book
Checkout our new book! Hands on AI Trading with Python, QuantConnect, and AWS Learn More arrow

Universes

Equity Options

Introduction

An Equity Options universe lets you select a basket of contracts for a single Option. LEAN models Option subscriptions as a universe of Option contracts.

Create Universes

To add a universe of Equity Option contracts, in the initialize method, call the add_option method. This method returns an Option object, which contains the canonical symbol. You can't trade with the canonical Option symbol, but save a reference to it so you can easily access the Option contracts in the OptionChain that LEAN passes to the on_data method.

Select Language: 
class BasicOptionAlgorithm(QCAlgorithm):
    
    def initialize(self):
        self.universe_settings.asynchronous = True
        option = self.add_option("SPY")
        option.set_filter(self._filter)
        self._symbol = option.symbol

    def _filter(self, universe):
        return universe.include_weeklys().expiration(0, 7).delta(0.35, 0.75)

    def on_data(self, data):
        chain = data.option_chains.get(self._symbol)
        if chain:
            contract = sorted(chain, key=lambda x: (x.expiry, x.greeks.delta))[0]

The following table describes the add_option method arguments:

ArgumentData TypeDescriptionDefault Value
tickerstrThe underlying Equity ticker. To view the supported underlying Equity tickers, see Supported Assets.
resolutionResolution/NoneTypeThe resolution of the market data. To view the supported resolutions, see Resolutions. The Equity resolution must be less than or equal to the Equity Option resolution. For example, if you set the Equity resolution to minute, then you must set the Equity Option resolution to minute, hour, or daily.None
marketstrThe underlying Equity market.None
fill_forwardboolIf true, the current slice contains the last available data even if there is no data at the current time.True
leveragefloatThe leverage for this Equity.Security.NULL_LEVERAGE
extended_market_hoursboolA flag that signals if LEAN should send data during pre- and post-market trading hours.False

If you add an Equity Option universe but don't have a subscription to the underlying Equity, LEAN automatically subscribes to the underlying Equity with the following settings:

SettingValue
Fill forwardSame as the Option universe
Leverage0
Extended Market HoursSame as the Option universe
Data NormalizationDataNormalizationMode.RAW

If you already have a subscription to the underlying Equity but it's not RAW data normalization, LEAN automatically changes it to RAW.

Filter by Investment Strategy

Options trading strategies consist of simultaneously buying or selling one or more Option contracts of the same underlying Equity, but with different features.

Select Language: 
# Example 1: Select a Straddle
option.set_filter(lambda option_filter_universe: option_filter_universe.straddle(30, 5, 10))

# Example 2: Select the contracts (including weeklys) that expire in the next 30 days that form an Iron Condor
option.set_filter(lambda option_filter_universe: option_filter_universe.include_weeklys().strikes(-20, 20).expiration(0, 30).iron_condor(30, 5, 10))

# Example 3: Select the 0DTE contracts that form an Strangle
option.set_filter(lambda option_filter_universe: option_filter_universe.include_weeklys().expiration(0, 0).strangle(30, 5, -10))

The following table describes the filter methods of the OptionFilterUniverse class that select contracts for Option strategies:

naked_call(min_days_till_expiry: int, strike_from_atm: float)

Selects a call contract to form Naked Call, Covered Call, or Protective Call Option strategies.

naked_put(min_days_till_expiry: int, strike_from_atm: float)

Selects a put contract to form Naked Put, Covered Put, or Protective Put Option strategies.

call_spread(min_days_till_expiry: int, higher_strike_from_atm: float, lower_strike_from_atm: float)

Selects two call contracts to form Bull Call Spread or Bear Call Spread Option strategies.

put_spread(min_days_till_expiry: int, higher_strike_from_atm: float, lower_strike_from_atm: float)

Selects two put contracts to form Bull Put Spread or Bear Put Spread Option strategies.

call_calendar_spread(strike_from_atm: int, min_near_days_till_expiry: int, min_far_days_till_expiry: int)

Selects two call contracts to form Long Call Calendar Spread or Short Call Calendar Spread Option strategies.

put_calendar_spread(strike_from_atm: int, min_near_days_till_expiry: int, min_far_days_till_expiry: int)

Selects two put contracts to form Long Put Calendar Spread or Short Put Calendar Spread Option strategies.

strangle(min_days_till_expiry: int, higher_strike_from_atm: float, lower_strike_from_atm: float)

Selects two contracts to form Long Strangle or Short Strangle Option strategies.

