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dispersion-trading.py
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dispersion-trading.py
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# https://quantpedia.com/strategies/dispersion-trading/
#
# The investment universe consists of stocks from the S&P 100 index.
# Trading vehicles are options on stocks from this index and also options on the index itself.
# The investor uses analyst forecasts of earnings per share from the Institutional Brokers Estimate System (I/B/E/S) database and
# computes for each firm the mean absolute difference scaled by an indicator of earnings uncertainty (see page 24 in the source academic paper for detailed methodology).
# Each month, investor sorts stocks into quintiles based on the size of belief disagreement.
# He buys puts of stocks with the highest belief disagreement and sells the index puts with Black-Scholes deltas ranging from -0.8 to -0.2.
#
# QC Implementation:
# - Due to lack of data, strategy only buys puts of 100 liquid US stocks and sells the SPX index puts.
#region imports
from AlgorithmImports import *
from numpy import floor
#endregion
class DispersionTrading(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2010, 1, 1)
self.SetCash(1000000)
self.min_expiry = 20
self.max_expiry = 60
self.index_symbol = self.AddIndex('SPX').Symbol
self.percentage_traded = 1.0
self.spx_contract = None
self.selected_symbols = []
self.subscribed_contracts = {}
self.coarse_count = 100
self.UniverseSettings.Resolution = Resolution.Minute
self.AddUniverse(self.CoarseSelectionFunction)
self.SetSecurityInitializer(lambda x: x.SetDataNormalizationMode(DataNormalizationMode.Raw))
self.UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw
def OnSecuritiesChanged(self, changes):
for security in changes.AddedSecurities:
security.SetFeeModel(CustomFeeModel())
security.SetLeverage(5)
def CoarseSelectionFunction(self, coarse):
# rebalance on SPX contract expiration (should be on monthly basis)
if len(self.selected_symbols) != 0:
return Universe.Unchanged
# select top n stocks by dollar volume
selected = sorted([x for x in coarse if x.HasFundamentalData and x.Market == 'usa' and x.Price > 5],
key=lambda x: x.DollarVolume, reverse=True)[:self.coarse_count]
self.selected_symbols = [x.Symbol for x in selected]
return self.selected_symbols
def OnData(self, data):
# liquidate portfolio, when SPX contract is about to expire in 2 days
if self.index_symbol in self.subscribed_contracts and self.subscribed_contracts[self.index_symbol].ID.Date.date() - timedelta(2) <= self.Time.date():
self.subscribed_contracts.clear() # perform new subscribtion
self.selected_symbols.clear() # perform new selection
self.Liquidate()
if len(self.subscribed_contracts) == 0:
if self.Portfolio.Invested:
self.Liquidate()
# NOTE order is important, index should come first
for symbol in [self.index_symbol] + self.selected_symbols:
# subscribe to contract
contracts = self.OptionChainProvider.GetOptionContractList(symbol, self.Time)
# get current price for stock
underlying_price = self.Securities[symbol].Price
# get strikes from stock contracts
strikes = [i.ID.StrikePrice for i in contracts]
# check if there is at least one strike
if len(strikes) <= 0:
continue
# at the money
atm_strike = min(strikes, key=lambda x: abs(x-underlying_price))
# filtred contracts based on option rights and strikes
atm_puts = [i for i in contracts if i.ID.OptionRight == OptionRight.Put and
i.ID.StrikePrice == atm_strike and
self.min_expiry <= (i.ID.Date - self.Time).days <= self.max_expiry]
# index contract is found
if symbol == self.index_symbol and len(atm_puts) == 0:
# cancel whole selection since index contract was not found
return
# make sure there are enough contracts
if len(atm_puts) > 0:
# sort by expiry
atm_put = sorted(atm_puts, key = lambda item: item.ID.Date, reverse=True)[0]
# add contract
option = self.AddOptionContract(atm_put, Resolution.Minute)
option.PriceModel = OptionPriceModels.CrankNicolsonFD()
option.SetDataNormalizationMode(DataNormalizationMode.Raw)
# store subscribed atm put contract
self.subscribed_contracts[symbol] = atm_put
# perform trade, when spx and stocks contracts are selected
if not self.Portfolio.Invested and len(self.subscribed_contracts) != 0 and self.index_symbol in self.subscribed_contracts:
index_option_contract = self.subscribed_contracts[self.index_symbol]
# make sure subscribed SPX contract has data
if self.Securities.ContainsKey(index_option_contract):
if self.Securities[index_option_contract].Price != 0 and self.Securities[index_option_contract].IsTradable:
# sell SPX ATM put contract
self.Securities[index_option_contract].MarginModel = BuyingPowerModel(2)
price = self.Securities[self.index_symbol].Price
if price != 0:
q = floor((self.Portfolio.TotalPortfolioValue * self.percentage_traded) / (price*100))
self.Sell(index_option_contract, q)
# buy stock's ATM put contracts
long_count = len(self.subscribed_contracts) - 1 # minus index symbol
for stock_symbol, stock_option_contract in self.subscribed_contracts.items():
if stock_symbol == self.index_symbol:
continue
if self.Securities[stock_option_contract].Price != 0 and self.Securities[stock_option_contract].IsTradable:
# buy contract
self.Securities[stock_option_contract].MarginModel = BuyingPowerModel(2)
if self.Securities.ContainsKey(stock_option_contract):
price = self.Securities[stock_symbol].Price
if price != 0:
q = floor(((self.Portfolio.TotalPortfolioValue / long_count) * self.percentage_traded) / (price*100))
self.Buy(stock_option_contract, q)
# Custom fee model
class CustomFeeModel(FeeModel):
def GetOrderFee(self, parameters):
fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
return OrderFee(CashAmount(fee, "USD"))