added options strategy algorithm
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@@ -1,10 +1,48 @@
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using System;
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namespace QuantConnect.Algorithm.Python
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{
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public class BasicTemplateOptionStrategyAlgorithm
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{
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public BasicTemplateOptionStrategyAlgorithm()
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{
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}
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}
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}
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from QuantConnect.Securities.Option import *
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from datetime import datetime, timedelta
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import numpy as np
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class BasicTemplateOptionStrategyAlgorithm(QCAlgorithm):
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''' This example demonstrates how to add option strategies for a given underlying equity security.
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It also shows how you can prefilter contracts easily based on strikes and expirations.
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It also shows how you can inspect the option chain to pick a specific option contract to trade. '''
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def Initialize(self):
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# Set the cash we'd like to use for our backtest
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self.SetCash(1000000)
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# Start and end dates for the backtest.
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self.SetStartDate(2015,12,24)
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self.SetEndDate(2015,12,24)
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self.UnderlyingTicker = "GOOG"
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# Add assets you'd like to see
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equity = self.AddEquity(self.UnderlyingTicker)
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option = self.AddOption(self.UnderlyingTicker)
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self.OptionSymbol = option.Symbol
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equity.SetDataNormalizationMode(DataNormalizationMode.Raw)
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# set our strike/expiry filter for this option chain
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option.SetFilter(-2, +2, timedelta(0), timedelta(180))
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# use the underlying equity as the benchmark
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self.SetBenchmark(equity.Symbol)
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def OnData(self,slice):
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if not self.Portfolio.Invested:
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for kvp in slice.OptionChains:
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chain = kvp.Value
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contracts = sorted(sorted(chain, key = lambda x: abs(chain.Underlying.Price - x.Strike)),
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key = lambda x: x.Expiry, reverse=False)
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if len(contracts) == 0: continue
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atmStraddle = contracts[0]
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if atmStraddle != None:
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self.Sell(OptionStrategies.Straddle(self.OptionSymbol, atmStraddle.Strike, atmStraddle.Expiry), 2)
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else:
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self.Liquidate()
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def OnOrderEvent(self, orderEvent):
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''' Order fill event handler. On an order fill update the resulting information is passed to this method.
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param "orderEvent"Order event details containing details of the evemts '''
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self.Log(str(orderEvent))
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