def test_united_states_calendar(self):
uscal = UnitedStates()
holiday_date = Date(4, Jul, 2010)
self.assertTrue(uscal.is_holiday(holiday_date))
uscal = UnitedStates(market=NYSE)
holiday_date = Date(5, Sep, 2011) # Labor day
self.assertTrue(uscal.is_holiday(holiday_date))
class CalendarFactory:
_lookup = dict([(cal.name(), cal) for cal in [
TARGET(),
NullCalendar(),
Germany(),
Germany(EUREX),
Germany(FrankfurtStockExchange),
Germany(GER_SETTLEMENT),
Germany(EUWAX),
Germany(XETRA),
UnitedKingdom(),
UnitedKingdom(EXCHANGE),
UnitedKingdom(METALS),
UnitedKingdom(UK_SETTLEMENT),
UnitedStates(),
UnitedStates(GOVERNMENTBOND),
UnitedStates(NYSE),
UnitedStates(NERC),
UnitedStates(US_SETTLEMENT)
]])
def test_bucketanalysis_bond(self):
face_amount = 100.0
redemption = 100.0
issue_date = Date(27, January, 2011)
maturity_date = Date(1, January, 2021)
coupon_rate = 0.055
fixed_bond_schedule = Schedule.from_rule(
issue_date,
maturity_date,
Period(Semiannual),
UnitedStates(market=GovernmentBond),
Unadjusted,
Unadjusted,
Backward,
False)
bond = FixedRateBond(
self.settlement_days,
face_amount,
fixed_bond_schedule,
[coupon_rate],
ActualActual(Bond),
Unadjusted,
redemption,
issue_date
)
pricing_engine = DiscountingBondEngine(self.ts)
bond.set_pricing_engine(pricing_engine)
self.assertAlmostEqual(bond.npv, 100.82127876105724)
quotes = [rh.quote for rh in self.rate_helpers]
delta, gamma = bucket_analysis(quotes, [bond])
self.assertEqual(len(quotes), len(delta))
old_values = [q.value for q in quotes]
delta_manual = []
gamma_manual = []
pv = bond.npv
shift = 1e-4
for v, q in zip(old_values, quotes):
q.value = v + shift
pv_plus = bond.npv
q.value = v - shift
pv_minus = bond.npv
delta_manual.append((pv_plus - pv_minus) * 0.5 / shift)
gamma_manual.append((pv_plus - 2 * pv + pv_minus) / shift ** 2)
q.value = v
assert_allclose(delta, delta_manual)
assert_allclose(gamma, gamma_manual, atol=1e-4)
def test_united_states_calendar(self):
uscal = UnitedStates()
holiday_date = Date(4, Jul, 2010)
self.assertTrue(uscal.is_holiday(holiday_date))
uscal = UnitedStates(market=NYSE)
holiday_date = Date(5, Sep, 2011) # Labor day
self.assertTrue(uscal.is_holiday(holiday_date))
def test_joint(self):
ukcal = UnitedKingdom()
uscal = UnitedStates()
bank_holiday_date = Date(3, May, 2010) #Early May Bank Holiday
thanksgiving_holiday_date = Date(22, Nov, 2012)
jtcal = JointCalendar(ukcal, uscal, JOINHOLIDAYS)
self.assertFalse(jtcal.is_business_day(bank_holiday_date))
self.assertFalse(jtcal.is_business_day(thanksgiving_holiday_date))
jtcal = JointCalendar(ukcal, uscal, JOINBUSINESSDAYS)
self.assertTrue(jtcal.is_business_day(bank_holiday_date))
self.assertTrue(jtcal.is_business_day(thanksgiving_holiday_date))
def dividendOption():
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++ General Parameter for all the computation +++++++++++++++++++++++
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# declaration of the today's date (date where the records are done)
todaysDate = Date(24 , Jan ,2012) # INPUT
Settings.instance().evaluation_date = todaysDate #!\ IMPORTANT COMMAND REQUIRED FOR ALL VALUATIONS
calendar = UnitedStates() # INPUT
settlement_days = 2 # INPUT
# Calcul of the settlement date : need to add a period of 2 days to the todays date
settlementDate = calendar.advance(
todaysDate, period=Period(settlement_days, Days)
)
dayCounter = Actual360() # INPUT
currency = USDCurrency() # INPUT
print("Date of the evaluation: ", todaysDate)
print("Calendar used: ", calendar.name)
print("Number of settlement Days: ", settlement_days)
print("Date of settlement: ", settlementDate)
print("Convention of day counter: ", dayCounter.name)
print("Currency of the actual context:\t\t", currency.name)
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++ Description of the underlying +++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
underlying_name = "IBM"
underlying_price = 191.75 # INPUT
underlying_vol = 0.2094 # INPUT
print("**********************************")
print("Name of the underlying: ", underlying_name)
print("Price of the underlying at t0: ", underlying_price)
print("Volatility of the underlying: ", underlying_vol)
# For a great managing of price and vol objects --> Handle
underlying_priceH = SimpleQuote(underlying_price)
# We suppose the vol constant : his term structure is flat --> BlackConstantVol object
flatVolTS = BlackConstantVol(settlementDate, calendar, underlying_vol, dayCounter)
