Overall Statistics |
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Probabilistic Sharpe Ratio 0% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio 0 Tracking Error 0 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 |
from System import * from QuantConnect import * from QuantConnect.Orders import * from QuantConnect.Algorithm import * from QuantConnect.Algorithm.Framework import * from QuantConnect.Algorithm.Framework.Alphas import * from QuantConnect.Algorithm.Framework.Portfolio import * from QuantConnect.Algorithm.Framework.Selection import * from Alphas.ConstantAlphaModel import ConstantAlphaModel from Selection.OptionUniverseSelectionModel import OptionUniverseSelectionModel from Execution.ImmediateExecutionModel import ImmediateExecutionModel from Risk.NullRiskManagementModel import NullRiskManagementModel from datetime import date, timedelta class BasicTemplateOptionsFrameworkAlgorithm(QCAlgorithm): def Initialize(self): self.UniverseSettings.Resolution = Resolution.Minute self.SetStartDate(2014, 6, 5) self.SetEndDate(2014, 6, 6) self.SetCash(100000) # set framework models self.SetUniverseSelection(MyOptionUniverseSelectionModel(self.SelectOptionChainSymbols)) self.SetAlpha(ConstantOptionContractAlphaModel(InsightType.Price, InsightDirection.Up, timedelta(hours = 0.5))) self.SetPortfolioConstruction(SingleSharePortfolioConstructionModel()) self.SetExecution(ImmediateExecutionModel()) self.SetRiskManagement(NullRiskManagementModel()) def SelectOptionChainSymbols(self, utcTime): newYorkTime = Extensions.ConvertFromUtc(utcTime, TimeZones.NewYork) ticker = "TWX" if newYorkTime.date() < date(2014, 6, 6) else "AAPL" return [ Symbol.Create(ticker, SecurityType.Option, Market.USA, f"?{ticker}") ] def OnWarmupFinished(self): self.Log(f"OnWarmupFinished at {self.Time}") class MyOptionUniverseSelectionModel(OptionUniverseSelectionModel): def __init__(self, select_option_chain_symbols): super().__init__(timedelta(1), select_option_chain_symbols) def Filter(self, filter): '''Defines the option chain universe filter''' return (filter.Strikes(-1, -1).Expiration(90-15, 90-15)) class EarliestExpiringWeeklyAtTheMoneyPutOptionUniverseSelectionModel(OptionUniverseSelectionModel): '''Creates option chain universes that select only the earliest expiry ATM weekly put contract and runs a user defined optionChainSymbolSelector every day to enable choosing different option chains''' def __init__(self, select_option_chain_symbols): super().__init__(timedelta(1), select_option_chain_symbols) def Filter(self, f): '''Defines the option chain universe filter''' return (f.Strikes(+1, +1) # Expiration method accepts timedelta objects or integer for days. # The following statements yield the same filtering criteria .Expiration(0, 7) # .Expiration(timedelta(0), timedelta(7)) .WeeklysOnly() .PutsOnly() .OnlyApplyFilterAtMarketOpen()) class ConstantOptionContractAlphaModel(ConstantAlphaModel): '''Implementation of a constant alpha model that only emits insights for option symbols''' def __init__(self, type, direction, period): super().__init__(type, direction, period) def ShouldEmitInsight(self, utcTime, symbol): # only emit alpha for option symbols and not underlying equity symbols if symbol.SecurityType != SecurityType.Option: return False return super().ShouldEmitInsight(utcTime, symbol) class SingleSharePortfolioConstructionModel(PortfolioConstructionModel): '''Portfolio construction model that sets target quantities to 1 for up insights and -1 for down insights''' def CreateTargets(self, algorithm, insights): targets = [] for insight in insights: targets.append(PortfolioTarget(insight.Symbol, insight.Direction)) return targets