# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from AlgorithmImports import *

### <summary>
### Example demonstrating how to define an option price model.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="options" />
### <meta name="tag" content="filter selection" />
### <meta name="tag" content="option price model" />
class BasicTemplateOptionsPriceModel(QCAlgorithm):
    '''Example demonstrating how to define an option price model.'''

    def initialize(self):
        self.set_start_date(2020, 1, 1)
        self.set_end_date(2020, 1, 5)
        self.set_cash(100000)

        # Add the option
        option = self.add_option("AAPL")
        self.option_symbol = option.symbol

        # Add the initial contract filter
        option.set_filter(-3, +3, 0, 31)

        # Define the Option Price Model
        option.price_model = OptionPriceModels.QuantLib.crank_nicolson_fd()
        #option.price_model = OptionPriceModels.QuantLib.black_scholes()
        #option.price_model = OptionPriceModels.QuantLib.additive_equiprobabilities()
        #option.price_model = OptionPriceModels.QuantLib.barone_adesi_whaley()
        #option.price_model = OptionPriceModels.QuantLib.binomial_cox_ross_rubinstein()
        #option.price_model = OptionPriceModels.QuantLib.binomial_jarrow_rudd()
        #option.price_model = OptionPriceModels.QuantLib.binomial_joshi()
        #option.price_model = OptionPriceModels.QuantLib.binomial_leisen_reimer()
        #option.price_model = OptionPriceModels.QuantLib.binomial_tian()
        #option.price_model = OptionPriceModels.QuantLib.binomial_trigeorgis()
        #option.price_model = OptionPriceModels.QuantLib.bjerksund_stensland()
        #option.price_model = OptionPriceModels.QuantLib.integral()

        # Set warm up with 30 trading days to warm up the underlying volatility model
        self.set_warm_up(30, Resolution.DAILY)


    def on_data(self,slice):
        '''OnData will test whether the option contracts has a non-zero Greeks.delta'''

        if self.is_warming_up or not slice.option_chains.contains_key(self.option_symbol):
            return

        chain = slice.option_chains[self.option_symbol]
        if not any([x for x in chain if x.greeks.delta != 0]):
            self.log(f'No contract with Delta != 0')