# ++++++++++++++++++++ Description of Yield Term Structure
# Libor data record
print("**********************************")
print("Description of the Libor used for the Yield Curve construction")
Libor_dayCounter = Actual360();
liborRates = []
liborRatesTenor = []
# INPUT : all the following data are input : the rate and the corresponding tenor
# You could make the choice of more or less data
# --> However you have tho choice the instruments with different maturities
liborRates = [ 0.002763, 0.004082, 0.005601, 0.006390, 0.007125, 0.007928, 0.009446,
0.01110]
liborRatesTenor = [Period(tenor, Months) for tenor in [1,2,3,4,5,6,9,12]]
for tenor, rate in zip(liborRatesTenor, liborRates):
print(tenor, "\t\t\t", rate)
# Swap data record
# description of the fixed leg of the swap
Swap_fixedLegTenor = Period(12, Months) # INPUT
Swap_fixedLegConvention = ModifiedFollowing # INPUT
Swap_fixedLegDayCounter = Actual360() # INPUT
# description of the float leg of the swap
Swap_iborIndex = Libor(
"USDLibor", Period(3,Months), settlement_days, USDCurrency(),
UnitedStates(), Actual360()
)
print("Description of the Swap used for the Yield Curve construction")
print("Tenor of the fixed leg: ", Swap_fixedLegTenor)
print("Index of the floated leg: ", Swap_iborIndex.name)
print("Maturity Rate ")
swapRates = []
swapRatesTenor = []
# INPUT : all the following data are input : the rate and the corresponding tenor
# You could make the choice of more or less data
# --> However you have tho choice the instruments with different maturities
swapRates = [0.005681, 0.006970, 0.009310, 0.012010, 0.014628, 0.016881, 0.018745,
0.020260, 0.021545]
swapRatesTenor = [Period(i, Years) for i in range(2, 11)]
for tenor, rate in zip(swapRatesTenor, swapRates):
print(tenor, "\t\t\t", rate)
# ++++++++++++++++++++ Creation of the vector of RateHelper (need for the Yield Curve construction)
# ++++++++++++++++++++ Libor
LiborFamilyName = currency.name + "Libor"
instruments = []
for rate, tenor in zip(liborRates, liborRatesTenor):
# Index description ___ creation of a Libor index
liborIndex = Libor(LiborFamilyName, tenor, settlement_days, currency, calendar,
Libor_dayCounter)
# Initialize rate helper ___ the DepositRateHelper link the recording rate with the Libor index
instruments.append(DepositRateHelper(rate, index=liborIndex))
# +++++++++++++++++++++ Swap
SwapFamilyName = currency.name + "swapIndex";
for tenor, rate in zip(swapRatesTenor, swapRates):
# swap description ___ creation of a swap index. The floating leg is described in the index 'Swap_iborIndex'
swapIndex = SwapIndex (SwapFamilyName, tenor, settlement_days, currency, calendar,
Swap_fixedLegTenor, Swap_fixedLegConvention, Swap_fixedLegDayCounter,
Swap_iborIndex)
# Initialize rate helper __ the SwapRateHelper links the swap index width his rate
instruments.append(SwapRateHelper.from_index(rate, swapIndex))
# ++++++++++++++++++ Now the creation of the yield curve
riskFreeTS = PiecewiseYieldCurve.from_reference_date(BootstrapTrait.ZeroYield,
Interpolator.Linear, settlementDate, instruments, dayCounter)
# ++++++++++++++++++ build of the underlying process : with a Black-Scholes model
print('Creating process')
bsProcess = BlackScholesProcess(underlying_priceH, riskFreeTS, flatVolTS)
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++ Description of the option +++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Option_name = "IBM Option"
maturity = Date(26, Jan, 2013)
strike = 190
option_type = Call
# Here, as an implementation exemple, we make the test with borth american and european exercise
europeanExercise = EuropeanExercise(maturity)
# The emericanExercise need also the settlement date, as his right to exerce the buy or call start at the settlement date!
#americanExercise = AmericanExercise(settlementDate, maturity)
americanExercise = AmericanExercise(maturity, settlementDate)
print("**********************************")
print("Description of the option: ", Option_name)
print("Date of maturity: ", maturity)
print("Type of the option: ", option_type)
print("Strike of the option: ", strike)
# ++++++++++++++++++ Description of the discrete dividends
# INPUT You have to determine the frequece and rates of the discrete dividend. Here is a sollution, but she's not the only one.