straddle(min_days_till_expiry: int)

Selects two contracts to form Long Straddle or Short Straddle Option strategies.

protective_collar(min_days_till_expiry: int, higher_strike_from_atm: float, lower_strike_from_atm: float)

Selects two contracts to form Protective Collar Option strategies.

conversion(min_days_till_expiry: int, strike_from_atm: float)

Selects two contracts to form Conversion or Reverse Conversion Option strategies.

call_butterfly(min_days_till_expiry: int, strike_spread: float)

Selects three contracts to form Long Call Butterfly or Short Call Butterfly Option strategies.

put_butterfly(min_days_till_expiry: int, strike_spread: float)

Selects three contracts to form Long Put Butterfly or Short Put Butterfly Option strategies.

iron_butterfly(min_days_till_expiry: int, strike_spread: float)

Selects four contracts to form Long Iron Butterfly or Short Iron Butterfly Option strategies.

iron_condor(min_days_till_expiry: int, near_strike_spread: float, far_strike_spread: float)

Selects four contracts to form Long Iron Condor or Short Iron Condor Option strategies.

box_spread(min_days_till_expiry: int, strike_spread: float)

Selects four contracts to form Box Spread or Short Box Spread Option strategies.

jelly_roll(strike_from_atm: float, min_near_days_till_expiry: int, min_far_days_till_expiry: int)

Selects four contracts to form Jelly Roll or Short Jelly Roll Option strategies.

call_ladder(min_days_till_expiry: int, higher_strike_from_atm: float, middle_strike_from_atm: float, lower_strike_from_atm: float)

Selects four contracts to form Bear Call Ladder or Bull Call Ladder Option strategies.

put_ladder(min_days_till_expiry: int, higher_strike_from_atm: float, middle_strike_from_atm: float, lower_strike_from_atm: float)

Selects four contracts to form Bear Put Ladder or Bull Put Ladder Option strategies.

The preceding methods return an OptionFilterUniverse, so you can chain the methods together.

Filter by Implied Volatility and Greeks

Option price models compute the theoretical price of Option contracts, their implied volatility, and their Greek values. Theoretical prices can help you detect undervalued and overvalued contracts, implied volatility can provide you insight into the upcoming volatility of the underlying security, and Greek values can help you hedge your portfolio.

Select Language: 
# Example 1: Select the contracts with delta between 0.25 and 0.75
option.set_filter(lambda option_filter_universe: option_filter_universe.delta(0.25, 0.75))

# Example 2: Select the contracts (including weeklys) that expire in the next 90 days with implied volatility below 20% 
option.set_filter(lambda option_filter_universe: option_filter_universe.include_weeklys().iv(0, 20).expiration(0, 90))

# Example 3: Select the contracts (including weeklys) that expire in the next 30 days with implied volatility below 20% that forms an Iron Condor
option.set_filter(lambda option_filter_universe: option_filter_universe.include_weeklys().iv(0, 20).expiration(0, 30).iron_condor(30, 5, 10))

The following table describes the filter methods of the OptionFilterUniverse class that select contract for a range of implied volatility, Greek values, and open interest:

iv(min: float, max: float)
implied_volatility(min: float, max: float)

Selects a contract with implied volatility within the range you set.

d(min: float, max: float)
delta(min: float, max: float)

Selects a contract with delta within the range you set.

g(min: float, max: float)
gamma(min: float, max: float)

Selects a contract with gamma within the range you set.

r(min: float, max: float)
rho(min: float, max: float)

Selects a contract with rho within the range you set.

v(min: float, max: float)
vega(min: float, max: float)

Selects a contract with vega within the range you set.

t(min: float, max: float)
theta(min: float, max: float)

Selects a contract with theta within the range you set.

oi(min: int, max: int)
open_interest(min: float, max: float)

Selects a contract with open interest within the range you set.

The preceding methods return an OptionFilterUniverse, so you can chain the methods together.

To perform thorough filtering on the OptionFilterUniverse, define an isolated filter method.

Select Language: 
# Select the put contracts with the lowest strike price.
option.set_filter(self._contract_selector)
    
def _contract_selector(self, option_filter_universe: OptionFilterUniverse) -> OptionFilterUniverse:
    return option_filter_universe \
        .delta(0.5, 1.5) \
        .gamma(0.0001, 0.0006) \
        .vega(0.01, 1.5) \
        .theta(-2.0, -0.5) \
        .rho(0.5, 3.0) \
        .implied_volatility(1, 3) \
        .open_interest(100,500)

Filter by Other Contract Properties

To set a contract filter, in the initialize method, call the set_filter method of the Option object.

