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

Option Strategies

Protective Call

Introduction

A Protective Call consists of a short position in a stock and a long position in a call Option for the same amount of stock. Protective calls aim to hedge the short position of a stock with a long ATM or slightly OTM call Option. At any time for American Options or at expiration for European Options, if the stock moves below the strike price, the Option contract becomes worthless but the short position acquires an unrealized gain. If the underlying price moves above the strike, you can exercise the Options contract and receive the underlying Equity, which closes your short position.

Implementation

Follow these steps to implement the protective call strategy:

  1. In the initialize method, set the start date, end date, cash, and Options universe.
  2. Select Language:
    def initialize(self) -> None:
        self.set_start_date(2014, 1, 1)
        self.set_end_date(2014, 3, 1)
        self.set_cash(100000)
    
        self.universe_settings.asynchronous = True
        option = self.add_option("IBM")
        self._symbol = option.symbol
        option.set_filter(lambda universe: universe.include_weeklys().naked_call(30, 0))

    The naked_call filter narrows the universe down to just the one contract you need to form a protective call.

  3. In the on_data method, select the Option contract.
  4. Select Language:
    def on_data(self, slice: Slice) -> None:
        if self.portfolio.invested:
            return
    
        chain = slice.option_chains.get(self._symbol)
        if not chain:
            return
    
        # Find ATM call with the farthest expiry
        expiry = max([x.expiry for x in chain])
        call_contracts = sorted([x for x in chain
            if x.right == OptionRight.CALL and x.expiry == expiry],
            key=lambda x: abs(chain.underlying.price - x.strike))
    
        if not call_contracts:
            return
    
        atm_call = call_contracts[0]
  5. In the on_data method, place the orders.
  6. Approach A: Call the OptionStrategies.protective_call method with the details of each leg and then pass the result to the buy method.

    Select Language:
    protective_call = OptionStrategies.protective_call(self._symbol, atm_call.strike, expiry)
    self.buy(protective_call, 1)

    Approach B: Create a list of Leg objects and then call the combo_market_order, combo_limit_order, or combo_leg_limit_order method.

    Select Language:
    legs = [
        Leg.create(atm_call.symbol, 1),
        Leg.create(chain.underlying.symbol, -chain.underlying.symbol_properties.contract_multiplier)
    ]
    self.combo_market_order(legs, 1)

Strategy Payoff

The payoff of the strategy is

CKT=(STK)+PT=(S0ST+CKTCK0)×mfee whereCKT=Call value at time TST=Underlying asset price at time TK=Call strike pricePT=Payout total at time TS0=Underlying asset price when the trade openedCK0=Call price when the trade opened (credit received)m=Contract multiplierT=Time of expiration

The following chart shows the payoff at expiration:

Strategy payoff decomposition and analysis of protective call

The maximum profit is S0CK0, which occurs when the underlying price is 0.

The maximum loss is S0KCK0, which occurs when the underlying price is above the strike price.

Example

The following table shows the price details of the assets in the algorithm:

AssetPrice ($)Strike ($)
Call3.50185.00
Underlying Equity at start of the trade186.94-
Underlying Equity at expiration190.01-

Therefore, the payoff is

CKT=(STK)+=(190.01185)+=5.01PT=(S0ST+CKTCK0)×mfee=(186.94190.01+5.013.50)×mfee=1.56×1002=158

So, the strategy loses $158.

The following algorithm implements a protective call Option strategy:

Select Language:
class ProtectiveCallAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2014, 1, 1)
        self.set_end_date(2014, 3, 1)
        self.set_cash(100000)

        option = self.add_option("IBM")
        self.symbol = option.symbol
        option.set_filter(lambda universe: universe.include_weeklys().naked_call(30, 0))

        self.call = None

        # use the underlying equity as the benchmark
        self.set_benchmark(self.symbol.underlying)

    def on_data(self, slice: Slice) -> None:
        if self.call and self.portfolio[self.call].invested:
            return

        chain = slice.option_chains.get(self.symbol)
        if not chain:
            return

        # Find ATM call with the farthest expiry
        expiry = max([x.expiry for x in chain])
        call_contracts = sorted([x for x in chain
            if x.right == OptionRight.CALL and x.expiry == expiry],
            key=lambda x: abs(chain.underlying.price - x.strike))

        if not call_contracts:
            return

        atm_call = call_contracts[0]

        protective_call = OptionStrategies.protective_call(self.symbol, atm_call.strike, expiry)
        self.buy(protective_call, 1)

        self.call = atm_call.symbol

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: