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Option Strategies

Protective Put

Introduction

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

Implementation

Follow these steps to implement the protective put strategy:

  1. In the initialize method, set the start date, end date, starting 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_put(30, 0))

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

  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 put with the farthest expiry
        expiry = max([x.expiry for x in chain])
        put_contracts = sorted([x for x in chain
            if x.right == OptionRight.PUT and x.expiry == expiry],
            key=lambda x: abs(chain.underlying.price - x.strike))
    
        if not put_contracts:
            return
    
        atm_put = put_contracts[0]
  5. In the on_data method, place the orders.
  6. Approach A: Call the OptionStrategies.protective_put method with the details of each leg and then pass the result to the buy method.

    Select Language:
    protective_put = OptionStrategies.protective_put(self._symbol, atm_put.strike, expiry)
    self.buy(protective_put, 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_put.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

PKT=(KST)+PT=(STS0+PKTPK0)×mfee wherePKT=Put value at time TST=Underlying asset price at time TK=Put strike pricePT=Payout total at time TS0=Underlying asset price when the trade openedPK0=Put 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 put

The maximum profit is STS0PK0, which occurs when the underlying price is above the S0+PK0.

The maximum loss is PK0, which occurs when the underlying price drops.

Example

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

AssetPrice ($)Strike ($)
Put1.53185.00
Underlying Equity at start of the trade187.07-
Underlying Equity at expiration190.01-

Therefore, the payoff is

PKT=(KST)+=(185190.1)+=0PT=(STS0+PKTPK0)×mfee=(190.01187.07+01.53)×mfee=1.41×1002=139

So, the strategy gains $139.

The following algorithm implements a protective put Option strategy:

Select Language:
class ProtectivePutAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self.SetStartDate(2014, 1, 1)
        self.SetEndDate(2014, 3, 1)
        self.SetCash(100000)

        option = self.AddOption("IBM")
        self.symbol = option.Symbol
        option.set_filter(lambda universe: universe.include_weeklys().naked_put(30, 0))

        self.put = None

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

    def OnData(self, slice: Slice) -> None:
        if self.put and self.Portfolio[self.put].Invested:
            return

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

        # Find ATM put with the farthest expiry
        expiry = max([x.Expiry for x in chain])
        put_contracts = sorted([x for x in chain
            if x.Right == OptionRight.Put and x.Expiry == expiry],
            key=lambda x: abs(chain.Underlying.Price - x.Strike))

        if not put_contracts:
            return

        atm_put = put_contracts[0]

        protective_put = OptionStrategies.ProtectivePut(self.symbol, atm_put.Strike, expiry)
        self.Buy(protective_put, 1)

        self.put = atm_put.Symbol

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