def to_ql_option_engine(engine_name=None, process=None, model=None):
""" Returns a QuantLib.PricingEngine for Options
:param engine_name: str
The engine name
:param process: QuantLib.StochasticProcess
The QuantLib object with the option Stochastic Process.
:param model: QuantLib.CalibratedModel
:return: QuantLib.PricingEngine
"""
if engine_name.upper() == 'BINOMIAL_VANILLA':
return ql.BinomialVanillaEngine(process, 'LR', 801)
elif engine_name.upper() == 'ANALYTIC_HESTON':
if model is None:
model = ql.HestonModel(process)
elif model is not None and process is not None:
model = model(process)
return ql.AnalyticHestonEngine(model)
elif engine_name.upper() == 'ANALYTIC_EUROPEAN':
return ql.AnalyticEuropeanEngine(process)
elif engine_name.upper() == 'ANALYTIC_EUROPEAN_DIVIDEND':
return ql.AnalyticDividendEuropeanEngine(process)
elif engine_name.upper() == "FINITE_DIFFERENCES":
return ql.FdBlackScholesVanillaEngine(process)
elif engine_name.upper() == 'HESTON_FINITE_DIFFERENCES':
if model is None:
model = ql.HestonModel(process)
elif model is not None and process is not None:
model = model(process)
return ql.FdHestonVanillaEngine(model)
elif engine_name.upper() == "BARONE_ADESI_WHALEY":
return ql.BaroneAdesiWhaleyEngine(process)
elif engine_name.upper() == "BJERKSUND_STENSLAND":
return ql.BjerksundStenslandEngine(process)
elif engine_name.upper() == "ANALYTIC_GJR_GARCH":
if model is None:
model = ql.GJRGARCHModel(process)
elif model is not None and process is not None:
model = model(process)
return ql.AnalyticGJRGARCHEngine(model)
elif engine_name.upper() == 'MC_GJR_GARCH':
return ql.MCEuropeanGJRGARCHEngine(process=process,
traits='pseudorandom',
timeStepsPerYear=20,
requiredTolerance=0.02)
else:
return None
eu_exercise = ql.EuropeanExercise(maturity_date)
european_option = ql.VanillaOption(payoff, eu_exercise)
spot_handle = ql.QuoteHandle(ql.SimpleQuote(spot_price))
flat_ts = ql.YieldTermStructureHandle(
ql.FlatForward(calculation_date, risk_free_rate, day_count))
dividend_yield = ql.YieldTermStructureHandle(
ql.FlatForward(calculation_date, dividend_rate, day_count))
flat_vol_ts = ql.BlackVolTermStructureHandle(
ql.BlackConstantVol(calculation_date, calendar, volatility, day_count))
bsm_process = ql.BlackScholesMertonProcess(spot_handle, dividend_yield,
spotCurveHandle, flat_vol_ts)
steps = 1000
binomial_engine = ql.AnalyticDividendEuropeanEngine(bsm_process)
european_option.setPricingEngine(binomial_engine)
#print (european_option.NPV()*ratio_up)
#AnalyticDividendEuropeanEngine
#BinomialVanillaEngine
'''
Price the short put option
'''
maturity_date = maturityDate
spot_price = 14.455
strike_price_2 = 12.4467
volatility_2 = 0.37 # the historical vols or implied vols
dividend_rate = .01
#european_option = ql.DividendVanillaOption(payoff, eu_exercise, div_dates_ql, div_amounts)
spot_handle = ql.QuoteHandle(ql.SimpleQuote(spot_price))
dividend_yield = ql.YieldTermStructureHandle(
ql.FlatForward(calculation_date, dividend_rate, day_count))
flat_vol_ts = ql.BlackVolTermStructureHandle(
ql.BlackConstantVol(calculation_date, calendar, volatility, day_count))
bsm_process = ql.BlackScholesMertonProcess(spot_handle, dividend_yield,
spotCurveHandle, flat_vol_ts)
#bs_process = ql.BlackScholesProcess(spot_handle, spotCurveHandle, flat_vol_ts)
steps = 1000
engine = ql.AnalyticDividendEuropeanEngine(bsm_process)
european_option.setPricingEngine(engine)
long_call = european_option.NPV()
'''
Price the short put option
'''
maturity_date = maturityDate
spot_price = spotPrice
strike_price_2 = min_conv_px
volatility_2 = vol_lower # the historical vols or implied vols
dividend_rate = div_yield
option_type_2 = ql.Option.Put
day_count = ql.Actual360()
def getPricingEngine(self):
engine = ql.AnalyticDividendEuropeanEngine(self.process)
return engine
