def getDailySpline():
data = pd.read_excel(
r"S:\Francesco\PRICING\Copy of BootstrappingSwapCurve_francesco.xlsx",
sheet_name='Sheet4')
data['x'] = pd.to_datetime(data['x'])
tableOfParameters = getTablesOfParameters(data)
#evaluationDate=pd.to_datetime('15/11/2018',format='%d/%m/%Y')
#interpolatedValue=getSplineValue(evaluationDate,tableOfParameters)
#plot the spline
datelist = pd.date_range(start=data.loc[0, 'x'],
end=data.loc[len(data) - 1, 'x']).tolist()
Interpolation = []
for i in range(len(datelist)):
interpolatedValue = getSplineValue(datelist[i], tableOfParameters)
Interpolation.append(interpolatedValue)
A = np.vstack(Interpolation)
data = pd.read_excel(
r"S:\Francesco\PRICING\Copy of BootstrappingSwapCurve_francesco.xlsx",
sheet_name='Sheet4')
data['x'] = pd.to_datetime(data['x'])
data1 = data.set_index('x')
dailySpline = pd.DataFrame(datelist)
dailySpline['x'] = A
dailySpline = dailySpline.set_index(0)
ax = data1.plot(legend=False,
figsize=(8, 5),
x_compat=True,
linestyle='',
marker='o',
color='r')
ax = dailySpline.plot(legend=False, ax=ax)
return dailySpline
from CubicSpline import getTablesOfParameters,getSplineValue,remove_duplicates
data=pd.read_excel(r"\\data01\primissu\ERQA\Analytical Tasks\Syndication\Pricing templates\BootstrappingSwapCurve_francesco.xlsx",sheet_name='libor')
tableOfParameters=getTablesOfParameters(data)
#########################################################################################################
#plot the spline
#########################################################################################################
datelist = pd.date_range(start = data.loc[0,'date'], end = data.loc[len(data)-1,'date'] ).tolist()
Interpolation=[]
for i in range(len(datelist)):
interpolatedValue=getSplineValue(datelist[i],tableOfParameters)
Interpolation.append(interpolatedValue)
A=np.vstack(Interpolation)
data=pd.read_excel(r"\\data01\primissu\ERQA\Analytical Tasks\Syndication\Pricing templates\BootstrappingSwapCurve_francesco.xlsx",sheet_name='libor')
data1=data.set_index('date')
G1=pd.DataFrame(datelist)
G1['date']=A
G1=G1.set_index(0)
#ax = data1.plot(legend=False, figsize=(8, 5), x_compat=True,linestyle='',marker='o',color='r')
#ax = G.plot(legend=False,ax=ax)
#############################################################################################################
#setting coupon dates given cobdate
def getZCandDFCurve(AA, yearFrac, startingSet):
YF = pd.DataFrame(yearFrac)
AAA = list(AA.columns)
YF = YF.set_index([AAA])
zc = list(startingSet.iloc[0, :])
df = list(startingSet.iloc[1, :])
A = list(pd.to_datetime(list(startingSet.columns), format='%d/%m/%Y'))
splineDataFrame = pd.DataFrame()
row1 = AA.iloc[0, :]
row1 = row1[row1 != 0]
nextdf = df[-1]
#BondPV=100
A.append(row1.index[-1])
splineDataFrame['x'] = A
numberMissing = list(row1[1:-1].index)
#while BondPV!=0:
for l in range(100):
zc = list(startingSet.iloc[0, :])
df = list(startingSet.iloc[1, :])
dfGuess = nextdf
zcGuess = -m.log(dfGuess) / float(
YF[YF.index == row1.index[-1]].values)
zc.insert(len(zc), zcGuess)
splineDataFrame['y'] = zc
tableOfParameters = getTablesOfParameters(splineDataFrame)
Interp = []
newdf = []
#newzc=[]
for j in range(len(numberMissing)):
evaluationDate = row1.index[-2 - j]
if evaluationDate < pd.to_datetime(startingSet.columns[0],
format='%d/%m/%Y'):
interpolatedValue = startingSet.iloc[0, 0]
Interp.append(pd.Series(interpolatedValue))
else:
interpolatedValue = getSplineValue(evaluationDate,
tableOfParameters)
Interp.append(interpolatedValue)
newdf.append(
m.exp(-Interp[j].iloc[0] *
float(YF[YF.index == evaluationDate].values)))
newdf.reverse()
#newdf=m.exp(-Interp[0].iloc[0]*yearFrac[3])
Interp.reverse()
newzc = [Interp[i].iloc[0] for i in range(len(Interp))] + [zcGuess]
df = [1] + newdf + [dfGuess]
BondPV = (sum([row1.iloc[i] * df[i] for i in range(len(df))]))
nextdf = df[-1] + BondPV / 2 * -1
df = list(startingSet.iloc[1, :]) + df[1:]
zc = list(startingSet.iloc[0, :]) + newzc
A = list(pd.to_datetime(list(startingSet.columns), format='%d/%m/%Y'))
B = list(row1.index[1:])
A = A + B
splineDataFrame = pd.DataFrame()
if len(AA) == 1:
pass
else:
for i in range(1, len(AA)):
#
row1 = AA.iloc[i, :]
row1 = row1[row1 != 0]
nextdf = df[-1]
#BondPV=100
previuoszc = zc
previuosdf = df
A.append(row1.index[-1])
splineDataFrame['x'] = A
numberMissing = int(
np.where(AA.loc[i, :] > 1)[0] -
np.where(AA.loc[i - 1, :] > 1)[0] - 1)
if numberMissing == 0:
row1 = AA.iloc[i, :]
row1 = row1[row1 != 0]
nextdf = df[-1]
previuoszc = zc
previuosdf = df
numberMissing = int(
np.where(AA.loc[i, :] > 1)[0] -
np.where(AA.loc[i - 1, :] > 1)[0] - 1)
for l in range(100):
newdf = [1] + df[3:] + [nextdf]
BondPV = (sum(
[row1.iloc[i] * newdf[i] for i in range(len(newdf))]))
nextdf = newdf[-1] + BondPV / 2 * -1
df = list(startingSet.iloc[1, :]) + newdf[1:]
zc = zc + [
-m.log(newdf[-1]) /
float(YF[YF.index == row1.index[-1]].values)
]
A = list(
pd.to_datetime(list(startingSet.columns),
format='%d/%m/%Y'))
B = list(row1.index[1:])
A = A + B
splineDataFrame = pd.DataFrame()
else:
#while BondPV!=0:
for l in range(100):
zc = copy.copy(previuoszc)
df = copy.copy(previuosdf)
dfGuess = nextdf
zcGuess = -m.log(dfGuess) / float(
YF[YF.index == row1.index[-1]].values)
zc.insert(len(zc), zcGuess)
splineDataFrame['y'] = zc
tableOfParameters = getTablesOfParameters(splineDataFrame)
Interp = []
newdf = []
#newzc=[]
for j in range(numberMissing):
evaluationDate = row1.index[-2 - j]
interpolatedValue = getSplineValue(
evaluationDate, tableOfParameters)
Interp.append(interpolatedValue)
newdf.append(
m.exp(
-Interp[j].iloc[0] *
float(YF[YF.index == evaluationDate].values)))
newdf.reverse()
#newdf=m.exp(-Interp[0].iloc[0]*yearFrac[3])
Interp.reverse()
newzc = [Interp[i].iloc[0]
for i in range(len(Interp))] + [zcGuess]
#newzc=[Interp[0].iloc[0],zcGuess]
df = [1] + previuosdf[3:] + newdf + [dfGuess]
BondPV = (sum(
[row1.iloc[i] * df[i] for i in range(len(df))]))
nextdf = df[-1] + BondPV / 2 * -1
df = list(startingSet.iloc[1, :]) + df[1:]
zc = previuoszc + newzc
A = list(
pd.to_datetime(list(startingSet.columns),
format='%d/%m/%Y'))
B = list(row1.index[1:])
A = A + B
splineDataFrame = pd.DataFrame()
dataFrameDF = pd.DataFrame()
dataFrameDF['df'] = df
dataFrameDF = dataFrameDF.set_index([A])
dataFrameZC = pd.DataFrame()
dataFrameZC['ZC'] = zc
dataFrameZC = dataFrameZC.set_index([A])
return dataFrameDF, dataFrameZC
from CubicSpline import getTablesOfParameters, getSplineValue, remove_duplicates
data = pd.read_excel(
r"S:\Francesco\PRICING\presentation\BootstrappingSwapCurve_francesco_cobdate15feb2019.xlsx",
sheet_name='Sheet4')
tableOfParameters = getTablesOfParameters(data)
#########################################################################################################
#plot the spline
#########################################################################################################
datelist = pd.date_range(start=data.loc[0, 'x'],
end=data.loc[len(data) - 1, 'x']).tolist()
Interpolation = []
for i in range(len(datelist)):
interpolatedValue = getSplineValue(datelist[i], tableOfParameters)
Interpolation.append(interpolatedValue)
A = np.vstack(Interpolation)
data = pd.read_excel(
r"S:\Francesco\PRICING\presentation\BootstrappingSwapCurve_francesco_cobdate15feb2019.xlsx",
sheet_name='Sheet4')
data1 = data.set_index('x')
G = pd.DataFrame(datelist)
G['x'] = A
G = G.set_index(0)
#ax = data1.plot(legend=False, figsize=(8, 5), x_compat=True,linestyle='',marker='o',color='r')
#ax = G.plot(legend=False,ax=ax)
import matplotlib.pyplot as plt