def test_BondPortfolio():
import pandas as pd
path = os.path.join(os.path.dirname(__file__), './data/giltBondPrices.txt')
bondDataFrame = pd.read_csv(path, sep='\t')
bondDataFrame['mid'] = 0.5*(bondDataFrame['bid'] + bondDataFrame['ask'])
freq_type = FrequencyTypes.SEMI_ANNUAL
accrual_type = DayCountTypes.ACT_ACT_ICMA
settlement = Date(19, 9, 2012)
testCases.header("DCTYPE", "MATDATE", "CPN", "PRICE", "ACCD", "YTM")
for accrual_type in DayCountTypes:
for _, bond in bondDataFrame.iterrows():
date_string = bond['maturity']
matDatetime = dt.datetime.strptime(date_string, '%d-%b-%y')
maturityDt = from_datetime(matDatetime)
issueDt = Date(maturityDt._d, maturityDt._m, 2000)
coupon = bond['coupon']/100.0
clean_price = bond['mid']
bond = Bond(issueDt, maturityDt,
coupon, freq_type, accrual_type)
ytm = bond.yield_to_maturity(settlement, clean_price)
accrued_interest = bond._accrued_interest
testCases.print(accrual_type, maturityDt, coupon*100.0,
clean_price, accrued_interest, ytm*100.0)
def test_BondZeroCurve():
import pandas as pd
path = os.path.join(os.path.dirname(__file__), './data/giltBondPrices.txt')
bondDataFrame = pd.read_csv(path, sep='\t')
bondDataFrame['mid'] = 0.5 * (bondDataFrame['bid'] + bondDataFrame['ask'])
freq_type = FrequencyTypes.SEMI_ANNUAL
accrual_type = DayCountTypes.ACT_ACT_ICMA
settlement = Date(19, 9, 2012)
bonds = []
clean_prices = []
for _, bondRow in bondDataFrame.iterrows():
date_string = bondRow['maturity']
matDatetime = dt.datetime.strptime(date_string, '%d-%b-%y')
maturityDt = from_datetime(matDatetime)
issueDt = Date(maturityDt._d, maturityDt._m, 2000)
coupon = bondRow['coupon'] / 100.0
clean_price = bondRow['mid']
bond = Bond(issueDt, maturityDt, coupon, freq_type, accrual_type)
bonds.append(bond)
clean_prices.append(clean_price)
###############################################################################
bondCurve = BondZeroCurve(settlement, bonds, clean_prices)
testCases.header("DATE", "ZERO RATE")
for _, bond in bondDataFrame.iterrows():
date_string = bond['maturity']
matDatetime = dt.datetime.strptime(date_string, '%d-%b-%y')
maturityDt = from_datetime(matDatetime)
zero_rate = bondCurve.zero_rate(maturityDt)
testCases.print(maturityDt, zero_rate)
if plotGraphs:
bondCurve.plot("BOND CURVE")
def test_BondYieldCurve():
###########################################################################
import pandas as pd
path = os.path.join(os.path.dirname(__file__), './data/giltBondPrices.txt')
bondDataFrame = pd.read_csv(path, sep='\t')
bondDataFrame['mid'] = 0.5 * (bondDataFrame['bid'] + bondDataFrame['ask'])
freq_type = FrequencyTypes.SEMI_ANNUAL
accrual_type = DayCountTypes.ACT_ACT_ICMA
settlement = Date(19, 9, 2012)
bonds = []
ylds = []
for _, bond in bondDataFrame.iterrows():
date_string = bond['maturity']
matDatetime = dt.datetime.strptime(date_string, '%d-%b-%y')
maturityDt = from_datetime(matDatetime)
issueDt = Date(maturityDt._d, maturityDt._m, 2000)
coupon = bond['coupon'] / 100.0
clean_price = bond['mid']
bond = Bond(issueDt, maturityDt, coupon, freq_type, accrual_type)
yld = bond.yield_to_maturity(settlement, clean_price)
bonds.append(bond)
ylds.append(yld)
###############################################################################
curveFitMethod = CurveFitPolynomial()
fittedCurve1 = BondYieldCurve(settlement, bonds, ylds, curveFitMethod)
# fittedCurve1.display("GBP Yield Curve")
curveFitMethod = CurveFitPolynomial(5)
fittedCurve2 = BondYieldCurve(settlement, bonds, ylds, curveFitMethod)
# fittedCurve2.display("GBP Yield Curve")
curveFitMethod = CurveFitNelsonSiegel()
fittedCurve3 = BondYieldCurve(settlement, bonds, ylds, curveFitMethod)
# fittedCurve3.display("GBP Yield Curve")
curveFitMethod = CurveFitNelsonSiegelSvensson()
fittedCurve4 = BondYieldCurve(settlement, bonds, ylds, curveFitMethod)
# fittedCurve4.display("GBP Yield Curve")
curveFitMethod = CurveFitBSpline()
fittedCurve5 = BondYieldCurve(settlement, bonds, ylds, curveFitMethod)
# fittedCurve5.display("GBP Yield Curve")
###############################################################################
testCases.header("PARAMETER", "VALUE")
testCases.print("values", fittedCurve1._curveFit._coeffs)
testCases.header("PARAMETER", "VALUE")
testCases.print("values", fittedCurve2._curveFit._coeffs)
testCases.header("PARAMETER", "VALUE")
testCases.print("beta1", fittedCurve3._curveFit._beta1)
testCases.print("beta2", fittedCurve3._curveFit._beta2)
testCases.print("beta3", fittedCurve3._curveFit._beta3)
testCases.print("tau", fittedCurve3._curveFit._tau)
testCases.header("PARAMETER", "VALUE")
testCases.print("beta1", fittedCurve4._curveFit._beta1)
testCases.print("beta2", fittedCurve4._curveFit._beta2)
testCases.print("beta3", fittedCurve4._curveFit._beta3)
testCases.print("beta4", fittedCurve4._curveFit._beta4)
testCases.print("tau1", fittedCurve4._curveFit._tau1)
testCases.print("tau2", fittedCurve4._curveFit._tau2)
###############################################################################
maturity_date = Date(19, 9, 2030)
interpolated_yield = fittedCurve5.interpolated_yield(maturity_date)
testCases.print(maturity_date, interpolated_yield)
def test_Bond():
import pandas as pd
path = os.path.join(os.path.dirname(__file__), './data/giltBondPrices.txt')
bondDataFrame = pd.read_csv(path, sep='\t')
bondDataFrame['mid'] = 0.5 * (bondDataFrame['bid'] + bondDataFrame['ask'])
freq_type = FrequencyTypes.SEMI_ANNUAL
settlement_date = Date(19, 9, 2012)
face = ONE_MILLION
for accrual_type in DayCountTypes:
testCases.header("MATURITY", "COUPON", "CLEAN_PRICE", "ACCD_DAYS",
"ACCRUED", "YTM")
for _, bond in bondDataFrame.iterrows():
date_string = bond['maturity']
matDatetime = dt.datetime.strptime(date_string, '%d-%b-%y')
maturityDt = from_datetime(matDatetime)
issueDt = Date(maturityDt._d, maturityDt._m, 2000)
coupon = bond['coupon'] / 100.0
clean_price = bond['mid']
bond = Bond(issueDt, maturityDt, coupon, freq_type, accrual_type,
100)
ytm = bond.yield_to_maturity(settlement_date, clean_price)
accrued_interest = bond._accrued_interest
accd_days = bond._accrued_days
testCases.print("%18s" % maturityDt, "%8.4f" % coupon,
"%10.4f" % clean_price, "%6.0f" % accd_days,
"%10.4f" % accrued_interest, "%8.4f" % ytm)
###########################################################################
# EXAMPLE FROM http://bondtutor.com/btchp4/topic6/topic6.htm
accrualConvention = DayCountTypes.ACT_ACT_ICMA
y = 0.062267
settlement_date = Date(19, 4, 1994)
issue_date = Date(15, 7, 1990)
maturity_date = Date(15, 7, 1997)
coupon = 0.085
face = ONE_MILLION
freq_type = FrequencyTypes.SEMI_ANNUAL
bond = Bond(issue_date, maturity_date, coupon, freq_type,
accrualConvention, face)
testCases.header("FIELD", "VALUE")
full_price = bond.full_price_from_ytm(settlement_date, y)
testCases.print("Full Price = ", full_price)
clean_price = bond.clean_price_from_ytm(settlement_date, y)
testCases.print("Clean Price = ", clean_price)
accrued_interest = bond._accrued_interest
testCases.print("Accrued = ", accrued_interest)
ytm = bond.yield_to_maturity(settlement_date, clean_price)
testCases.print("Yield to Maturity = ", ytm)
bump = 1e-4
priceBumpedUp = bond.full_price_from_ytm(settlement_date, y + bump)