Select Language: 
# Select contracts that have a strike price within 1 strike level above and below the underlying price
option.set_filter(min_strike=-1, max_strike=1)

# Select contracts that expire within 30 days
option.set_filter(min_expiry=timedelta(days=0), maxExpiry=timedelta(days=30))

# Select contracts that have a strike price within 1 strike level and expire within 30 days
option.set_filter(min_strike=-1, max_strike=1, min_expiry=timedelta(days=0), maxExpiry=timedelta(days=30))

# Select call contracts
option.set_filter(lambda option_filter_universe: option_filter_universe.calls_only())

The following table describes the available filter techniques:

set_filter(minStrike: int, maxStrike: int)

Selects the contracts that have a strike price within a minimum and maximum strike level relative to the underlying price. For example, say the underlying price is $302 and there are strikes at every $5. If you set m_strike to -1 and max_strike to 1, LEAN selects the contracts that have a strike of $300 or $305. This filter runs asynchronously by default.

set_filter(minExpiry: timedelta, maxExpiry: timedelta)

Selects the contracts that expire within the range you set. This filter runs asynchronously by default.

set_filter(minStrike: int, maxStrike: int, minExpiry: timedelta, maxExpiry: timedelta)

Selects the contracts that expire and have a strike within the range you set. This filter runs asynchronously by default.

set_filter(universeFunc: Callable[[OptionFilterUniverse], OptionFilterUniverse])

Selects the contracts that a function selects.

The following table describes the filter methods of the OptionFilterUniverse class:

strikes(min_strike: int, max_strike: int)

Selects contracts that are within m_strike strikes below the underlying price and max_strike strikes above the underlying price.

calls_only()

Selects call contracts.

puts_only()

Selects put contracts.

standards_only()

Selects standard contracts.

include_weeklys()

Selects non-standard weeklys contracts.

weeklys_only()

Selects weekly contracts.

front_month()

Selects the front month contract.

back_months()

Selects the non-front month contracts.

back_month()

Selects the back month contracts.

expiration(min_expiryDays: int, max_expiryDays: int)

Selects contracts that expire within a range of dates relative to the current day.

contracts(contracts: list[Symbol])

Selects a list of contracts.

contracts(contract_selector: Callable[[list[Symbol]], list[Symbol]])

Selects contracts that a selector function selects.

The preceding methods return an OptionFilterUniverse, so you can chain the methods together.

Select Language: 
# Example 1: Select the front month call contracts
option.set_filter(lambda option_filter_universe: option_filter_universe.calls_only().front_month())

# Example 2: Select the contracts (including weeklys) that expire in the next 90 days
option.set_filter(lambda option_filter_universe: option_filter_universe.include_weeklys().strikes(-20, 20).expiration(0, 90))

Some of the preceding filter methods only set an internal enumeration in the OptionFilterUniverse that it uses later on in the filter process. This subset of filter methods don't immediately reduce the number of contract Symbol objects in the OptionFilterUniverse.

Default Filter

By default, LEAN subscribes to the Option contracts that have the following characteristics:

  • Standard type (exclude weeklys)
  • Within 1 strike price of the underlying asset price
  • Expire within 35 days

To adjust the universe of contracts, set a filter. The filter usually runs at the first bar of every day. When the filter selects a contract that isn't currently in your universe, LEAN adds the new contract data to the next Slice that it passes to the on_data method.

Navigate Intraday Option Chains

OptionChain objects represent an entire chain of Option contracts for a single underlying security.

To get the OptionChain, index the option_chains property of the Slice with the canonical symbol. After you get the OptionChain, you can sort and filter the Option contracts in the chain.

Select Language: 
def on_data(self, slice: Slice) -> None:
    # Try to get the OptionChain using the canonical symbol
    chain = slice.option_chains.get(self._symbol)
    if chain:
        # Example: Find 5 put contracts that are closest to at-the-money (ATM) and have the farthest expiration
        contracts = [x for x in chain if x.right == OptionRight.PUT]
        contracts = sorted(sorted(contracts, \
            key = lambda x: abs(chain.underlying.price - x.strike)), \
            key = lambda x: x.expiry, reverse=True)[:5]
    
        # Select the contract with the delta closest to -0.5
        contract = sorted(contracts, key=lambda x: abs(-0.5 - x.greeks.delta))[0]

You can also loop through the option_chains property to get each OptionChain.

Select Language: 
def on_data(self, slice: Slice) -> None:
    # Iterate all received Canonical Symbol-OptionChain key-value pairs
    for canonical_symbol, chain in slice.option_chains.items():
        contracts = chain.contracts

OptionChain objects have the following properties:

Navigate Daily Option Chains

To get the daily, pre-calculated Greeks and implied volaility of all the currently tradable contracts, call the option_chain method. This method returns a DataHistory[OptionUniverse] object, which you can format into a DataFrame or iterate through. Each row in the DataFrame and each OptionUniverse object represents a single contract. The data this method returns contains information on all the currently tradable contracts, not just the contracts that pass your filter.

Select Language: 
# In the initialize method, create a Scheduled Event to get the Option 
# chain and rebalance the portfolio.
self.schedule.on(
    self.date_rules.week_start(self._symbol), 
    self.time_rules.after_market_open(self._symbol, 1), 
    self._rebalance
  )

# Define the method.
def _rebalance(self):
    daily_option_chain = self.option_chain(self._symbol, flatten=True)

    # Get the DataFrame format.
    df = daily_option_chain.data_frame
    delta_by_symbol = df.delta
    
    # Get the OptionUniverse objects format.
    for option_universe in daily_option_chain:
        close = option_universe.close
        oi = option_universe.open_interest
        delta = option_universe.greeks.delta

The option_chain method was previously known as the option_chain_provider.get_option_contract_list method.

OptionUniverse objects have the following properties:

Greeks and Implied Volatility

There are several ways to get the implied volatility and Greeks of contracts.

The Greeks and IV values in the filter function are the daily, pre-calculated values based on the end of the previous trading day.

Select Language: 
def initialize(self):
    option = self.add_option("SPY")
    option.set_filter(lambda universe: universe.include_weeklys().delta(0.3, 0.7).expiration(0,7))

To calculate the values, we use our implementation of the forward tree pricing model, which accounts for the interest rate and dividend payments.

You can't customize the Greeks and IV values that the filter function receives. However, you can create indicators to customize how the Greeks and IV are calculated for the contracts already in your universe.

To override the default pricing model of the Option, set a pricing model. If you set a price model, it sets the price model of the individual contracts in the universe.

Select Language: 
// Set price_model field to use the Crank-Nicolson finite-difference model to price the Options.
option.price_model = OptionPriceModels.crank_nicolson_fd()

To override the initial guess of implied volatility, set and warm up the underlying volatility model.

Historical Data

To get historical chains for an Equity Option, call the history[OptionUniverse] method with the canonical Option Symbol. This method returns the entire Option chain for each trading day, not the subset of contracts that pass your universe filter.

Select Language: 
class OptionHistoryAlgorithm(QCAlgorithm):

    def initialize(self):
        self.set_start_date(2020, 1, 1)
        option = self.add_option('SPY')
        # DataFrame example:
        history_df = self.history(option.symbol, 5, flatten=True)
        # OptionUniverse objects example:
        history = self.history[OptionUniverse](option.symbol, 5)
        for chain in history:
            end_time = chain.end_time
            filtered_contracts = [c for c in chain if c.greeks.delta > 0.3]
            for contract in filtered_contracts:
                symbol = contract.symbol
                expiry = contract.id.date
                strike = contract.id.strike_price
                price = contract.close
                iv = contract.implied_volatility

The Greeks and IV values that you get from a history request of the Option universe are the daily, pre-calculated values based on the end of the previous trading day. To get the intraday values or to customize the Greeks and IV calculations, create some Option indicators.

The method represents each contract with an OptionUniverse object, which have the following properties:

Selection Frequency

By default, Equity Option universes run at the first time step of each day to select their contracts.

Examples

The following examples demonstrate some common Equity Option universes.

Example 1: 0DTE Contracts

0DTE Options are Option contracts that expire on the same day you trade them. The following algorithm selects 0DTE Option contracts for the SPY that fall within 3 strikes of the underlying price.

Select Language: 
class ZeroDTEOptionUniverseAlgorithm(QCAlgorithm):

    def initialize(self):
        option = self.add_option('SPY')
        option.set_filter(lambda u: u.include_weeklys().expiration(0, 0).strikes(-3, 3))

For trading full examples of Equity Option Universe, please refer to the Securities > Equity Options > Requesting Data > Universes page.

You can also see our Videos. You can also get in touch with us via Discord.

Did you find this page helpful?

Contribute to the documentation: