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 0.309 Tracking Error 0.197 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
# region imports from AlgorithmImports import * import datetime as dt import ast import json from Selection.FundamentalUniverseSelectionModel import FundamentalUniverseSelectionModel from io import StringIO import pandas as pd # endregion class AdaptableVioletJaguar(QCAlgorithm): def Initialize(self): self.SetStartDate(2022, 1, 1) # Set Start Date self.SetCash(50000) # Set Strategy Cash self.UniverseSettings.Resolution = Resolution.Minute self.tickers = ["AAPL"] self.AddUniverse(self.CoarseSelection, self.FineSelection) self.symbolDataBySymbol = {} self.fineFundamentals = {} self.SAVE_EARNINGS = False self.loaded_earnings = {} self.slice = None if not self.SAVE_EARNINGS: self.SetEndDate(2023, 2, 1) earnings = json.loads(self.ObjectStore.Read("Earnings_dates")) temp_earnings = dict(earnings) for ticker, str_dates in earnings.items(): temp_earnings[ticker] = [dt.datetime.strptime(x, '%m/%d/%Y').date() for x in ast.literal_eval(str_dates)] self.loaded_earnings = dict(temp_earnings) self.Debug(temp_earnings) del temp_earnings del earnings elif self.SAVE_EARNINGS and self.ObjectStore.ContainsKey("Earnings_dates"): self.SetEndDate(2023, 2, 10) self.ObjectStore.Delete("Earnings_dates") self.spy = self.AddEquity("SPY", Resolution.Daily) self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.AfterMarketOpen("SPY", -10), self.CheckEarningsRules) self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.BeforeMarketClose("SPY", 60), self.UpdateEarningsObject) self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.BeforeMarketClose("SPY", 30), self.TradeOptions) def UpdateEarningsObject(self): if self.SAVE_EARNINGS: for symbol, symbolData in self.symbolDataBySymbol.items(): symbolData.update_earnings(self.fineFundamentals[symbol].EarningReports.FileDate) # Long Entry Criteria # at least 30 days since the last earnings report # over 30 days until the next earnings report # # Short Entry Criteria # less than 10 days until the next earnings report # # Short Exit Criteria # over 30 days since last earnings report # def CheckEarningsRules(self): if self.SAVE_EARNINGS: return cur_date = self.Time.date() for symbol, symbolData in self.symbolDataBySymbol.items(): symbol_earnings = symbolData.earnings_dates symbol_earnings_series = pd.Series(symbol_earnings) insertion_index = symbol_earnings_series.searchsorted(cur_date) ## Result is the index at which it will exit in the next list prev_earnings_date = symbol_earnings[insertion_index-1] next_earnings_date = symbol_earnings[insertion_index] ## WHEN RUNNING ALGORITHM, MAKE SURE self.EndDate IS LESS THAN THE LAST EARNINGS VALUE delta_prev = cur_date - prev_earnings_date delta_next = next_earnings_date - cur_date if delta_prev.days >= 30 and delta_next.days > 30: symbolData.long_entry_earnings = True else: symbolData.long_entry_earnings = False if delta_next.days < 10: symbolData.short_entry_earnings = True else: symbolData.short_entry_earnings = False if delta_prev.days >= 30: symbolData.short_exit_earnings = True else: symbolData.short_exit_earnings = False self.Debug(f"{insertion_index} {self.Time.date()} {symbol.Value} : long etr - {symbolData.long_entry_earnings}, short etr - {symbolData.short_entry_earnings}, short ext - {symbolData.short_exit_earnings}") def ContractFilter(self, symbol, min_strike, max_strike, min_expiry_days, max_expiry_days): contracts = self.OptionChainProvider.GetOptionContractList(symbol, self.Time.date()) if len(contracts) == 0 : return [] contract_list = [i for i in contracts if min_expiry_days < (i.ID.Date.date() - self.Time.date()).days < max_expiry_days] if len(contract_list) == 0: return [] min_strike_price = sorted(contract_list, key = lambda x: abs(x.ID.StrikePrice - min_strike))[0].ID.StrikePrice max_strike_price = sorted(contract_list, key = lambda x: abs(x.ID.StrikePrice - max_strike))[0].ID.StrikePrice self.Debug(f"Min: {min_strike}") self.Debug(f"Max: {max_strike}") strike_list = sorted(set([i.ID.StrikePrice for i in contract_list])) min_strike_rank = strike_list.index(min_strike_price) max_strike_rank = strike_list.index(max_strike_price) try: strikes = strike_list[min_strike_rank:max_strike_rank] except: strikes = strike_list filtered_contracts = [i for i in contract_list if i.ID.StrikePrice in strikes] return filtered_contracts def AddContract(self, slice, symbol, symbolData, position): security_price = self.Securities[symbol].Price lower_atr_strike = (symbolData.atr.Current.Value * 8) + security_price upper_atr_strike = (symbolData.atr.Current.Value * 12) + security_price cur_atr_strike = (symbolData.atr.Current.Value * 10) + security_price cur_atr = symbolData.atr.Current.Value if position == 'long': self.Debug('long') self.Debug(f"p: {security_price}, atr_l: {lower_atr_strike}, atr_u: {upper_atr_strike}, atr_c: {cur_atr_strike}, atr: {cur_atr}") filtered_contracts = self.ContractFilter(symbol, lower_atr_strike, upper_atr_strike, 300, 400) elif position == 'short': self.Debug('short') self.Debug(f"atr_l: {lower_atr_strike}, atr_u: {upper_atr_strike}, atr_c: {cur_atr_strike}, atr: {cur_atr}") filtered_contracts = self.ContractFilter(symbol, lower_atr_strike, upper_atr_strike, 20, 30) if len(filtered_contracts) == 0: return [] else: calls = [x for x in filtered_contracts if x.ID.OptionRight == OptionRight.Call] test = [x.ID.StrikePrice for x in calls] test2 = [x.ID.Date.date() for x in calls] self.Debug(f"Strikes: {test}") self.Debug(f"Expirys: {test2}") # contracts = sorted(sorted(calls, key = lambda x: abs(self.Securities[self.underlying].Price- x.ID.StrikePrice)), # key = lambda x: x.ID.Date, reverse=True) # if len(contracts) > 0: # self.AddOptionContract(contracts[0], Resolution.Minute) # return contracts[0] # else: # return str() def TradeOptions(self): if self.SAVE_EARNINGS: return for symbol, symbolData in self.symbolDataBySymbol.items(): if symbolData.long_call == None: symbolData.long_call = self.AddContract(self.slice, symbol, symbolData, 'long') if symbolData.short_call == None: symbolData.short_call = self.AddContract(self.slice, symbol, symbolData, 'short') def OnData(self, data: Slice): self.slice = Slice def OnSecuritiesChanged(self, changes): for security in changes.AddedSecurities: if security.Symbol.Value == "SPY" or security.Symbol.SecurityType != SecurityType.Equity: continue atr = self.ATR(security.Symbol, 20, MovingAverageType.Simple, Resolution.Daily) history = self.History(security.Symbol, 20, Resolution.Daily) for bar in history.itertuples(): tradebar = TradeBar(bar.Index[1], security.Symbol, bar.open, bar.high, bar.low, bar.close, bar.volume) atr.Update(tradebar) symbolData = SymbolData(self, security, atr) if not self.SAVE_EARNINGS: symbolData.earnings_dates = self.loaded_earnings[security.Symbol.Value] self.symbolDataBySymbol[security.Symbol] = symbolData for security in changes.RemovedSecurities: if security.Symbol.SecurityType == SecurityType.Equity: self.symbolDataBySymbol.pop(security.Symbol) else: # self.RemoveSecurity(x.Symbol) for symbol in self.Securities.Keys: if symbol.SecurityType == SecurityType.Option and symbol.Underlying == security.Symbol: self.RemoveSecurity(symbol) def CoarseSelection(self, coarse): filteredCoarse = [x.Symbol for x in coarse if x.Symbol.Value in self.tickers and x.HasFundamentalData] return filteredCoarse def FineSelection(self, fine): for x in fine: self.fineFundamentals[x.Symbol] = x return [x.Symbol for x in fine] def OnEndOfAlgorithm(self): if self.SAVE_EARNINGS: earnings_dict = {} for symbol, symbolData in self.symbolDataBySymbol.items(): self.Debug(f"{symbol.Value} : {symbolData.earnings_dates}") string_earnings = [t.strftime('%m/%d/%Y') for t in symbolData.earnings_dates] earnings_dict[str(symbol.Value)] = str(string_earnings) dump = json.dumps(earnings_dict) self.ObjectStore.Save("Earnings_dates", dump) self.Debug(earnings_dict) else: for symbol, symbolData in self.symbolDataBySymbol.items(): self.Debug(symbolData.earnings_dates) class SymbolData: def __init__(self, algo, security, atr): self.algo = algo self.security = security self.symbol = security.Symbol self.earnings_dates = [] self.long_entry_earnings = False self.short_entry_earnings = False self.short_exit_earnings = False self.long_call = None self.short_call = None self.atr = atr def update_earnings(self, date): if date.date() not in self.earnings_dates: self.earnings_dates.append(date.date())