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%matplotlib inline
import numpy as np
import pandas as pd
pd.set_option('precision', 2)
from QuantLib import *

Parameter



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maturity_date = Date(31, 1, 2018)
start_date = Date(1, 1, 2018)

strangle_width = 400.
lower_protect_area = 800.
upper_protect_area = 600.

spot_price = 14400.
lower_strike = 14000.
lower_bound = lower_strike - lower_protect_area
upper_strike = lower_strike + strangle_width
upper_bound = upper_strike + upper_protect_area

volatility = 0.30
risk_free_rate = 0.
dividend_rate = 0.
day_count = Actual365Fixed()
calendar = China(China.SSE)

Market Data



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calculation_date = start_date
Settings.instance().evaluationDate = calculation_date

spot_handle = RelinkableQuoteHandle(SimpleQuote(spot_price))
vol_handle =  RelinkableQuoteHandle(SimpleQuote(volatility))

flat_ts = YieldTermStructureHandle(FlatForward(calculation_date, risk_free_rate, day_count))
dividend_yield = YieldTermStructureHandle(FlatForward(calculation_date, dividend_rate, day_count))
flat_vol_ts = BlackVolTermStructureHandle(BlackConstantVol(calculation_date, calendar, vol_handle, day_count))

bsm_process = BlackScholesMertonProcess(spot_handle, dividend_yield, flat_ts, flat_vol_ts)



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put_payoff1 = PlainVanillaPayoff(Option.Put, lower_strike)
put_payoff2 = PlainVanillaPayoff(Option.Put, lower_bound)
call_payoff1 = PlainVanillaPayoff(Option.Call, upper_strike)
call_payoff2 = PlainVanillaPayoff(Option.Call, upper_bound)



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exercise = EuropeanExercise(maturity_date)
put_option1 = VanillaOption(put_payoff1, exercise)
put_option2 = VanillaOption(put_payoff2, exercise)
call_option1 = VanillaOption(call_payoff1, exercise)
call_option2 = VanillaOption(call_payoff2, exercise)



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%%time
engine = AnalyticEuropeanEngine(bsm_process)
put_option1.setPricingEngine(engine)
put_option2.setPricingEngine(engine)
call_option1.setPricingEngine(engine)
call_option2.setPricingEngine(engine)

bsm_price = put_option1.NPV() - put_option2.NPV() + call_option1.NPV() - call_option2.NPV()
print("BSM european theoreticl price is {0:.4f}".format(bsm_price))

Scenario Analysis



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%%time
spot_scenarios = [13500, 14000, 14500, 15000]
vol_scenarios = [0.20, 0.30, 0.40, 0.5]

price_table = np.zeros((len(spot_scenarios), len(vol_scenarios)))

for i, spot in enumerate(spot_scenarios):
    for j, vol in enumerate(vol_scenarios):
        spot_handle.linkTo(SimpleQuote(spot))
        vol_handle.linkTo(SimpleQuote(vol))
        
        bsm_price = put_option1.NPV() - put_option2.NPV() + call_option1.NPV() - call_option2.NPV()
        price_table[i, j] = bsm_price



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df = pd.DataFrame(price_table, index=spot_scenarios, columns=['vol - {0:=}%'.format(v*100) for v in vol_scenarios])
df.index.name = 'spot'



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print("向下保护区间：{0} ~ {1}".format(lower_bound, lower_strike))
print("向上保护区间：{0} ~ {1}".format(upper_strike, upper_bound))
df



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