testCases.print("Price Bumped Up:", priceBumpedUp)
priceBumpedDn = bond.full_price_from_ytm(settlement_date, y - bump)
testCases.print("Price Bumped Dn:", priceBumpedDn)
durationByBump = -(priceBumpedUp - full_price) / bump
testCases.print("Duration by Bump = ", durationByBump)
duration = bond.dollar_duration(settlement_date, y)
testCases.print("Dollar Duration = ", duration)
testCases.print("Duration Difference:", duration - durationByBump)
modified_duration = bond.modified_duration(settlement_date, y)
testCases.print("Modified Duration = ", modified_duration)
macauley_duration = bond.macauley_duration(settlement_date, y)
testCases.print("Macauley Duration = ", macauley_duration)
conv = bond.convexity_from_ytm(settlement_date, y)
testCases.print("Convexity = ", conv)
# ASSET SWAP SPREAD
# When the libor curve is the flat bond curve then the ASW is zero by
# definition
flat_curve = DiscountCurveFlat(settlement_date, ytm,
FrequencyTypes.SEMI_ANNUAL)
testCases.header("FIELD", "VALUE")
clean_price = bond.clean_price_from_ytm(settlement_date, ytm)
asw = bond.asset_swap_spread(settlement_date, clean_price, flat_curve)
testCases.print("Discounted on Bond Curve ASW:", asw * 10000)
# When the libor curve is the Libor curve then the ASW is positive
libor_curve = build_Ibor_Curve(settlement_date)
asw = bond.asset_swap_spread(settlement_date, clean_price, libor_curve)
oas = bond.option_adjusted_spread(settlement_date, clean_price,
libor_curve)
testCases.print("Discounted on LIBOR Curve ASW:", asw * 10000)
testCases.print("Discounted on LIBOR Curve OAS:", oas * 10000)
p = 90.0
asw = bond.asset_swap_spread(settlement_date, p, libor_curve)
oas = bond.option_adjusted_spread(settlement_date, p, libor_curve)
testCases.print("Deep discount bond at 90 ASW:", asw * 10000)
testCases.print("Deep discount bond at 90 OAS:", oas * 10000)
p = 100.0
asw = bond.asset_swap_spread(settlement_date, p, libor_curve)
oas = bond.option_adjusted_spread(settlement_date, p, libor_curve)
testCases.print("Par bond at 100 ASW:", asw * 10000)
testCases.print("Par bond at 100 OAS:", oas * 10000)
p = 120.0
asw = bond.asset_swap_spread(settlement_date, p, libor_curve)
oas = bond.option_adjusted_spread(settlement_date, p, libor_curve)
testCases.print("Above par bond at 120 ASW:", asw * 10000)
testCases.print("Above par bond at 120 OAS:", oas * 10000)
##########################################################################
# https://data.bloomberglp.com/bat/sites/3/2017/07/SF-2017_Paul-Fjeldsted.pdf
# Page 10 TREASURY NOTE SCREENSHOT
##########################################################################
testCases.banner("BLOOMBERG US TREASURY EXAMPLE")
settlement_date = Date(21, 7, 2017)
issue_date = Date(15, 5, 2010)
maturity_date = Date(15, 5, 2027)
coupon = 0.02375
freq_type = FrequencyTypes.SEMI_ANNUAL
accrual_type = DayCountTypes.ACT_ACT_ICMA
face = 100.0
bond = Bond(issue_date, maturity_date, coupon, freq_type, accrual_type,
face)
testCases.header("FIELD", "VALUE")
clean_price = 99.7808417
yld = bond.current_yield(clean_price)
testCases.print("Current Yield = ", yld)
ytm = bond.yield_to_maturity(settlement_date, clean_price,
YTMCalcType.UK_DMO)
testCases.print("UK DMO Yield To Maturity = ", ytm)
ytm = bond.yield_to_maturity(settlement_date, clean_price,
YTMCalcType.US_STREET)
testCases.print("US STREET Yield To Maturity = ", ytm)
ytm = bond.yield_to_maturity(settlement_date, clean_price,
YTMCalcType.US_TREASURY)
testCases.print("US TREASURY Yield To Maturity = ", ytm)
full_price = bond.full_price_from_ytm(settlement_date, ytm)
testCases.print("Full Price = ", full_price)
clean_price = bond.clean_price_from_ytm(settlement_date, ytm)
testCases.print("Clean Price = ", clean_price)
accrued_interest = bond._accrued_interest
testCases.print("Accrued = ", accrued_interest)
accddays = bond._accrued_days
testCases.print("Accrued Days = ", accddays)
duration = bond.dollar_duration(settlement_date, ytm)
testCases.print("Dollar Duration = ", duration)
modified_duration = bond.modified_duration(settlement_date, ytm)
testCases.print("Modified Duration = ", modified_duration)
macauley_duration = bond.macauley_duration(settlement_date, ytm)
testCases.print("Macauley Duration = ", macauley_duration)
conv = bond.convexity_from_ytm(settlement_date, ytm)
testCases.print("Convexity = ", conv)
##########################################################################
# Page 11 APPLE NOTE SCREENSHOT
##########################################################################
testCases.banner("BLOOMBERG APPLE CORP BOND EXAMPLE")
settlement_date = Date(21, 7, 2017)
issue_date = Date(13, 5, 2012)
maturity_date = Date(13, 5, 2022)
coupon = 0.027
freq_type = FrequencyTypes.SEMI_ANNUAL
accrual_type = DayCountTypes.THIRTY_E_360_ISDA
face = 100.0
bond = Bond(issue_date, maturity_date, coupon, freq_type, accrual_type,
face)
testCases.header("FIELD", "VALUE")
clean_price = 101.581564
yld = bond.current_yield(clean_price)
testCases.print("Current Yield", yld)
ytm = bond.yield_to_maturity(settlement_date, clean_price,
YTMCalcType.UK_DMO)
testCases.print("UK DMO Yield To Maturity", ytm)
ytm = bond.yield_to_maturity(settlement_date, clean_price,
YTMCalcType.US_STREET)
testCases.print("US STREET Yield To Maturity", ytm)
ytm = bond.yield_to_maturity(settlement_date, clean_price,
YTMCalcType.US_TREASURY)
testCases.print("US TREASURY Yield To Maturity", ytm)
full_price = bond.full_price_from_ytm(settlement_date, ytm)
testCases.print("Full Price", full_price)
clean_price = bond.clean_price_from_ytm(settlement_date, ytm)
testCases.print("Clean Price", clean_price)
accddays = bond._accrued_days
testCases.print("Accrued Days", accddays)
accrued_interest = bond._accrued_interest
testCases.print("Accrued", accrued_interest)
duration = bond.dollar_duration(settlement_date, ytm)
testCases.print("Dollar Duration", duration)
modified_duration = bond.modified_duration(settlement_date, ytm)
testCases.print("Modified Duration", modified_duration)
macauley_duration = bond.macauley_duration(settlement_date, ytm)
testCases.print("Macauley Duration", macauley_duration)
conv = bond.convexity_from_ytm(settlement_date, ytm)
testCases.print("Convexity", conv)
import pandas as pd
path = os.path.join(os.path.dirname(__file__), './data/giltBondPrices.txt')
bondDataFrame = pd.read_csv(path, sep='\t')
bondDataFrame['mid'] = 0.5 * (bondDataFrame['bid'] + bondDataFrame['ask'])
freq_type = FrequencyTypes.SEMI_ANNUAL
accrual_type = DayCountTypes.ACT_ACT_ICMA
settlement = Date(19, 9, 2012)
bonds = []
clean_prices = []
for _, bondRow in bondDataFrame.iterrows():
date_string = bondRow['maturity']
matDatetime = dt.datetime.strptime(date_string, '%d-%b-%y')
maturityDt = from_datetime(matDatetime)
issueDt = Date(maturityDt._d, maturityDt._m, 2000)
coupon = bondRow['coupon'] / 100.0
clean_price = bondRow['mid']
bond = Bond(issueDt, maturityDt, coupon, freq_type, accrual_type)
bonds.append(bond)
clean_prices.append(clean_price)
bondCurve = BondZeroCurve(settlement, bonds, clean_prices)
def test_zero_curve():
maturityDt = Date(7, 3, 2013)
zero_rate = bondCurve.zero_rate(maturityDt)
assert round(zero_rate, 4) == 0.0022