sum()))
print('5 years Par Spread for each quarter= ', str(VCDS.parSpread()))
print('5 years Mark to Market Value for each quarter = ', VCDS.MTM())
