Louis Szeto
c049a35121
* Add gamma indicator * add helper method * add unit tests * add in regression tests * Address peer review * add vega indicator * add theta and rho indicators * Address peer review, refactor
85 lines
5.1 KiB
Python
85 lines
5.1 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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from scipy.optimize import brentq
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class OptionIndicatorsRegressionAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetStartDate(2014, 6, 5)
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self.SetEndDate(2014, 6, 7)
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self.SetCash(1000000)
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equity = self.AddEquity("AAPL", Resolution.Daily).Symbol
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option = Symbol.CreateOption("AAPL", Market.USA, OptionStyle.American, OptionRight.Put, 650, datetime(2014, 6, 21))
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self.AddOptionContract(option, Resolution.Daily)
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# add the call counter side of the mirrored pair
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mirror_option = Symbol.CreateOption("AAPL", Market.USA, OptionStyle.American, OptionRight.Call, 650, datetime(2014, 6, 21))
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self.AddOptionContract(mirror_option, Resolution.Daily)
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self.delta = self.D(option, mirror_option, optionModel = OptionPricingModelType.BinomialCoxRossRubinstein, ivModel = OptionPricingModelType.BlackScholes)
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self.gamma = self.G(option, mirror_option, optionModel = OptionPricingModelType.ForwardTree, ivModel = OptionPricingModelType.BlackScholes)
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self.vega = self.V(option, mirror_option, optionModel = OptionPricingModelType.ForwardTree, ivModel = OptionPricingModelType.BlackScholes)
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self.theta = self.T(option, mirror_option, optionModel = OptionPricingModelType.ForwardTree, ivModel = OptionPricingModelType.BlackScholes)
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self.rho = self.R(option, mirror_option, optionModel = OptionPricingModelType.ForwardTree, ivModel = OptionPricingModelType.BlackScholes)
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# A custom IV indicator with custom calculation of IV
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riskFreeRateModel = InterestRateProvider()
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dividendYieldModel = DividendYieldProvider(equity)
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self.impliedVolatility = CustomImpliedVolatility(option, mirror_option, riskFreeRateModel, dividendYieldModel)
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self.RegisterIndicator(option, self.impliedVolatility, QuoteBarConsolidator(timedelta(1)))
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self.RegisterIndicator(mirror_option, self.impliedVolatility, QuoteBarConsolidator(timedelta(1)))
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self.RegisterIndicator(equity, self.impliedVolatility, TradeBarConsolidator(timedelta(1)))
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# custom IV smoothing function: assume the lower IV is more "fair"
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smoothing_func = lambda iv, mirror_iv: min(iv, mirror_iv)
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# set the smoothing function
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self.delta.ImpliedVolatility.SetSmoothingFunction(smoothing_func)
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self.gamma.ImpliedVolatility.SetSmoothingFunction(smoothing_func)
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self.vega.ImpliedVolatility.SetSmoothingFunction(smoothing_func)
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self.theta.ImpliedVolatility.SetSmoothingFunction(smoothing_func)
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self.rho.ImpliedVolatility.SetSmoothingFunction(smoothing_func)
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def OnEndOfAlgorithm(self):
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if self.impliedVolatility.Current.Value == 0 or self.delta.Current.Value == 0 or self.gamma.Current.Value == 0 \
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or self.vega.Current.Value == 0 or self.theta.Current.Value == 0 or self.rho.Current.Value == 0:
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raise Exception("Expected IV/greeks calculated")
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self.Debug(f"""Implied Volatility: {self.impliedVolatility.Current.Value},
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Delta: {self.delta.Current.Value},
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Gamma: {self.gamma.Current.Value},
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Vega: {self.vega.Current.Value},
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Theta: {self.theta.Current.Value},
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Rho: {self.rho.Current.Value}""")
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class CustomImpliedVolatility(ImpliedVolatility):
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def __init__(self, option, mirror_option, risk_free_rate_model, dividend_yield_model):
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super().__init__(option, risk_free_rate_model, dividend_yield_model, mirror_option, period=2)
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self.SetSmoothingFunction(lambda iv, mirror_iv: iv)
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def CalculateIV(self, timeTillExpiry: float) -> float:
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try:
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return brentq(self.f, 1e-7, 2.0, args=(timeTillExpiry), xtol=1e-4, maxiter=100)
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except:
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print("ImpliedVolatility.CalculateIV(): Fail to converge, returning 0.")
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return 0.0
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# we demonstate put-call parity calculation here, but note that it is not suitable for American options
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def f(self, vol: float, time_till_expiry: float) -> float:
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call_black_price = OptionGreekIndicatorsHelper.BlackTheoreticalPrice(
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vol, UnderlyingPrice.Current.Value, Strike, timeTillExpiry, RiskFreeRate.Current.Value, DividendYield.Current.Value, OptionRight.Call);
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put_black_price = OptionGreekIndicatorsHelper.BlackTheoreticalPrice(
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vol, UnderlyingPrice.Current.Value, Strike, timeTillExpiry, RiskFreeRate.Current.Value, DividendYield.Current.Value, OptionRight.Put);
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return Price.Current.Value + OppositePrice.Current.Value - call_black_price - put_black_price
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