| 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())