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Option Strategies

Naked Put

Introduction

A Naked Put, also known as an uncovered put, consists of selling put Options without having a corresponding short position in the underlying security. It's called "naked" because you don't have any cover or protection in the form of a short position in the underlying asset, which exposes you to potentially unlimited risk. Naked puts aim to profit from the Option premium by selling puts. At any time for American Options or at expiration for European Options, if the stock moves above the strike price, you keep the premium. If the underlying price moves below the strike, the Option buyer can exercise the Options contract, which means you need sell the underlying at market price to fulfill your obligation to buy it at the strike price and keep the premium.

Implementation

Follow these steps to implement the naked 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 naked 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.naked_put method with the details of each leg and then pass the result to the buy method.

    Select Language:
    naked_put = OptionStrategies.naked_put(self._symbol, atm_put.strike, expiry)
    self.buy(naked_put, 1)

    Approach B: Call the market_order or limit_order method.

    Select Language:
    self.market_order(atm_put.symbol, -1)

Strategy Payoff

The payoff of the strategy is

PKT=(KST)+PT=(PK0PKT)×mfee
wherePKT=Put value at time TST=Underlying asset price at time TK=Put strike pricePT=Payout total at time TPK0=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 naked put

The maximum profit is PK0, which occurs when the underlying price is at or above the strike price of the put at expiration.

The maximum loss is KPK0, which ocurrs when the underlying price drops to zero.

If the Option is American Option, there is a risk of early assignment on the contract you sell.

Example

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

AssetPrice ($)Strike ($)
Put1.37185.00
Underlying Equity at expiration190.01-

Therefore, the payoff is

PKT=(KST)+=(185190.01)+=0.0PT=(PK0PKT)×mfee=(1.370.0)×mfee=1.37×1001=136

So, the strategy gains $136.

The following algorithm implements a naked put Option strategy:

Select Language:
class NakedPutAlgorithm(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_put(30, 0))

        self.put = None

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

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

        naked_put = OptionStrategies.naked_put(self.symbol, atm_put.strike, expiry)
        self.buy(naked_put, 1)

        self.put = atm_put.symbol

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