# Last know dividend:
dividend = 0.75 #//0.75
next_dividend_date = Date(10,Feb,2012)
# HERE we have make the assumption that the dividend will grow with the quarterly croissance:
dividendCroissance = 1.03
dividendfrequence = Period(3, Months)
dividendDates = []
dividends = []
d = next_dividend_date
while d <= maturity:
dividendDates.append(d)
dividends.append(dividend)
d = d + dividendfrequence
dividend *= dividendCroissance
print("Discrete dividends ")
print("Dates Dividends ")
for date, div in zip(dividendDates, dividends):
print(date, " ", div)
# ++++++++++++++++++ Description of the final payoff
payoff = PlainVanillaPayoff(option_type, strike)
# ++++++++++++++++++ The OPTIONS : (American and European) with their dividends description:
dividendEuropeanOption = DividendVanillaOption(
payoff, europeanExercise, dividendDates, dividends
)
dividendAmericanOption = DividendVanillaOption(
payoff, americanExercise, dividendDates, dividends
)
# just too test
europeanOption = VanillaOption(payoff, europeanExercise)
americanOption = VanillaOption(payoff, americanExercise)
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++ Description of the pricing +++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# For the european options we have a closed analytic formula: The Black Scholes:
dividendEuropeanEngine = AnalyticDividendEuropeanEngine(bsProcess)
# For the american option we have make the choice of the finite difference model with the CrankNicolson scheme
# this model need to precise the time and space step
# More they are greater, more the calul will be precise.
americanGirdPoints = 600
americanTimeSteps = 600
dividendAmericanEngine = FDDividendAmericanEngine('CrankNicolson', bsProcess,americanTimeSteps, americanGirdPoints)
# just to test
europeanEngine = AnalyticEuropeanEngine(bsProcess)
americanEngine = FDAmericanEngine('CrankNicolson', bsProcess,americanTimeSteps, americanGirdPoints)
# ++++++++++++++++++++ Valorisation ++++++++++++++++++++++++++++++++++++++++
# Link the pricing Engine to the option
dividendEuropeanOption.set_pricing_engine(dividendEuropeanEngine)
dividendAmericanOption.set_pricing_engine(dividendAmericanEngine)
# just to test
europeanOption.set_pricing_engine(europeanEngine)
americanOption.set_pricing_engine(americanEngine)
# Now we make all the needing calcul
# ... and final results
print("NPV of the European Option with discrete dividends=0: {:.4f}".format(dividendEuropeanOption.npv))
print("NPV of the European Option without dividend: {:.4f}".format(europeanOption.npv))
print("NPV of the American Option with discrete dividends=0: {:.4f}".format(dividendAmericanOption.npv))
print("NPV of the American Option without dividend: {:.4f}".format(americanOption.npv))
# just a single test
print("ZeroRate with a maturity at ", maturity, ": ", \
riskFreeTS.zero_rate(maturity, dayCounter, Simple))
def dividendOption():
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++ General Parameter for all the computation +++++++++++++++++++++++
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# declaration of the today's date (date where the records are done)
todaysDate = Date(24, Jan, 2012) # INPUT
Settings.instance(
).evaluation_date = todaysDate #!\ IMPORTANT COMMAND REQUIRED FOR ALL VALUATIONS
calendar = UnitedStates() # INPUT
settlement_days = 2 # INPUT
# Calcul of the settlement date : need to add a period of 2 days to the todays date
settlementDate = calendar.advance(todaysDate,
period=Period(settlement_days, Days))
dayCounter = Actual360() # INPUT
currency = USDCurrency() # INPUT
print("Date of the evaluation: ", todaysDate)
print("Calendar used: ", calendar.name)
print("Number of settlement Days: ", settlement_days)
print("Date of settlement: ", settlementDate)
print("Convention of day counter: ", dayCounter.name())
print("Currency of the actual context:\t\t", currency.name)
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++ Description of the underlying +++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
underlying_name = "IBM"
underlying_price = 191.75 # INPUT
underlying_vol = 0.2094 # INPUT
print("**********************************")
print("Name of the underlying: ", underlying_name)
print("Price of the underlying at t0: ", underlying_price)
print("Volatility of the underlying: ", underlying_vol)
# For a great managing of price and vol objects --> Handle
underlying_priceH = SimpleQuote(underlying_price)
# We suppose the vol constant : his term structure is flat --> BlackConstantVol object
flatVolTS = BlackConstantVol(settlementDate, calendar, underlying_vol,
dayCounter)
# ++++++++++++++++++++ Description of Yield Term Structure
# Libor data record
print("**********************************")
print("Description of the Libor used for the Yield Curve construction")
Libor_dayCounter = Actual360()
liborRates = []
liborRatesTenor = []
# INPUT : all the following data are input : the rate and the corresponding tenor
# You could make the choice of more or less data
# --> However you have tho choice the instruments with different maturities
liborRates = [
0.002763, 0.004082, 0.005601, 0.006390, 0.007125, 0.007928, 0.009446,
0.01110
]
liborRatesTenor = [
Period(tenor, Months) for tenor in [1, 2, 3, 4, 5, 6, 9, 12]
]
for tenor, rate in zip(liborRatesTenor, liborRates):
print(tenor, "\t\t\t", rate)
# Swap data record
# description of the fixed leg of the swap
Swap_fixedLegTenor = Period(12, Months) # INPUT
Swap_fixedLegConvention = ModifiedFollowing # INPUT
Swap_fixedLegDayCounter = Actual360() # INPUT
# description of the float leg of the swap
Swap_iborIndex = Libor("USDLibor", Period(3, Months), settlement_days,
USDCurrency(), UnitedStates(), Actual360())
print("Description of the Swap used for the Yield Curve construction")
print("Tenor of the fixed leg: ", Swap_fixedLegTenor)
print("Index of the floated leg: ", Swap_iborIndex.name)
print("Maturity Rate ")
swapRates = []
swapRatesTenor = []
# INPUT : all the following data are input : the rate and the corresponding tenor
# You could make the choice of more or less data
# --> However you have tho choice the instruments with different maturities
swapRates = [
0.005681, 0.006970, 0.009310, 0.012010, 0.014628, 0.016881, 0.018745,
0.020260, 0.021545
]
swapRatesTenor = [Period(i, Years) for i in range(2, 11)]
for tenor, rate in zip(swapRatesTenor, swapRates):
print(tenor, "\t\t\t", rate)
# ++++++++++++++++++++ Creation of the vector of RateHelper (need for the Yield Curve construction)
# ++++++++++++++++++++ Libor
LiborFamilyName = currency.name + "Libor"
instruments = []
for rate, tenor in zip(liborRates, liborRatesTenor):
# Index description ___ creation of a Libor index
liborIndex = Libor(LiborFamilyName, tenor, settlement_days, currency,
calendar, Libor_dayCounter)
# Initialize rate helper ___ the DepositRateHelper link the recording rate with the Libor index
instruments.append(DepositRateHelper(rate, index=liborIndex))
# +++++++++++++++++++++ Swap
SwapFamilyName = currency.name + "swapIndex"
for tenor, rate in zip(swapRatesTenor, swapRates):
# swap description ___ creation of a swap index. The floating leg is described in the index 'Swap_iborIndex'
swapIndex = SwapIndex(SwapFamilyName, tenor, settlement_days, currency,
calendar, Swap_fixedLegTenor,
Swap_fixedLegConvention, Swap_fixedLegDayCounter,
Swap_iborIndex)
# Initialize rate helper __ the SwapRateHelper links the swap index width his rate
instruments.append(SwapRateHelper.from_index(rate, swapIndex))
# ++++++++++++++++++ Now the creation of the yield curve
riskFreeTS = PiecewiseYieldCurve.from_reference_date(
BootstrapTrait.ZeroYield, Interpolator.Linear, settlementDate,
instruments, dayCounter)
# ++++++++++++++++++ build of the underlying process : with a Black-Scholes model
print('Creating process')
bsProcess = BlackScholesProcess(underlying_priceH, riskFreeTS, flatVolTS)
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++ Description of the option +++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Option_name = "IBM Option"
maturity = Date(26, Jan, 2013)
strike = 190
option_type = 'call'
# Here, as an implementation exemple, we make the test with borth american and european exercise
europeanExercise = EuropeanExercise(maturity)
# The emericanExercise need also the settlement date, as his right to exerce the buy or call start at the settlement date!
#americanExercise = AmericanExercise(settlementDate, maturity)
americanExercise = AmericanExercise(maturity, settlementDate)
print("**********************************")
print("Description of the option: ", Option_name)
print("Date of maturity: ", maturity)
print("Type of the option: ", option_type)
print("Strike of the option: ", strike)
# ++++++++++++++++++ Description of the discrete dividends
# INPUT You have to determine the frequece and rates of the discrete dividend. Here is a sollution, but she's not the only one.
# Last know dividend:
dividend = 0.75 #//0.75
next_dividend_date = Date(10, Feb, 2012)
# HERE we have make the assumption that the dividend will grow with the quarterly croissance:
dividendCroissance = 1.03
dividendfrequence = Period(3, Months)
dividendDates = []
dividends = []
d = next_dividend_date
while d <= maturity:
dividendDates.append(d)
dividends.append(dividend)
d = d + dividendfrequence
dividend *= dividendCroissance
print("Discrete dividends ")
print("Dates Dividends ")
for date, div in zip(dividendDates, dividends):
print(date, " ", div)
# ++++++++++++++++++ Description of the final payoff
payoff = PlainVanillaPayoff(option_type, strike)
# ++++++++++++++++++ The OPTIONS : (American and European) with their dividends description:
dividendEuropeanOption = DividendVanillaOption(payoff, europeanExercise,
dividendDates, dividends)
dividendAmericanOption = DividendVanillaOption(payoff, americanExercise,
dividendDates, dividends)
# just too test
europeanOption = VanillaOption(payoff, europeanExercise)
americanOption = VanillaOption(payoff, americanExercise)
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++ Description of the pricing +++++++++++++++++++++++++++++++++++++
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# For the european options we have a closed analytic formula: The Black Scholes:
dividendEuropeanEngine = AnalyticDividendEuropeanEngine(bsProcess)
# For the american option we have make the choice of the finite difference model with the CrankNicolson scheme
# this model need to precise the time and space step
# More they are greater, more the calul will be precise.
americanGirdPoints = 600
americanTimeSteps = 600
dividendAmericanEngine = FDDividendAmericanEngine('CrankNicolson',
bsProcess,
americanTimeSteps,
americanGirdPoints)
# just to test
europeanEngine = AnalyticEuropeanEngine(bsProcess)
americanEngine = FDAmericanEngine('CrankNicolson', bsProcess,
americanTimeSteps, americanGirdPoints)
# ++++++++++++++++++++ Valorisation ++++++++++++++++++++++++++++++++++++++++
# Link the pricing Engine to the option
dividendEuropeanOption.set_pricing_engine(dividendEuropeanEngine)
dividendAmericanOption.set_pricing_engine(dividendAmericanEngine)
# just to test
europeanOption.set_pricing_engine(europeanEngine)
americanOption.set_pricing_engine(americanEngine)
# Now we make all the needing calcul
# ... and final results
print(
"NPV of the European Option with discrete dividends=0: {:.4f}".format(
dividendEuropeanOption.npv))
print("NPV of the European Option without dividend: {:.4f}".format(
europeanOption.npv))
print(
"NPV of the American Option with discrete dividends=0: {:.4f}".format(
dividendAmericanOption.npv))
print("NPV of the American Option without dividend: {:.4f}".format(
americanOption.npv))
# just a single test
print("ZeroRate with a maturity at ", maturity, ": ", \
riskFreeTS.zero_rate(maturity, dayCounter, Simple))
def test_pricing_bond(self):
'''Inspired by the C++ code from http://quantcorner.wordpress.com/.'''
settings = Settings()
# Date setup
calendar = TARGET()
# Settlement date
settlement_date = calendar.adjust(Date(28, January, 2011))
# Evaluation date
fixing_days = 1
settlement_days = 1
todays_date = calendar.advance(settlement_date, -fixing_days, Days)
settings.evaluation_date = todays_date
# Bound attributes
face_amount = 100.0
redemption = 100.0
issue_date = Date(27, January, 2011)
maturity_date = Date(31, August, 2020)
coupon_rate = 0.03625
bond_yield = 0.034921
discounting_term_structure = YieldTermStructure(relinkable=True)
flat_term_structure = FlatForward(
reference_date=settlement_date,
forward=bond_yield,
daycounter=Actual365Fixed(
), #actual_actual.ActualActual(actual_actual.Bond),
compounding=Compounded,
frequency=Semiannual)
# have a look at the FixedRateBondHelper to simplify this
# construction
discounting_term_structure.link_to(flat_term_structure)
#Rate
fixed_bond_schedule = Schedule(issue_date, maturity_date,
Period(Semiannual),
UnitedStates(market=GOVERNMENTBOND),
Unadjusted, Unadjusted, Backward, False)
bond = FixedRateBond(settlement_days, face_amount,
fixed_bond_schedule, [coupon_rate],
ActualActual(Bond), Unadjusted, redemption,
issue_date)
bond.set_pricing_engine(discounting_term_structure)
# tests
self.assertTrue(Date(27, January, 2011), bond.issue_date)
self.assertTrue(Date(31, August, 2020), bond.maturity_date)
self.assertTrue(settings.evaluation_date, bond.valuation_date)
# the following assertion fails but must be verified
self.assertAlmostEqual(101.1, bond.clean_price, 1)
self.assertAlmostEqual(101.1, bond.net_present_value, 1)
self.assertAlmostEqual(101.1, bond.dirty_price)
self.assertAlmostEqual(0.009851, bond.accrued_amount())
print(settings.evaluation_date)
print('Principal: {}'.format(face_amount))
print('Issuing date: {} '.format(bond.issue_date))
print('Maturity: {}'.format(bond.maturity_date))
print('Coupon rate: {:.4%}'.format(coupon_rate))
print('Yield: {:.4%}'.format(bond_yield))
print('Net present value: {:.4f}'.format(bond.net_present_value))
print('Clean price: {:.4f}'.format(bond.clean_price))
print('Dirty price: {:.4f}'.format(bond.dirty_price))
print('Accrued coupon: {:.6f}'.format(bond.accrued_amount()))
print('Accrued coupon: {:.6f}'.format(
bond.accrued_amount(Date(1, March, 2011))))
def test_excel_example_with_floating_rate_bond(self):
todays_date = Date(25, August, 2011)
settings = Settings()
settings.evaluation_date = todays_date
calendar = TARGET()
effective_date = Date(10, Jul, 2006)
termination_date = calendar.advance(effective_date,
10,
Years,
convention=Unadjusted)
settlement_date = calendar.adjust(Date(28, January, 2011))
settlement_days = 3 #1
face_amount = 13749769.27 #2
coupon_rate = 0.05
redemption = 100.0
float_bond_schedule = Schedule(effective_date, termination_date,
Period(Annual), calendar,
ModifiedFollowing, ModifiedFollowing,
Backward) #3
flat_discounting_term_structure = YieldTermStructure(relinkable=True)
forecastTermStructure = YieldTermStructure(relinkable=True)
dc = Actual360()
ibor_index = Euribor6M(forecastTermStructure) #5
fixing_days = 2 #6
gearings = [1, 0.0] #7
spreads = [1, 0.05] #8
caps = [] #9
floors = [] #10
pmt_conv = ModifiedFollowing #11
issue_date = effective_date
float_bond = FloatingRateBond(settlement_days, face_amount,
float_bond_schedule, ibor_index, dc,
fixing_days, gearings, spreads, caps,
floors, pmt_conv, redemption, issue_date)
flat_term_structure = FlatForward(settlement_days=1,
forward=0.055,
calendar=NullCalendar(),
daycounter=Actual365Fixed(),
compounding=Continuous,
frequency=Annual)
flat_discounting_term_structure.link_to(flat_term_structure)
forecastTermStructure.link_to(flat_term_structure)
engine = DiscountingBondEngine(flat_discounting_term_structure)
float_bond.set_pricing_engine(engine)
cons_option_vol = ConstantOptionletVolatility(settlement_days,
UnitedStates(SETTLEMENT),
pmt_conv, 0.95,
Actual365Fixed())
coupon_pricer = BlackIborCouponPricer(cons_option_vol)
set_coupon_pricer(float_bond, coupon_pricer)
self.assertEquals(Date(10, Jul, 2016), termination_date)
self.assertEquals(calendar.advance(todays_date, 3, Days),
float_bond.settlement_date())
self.assertEquals(Date(11, Jul, 2016), float_bond.maturity_date)
self.assertAlmostEqual(
0.6944, float_bond.accrued_amount(float_bond.settlement_date()), 4)
self.assertAlmostEqual(98.2485, float_bond.dirty_price, 4)
self.assertAlmostEqual(13500805.2469, float_bond.npv, 4)
def test_display(self):
settings = Settings()
# Date setup
calendar = TARGET()
# Settlement date
settlement_date = calendar.adjust(Date(28, January, 2011))
# Evaluation date
fixing_days = 1
settlement_days = 1
todays_date = calendar.advance(
settlement_date, -fixing_days, Days
)
settings.evaluation_date = todays_date
# Bound attributes
face_amount = 100.0
redemption = 100.0
issue_date = Date(27, January, 2011)
maturity_date = Date(31, August, 2020)
coupon_rate = 0.03625
bond_yield = 0.034921
flat_discounting_term_structure = YieldTermStructure()
flat_term_structure = FlatForward(
reference_date = settlement_date,
forward = bond_yield,
daycounter = Actual365Fixed(), #actual_actual.ActualActual(actual_actual.Bond),
compounding = Compounded,
frequency = Semiannual)
# have a look at the FixedRateBondHelper to simplify this
# construction
flat_discounting_term_structure.link_to(flat_term_structure)
#Rate
fixed_bond_schedule = Schedule(
issue_date,
maturity_date,
Period(Semiannual),
UnitedStates(market=GOVERNMENTBOND),
Unadjusted,
Unadjusted,
Backward,
False);
bond = FixedRateBond(
settlement_days,
face_amount,
fixed_bond_schedule,
[coupon_rate],
ActualActual(Bond),
Unadjusted,
redemption,
issue_date
)
d=bf.startDate(bond)
zspd=bf.zSpread(bond, 100.0, flat_term_structure, Actual365Fixed(),
Compounded, Semiannual, settlement_date, 1e-6, 100, 0.5)
#Also need a test case for a PiecewiseTermStructure...
depositData = [[ 1, Months, 4.581 ],
[ 2, Months, 4.573 ],
[ 3, Months, 4.557 ],
[ 6, Months, 4.496 ],
[ 9, Months, 4.490 ]]
swapData = [[ 1, Years, 4.54 ],
[ 5, Years, 4.99 ],
[ 10, Years, 5.47 ],
[ 20, Years, 5.89 ],
[ 30, Years, 5.96 ]]
rate_helpers = []
end_of_month = True
for m, period, rate in depositData:
tenor = Period(m, Months)
helper = DepositRateHelper(SimpleQuote(rate/100), tenor, settlement_days,
calendar, ModifiedFollowing, end_of_month,
Actual360())
rate_helpers.append(helper)
liborIndex = Libor('USD Libor', Period(6, Months), settlement_days,
USDCurrency(), calendar, Actual360(),
YieldTermStructure(relinkable=False))
spread = SimpleQuote(0)
fwdStart = Period(0, Days)
for m, period, rate in swapData:
helper = SwapRateHelper.from_tenor(
SimpleQuote(rate/100), Period(m, Years), calendar, Annual, Unadjusted, Thirty360(), liborIndex,
spread, fwdStart
)
rate_helpers.append(helper)
ts_day_counter = ActualActual(ISDA)
tolerance = 1.0e-15
ts = PiecewiseYieldCurve.from_reference_date(
BootstrapTrait.Discount, Interpolator.LogLinear, settlement_date, rate_helpers,
ts_day_counter, tolerance)
pyc_zspd=bf.zSpread(bond, 102.0, ts, ActualActual(ISDA),
Compounded, Semiannual, Date(1, April, 2015), 1e-6, 100, 0.5)
pyc_zspd_disco=bf.zSpread(bond, 95.0, ts, ActualActual(ISDA),
Compounded, Semiannual, settlement_date, 1e-6, 100, 0.5)
yld = bf.yld(bond, 102.0, ActualActual(ISDA), Compounded, Semiannual, settlement_date, 1e-6, 100, 0.5)
dur = bf.duration(bond, yld, ActualActual(ISDA), Compounded, Semiannual, 2, settlement_date)
yld_disco = bf.yld(bond, 95.0, ActualActual(ISDA), Compounded, Semiannual, settlement_date, 1e-6, 100, 0.5)
dur_disco = bf.duration(bond, yld_disco, ActualActual(ISDA), Compounded, Semiannual, 2, settlement_date)
self.assertEqual(round(zspd, 6), 0.001281)
self.assertEqual(round(pyc_zspd, 4), -0.0264)
self.assertEqual(round(pyc_zspd_disco, 4), -0.0114)
self.assertEqual(round(yld, 4), 0.0338)
self.assertEqual(round(yld_disco, 4), 0.0426)
self.assertEqual(round(dur, 4), 8.0655)
self.assertEqual(round(dur_disco, 4), 7.9702)
def test_bucketanalysis_bond(self):
settings = Settings()
calendar = TARGET()
settlement_date = calendar.adjust(Date(28, January, 2011))
simple_quotes = []
fixing_days = 1
settlement_days = 1
todays_date = calendar.advance(settlement_date, -fixing_days, Days)
settings.evaluation_date = todays_date
face_amount = 100.0
redemption = 100.0
issue_date = Date(27, January, 2011)
maturity_date = Date(1, January, 2021)
coupon_rate = 0.055
bond_yield = 0.034921
flat_discounting_term_structure = YieldTermStructure()
flat_term_structure = FlatForward(reference_date=settlement_date,
forward=bond_yield,
daycounter=Actual365Fixed(),
compounding=Compounded,
frequency=Semiannual)
flat_discounting_term_structure.link_to(flat_term_structure)
fixed_bond_schedule = Schedule.from_rule(
issue_date, maturity_date, Period(Semiannual),
UnitedStates(market=GovernmentBond), Unadjusted, Unadjusted,
Backward, False)
bond = FixedRateBond(settlement_days, face_amount,
fixed_bond_schedule, [coupon_rate],
ActualActual(Bond), Unadjusted, redemption,
issue_date)
zspd = bf.zSpread(bond, 100.0, flat_term_structure, Actual365Fixed(),
Compounded, Semiannual, settlement_date, 1e-6, 100,
0.5)
depositData = [[1, Months, 4.581], [2, Months, 4.573],
[3, Months, 4.557], [6, Months, 4.496],
[9, Months, 4.490]]
swapData = [[1, Years, 4.54], [5, Years, 4.99], [10, Years, 5.47],
[20, Years, 5.89], [30, Years, 5.96]]
rate_helpers = []
end_of_month = True
for m, period, rate in depositData:
tenor = Period(m, Months)
sq_rate = SimpleQuote(rate / 100)
helper = DepositRateHelper(sq_rate, tenor, settlement_days,
calendar, ModifiedFollowing,
end_of_month, Actual360())
simple_quotes.append(sq_rate)
rate_helpers.append(helper)
liborIndex = Libor('USD Libor', Period(6, Months), settlement_days,
USDCurrency(), calendar, Actual360())
spread = SimpleQuote(0)
fwdStart = Period(0, Days)
for m, period, rate in swapData:
sq_rate = SimpleQuote(rate / 100)
helper = SwapRateHelper.from_tenor(sq_rate, Period(m, Years),
calendar, Annual, Unadjusted,
Thirty360(), liborIndex, spread,
fwdStart)
simple_quotes.append(sq_rate)
rate_helpers.append(helper)
ts_day_counter = ActualActual(ISDA)
tolerance = 1.0e-15
ts = PiecewiseYieldCurve.from_reference_date(BootstrapTrait.Discount,
Interpolator.LogLinear,
settlement_date,
rate_helpers,
ts_day_counter, tolerance)
discounting_term_structure = YieldTermStructure()
discounting_term_structure.link_to(ts)
pricing_engine = DiscountingBondEngine(discounting_term_structure)
bond.set_pricing_engine(pricing_engine)
self.assertAlmostEqual(bond.npv, 100.83702940160767)
ba = bucket_analysis([simple_quotes], [bond], [1], 0.0001, 1)
self.assertTrue(2, ba)
self.assertTrue(type(tuple), ba)
self.assertEqual(len(simple_quotes), len(ba[0][0]))
self.assertEqual(0, ba[0][0][8])
class Calendars(dict):
'''
Wrapper for quantlib Calendar objects and methods.
Accepts python.datetime objects and strings
instead of pyql.quantlib dates.
:adjust: Adjust date to business day
:advance: Advance date by specified period
:is_business_day: Checks date
can be used as a dict using name property of pyql.quantlib.calendar objects
for example:
Calendars()['TARGET'] returns TARGET calendar
'''
from quantlib.time.calendar import TARGET
from quantlib.time.calendars.null_calendar import NullCalendar
from quantlib.time.calendars.germany import (
Germany, EUREX, FrankfurtStockExchange, SETTLEMENT as GER_SETTLEMENT,
EUWAX, XETRA
)
from quantlib.time.calendars.united_kingdom import (
EXCHANGE, METALS, SETTLEMENT as UK_SETTLEMENT,
UnitedKingdom
)
from quantlib.time.calendars.united_states import (
UnitedStates, GOVERNMENTBOND, NYSE, NERC, SETTLEMENT as US_SETTLEMENT
)
_lookup = dict([(cal.name(), cal) for cal in
[TARGET(), NullCalendar(),
Germany(), Germany(EUREX), Germany(
FrankfurtStockExchange),
Germany(GER_SETTLEMENT), Germany(
EUWAX), Germany(XETRA),
UnitedKingdom(),
UnitedKingdom(EXCHANGE), UnitedKingdom(METALS),
UnitedKingdom(UK_SETTLEMENT),
UnitedStates(),
UnitedStates(GOVERNMENTBOND), UnitedStates(
NYSE), UnitedStates(NERC),
UnitedStates(US_SETTLEMENT)]
]
)
def __init__(self, *args):
dict.__init__(self, self._lookup)
self.update(*args)
@classmethod
def adjust(cls, date, calendar=None, convention=None):
if not calendar:
calendar = cls.TARGET()
elif not hasattr(calendar, "adjust"):
return None
if not convention:
convention = BusinessDayConventions.Following
qldate = qldate_from_pydate(pydate(date))
try:
return pydate_from_qldate(calendar.adjust(qldate, convention))
except:
try:
return pydate_from_qldate(calendar().adjust(qldate,
convention))
except:
return None
@classmethod
def advance(cls, date, n, timeunit=None, calendar=None, convention=None):
"""
Advance pydate according the specified calendar and convention
:pydate: e.g. 19600809, date(1964, 9, 29), '5-23-1993'
:n: integer
:timeunit: e.g., enums.TimeUnits.Days
usage
-----
Note 9/6/1980 is a weekend
>>> Calendars.advance(19800906, 1)
datetime.date(1980, 9, 8)
"""
if not calendar:
calendar = cls.TARGET()
elif not hasattr(calendar, "advance"):
return None
if not convention:
convention = BusinessDayConventions.Following
if not timeunit:
timeunit = TimeUnits.Days
qldate = qldate_from_pydate(pydate(date))
try:
return pydate_from_qldate(calendar.advance(qldate, n, timeunit))
except:
try:
return pydate_from_qldate(
calendar().advance(qldate, n, timeunit)
)
except:
print("failure {}".format(qldate))
return None
@classmethod
def is_business_day(cls, date, calendar=None):
if not calendar:
calendar = cls.TARGET()
elif not hasattr(calendar, "advance"):
return None
qldate = qldate_from_pydate(pydate(date))
try:
return calendar.is_business_day(qldate)
except:
try:
return calendar().is_business_day(qldate)
except:
return None