In This Page

Introduction

Implementation

Strategy Payoff

Example

Option Strategies

Bear Put Ladder

Introduction

Bear put ladder, also known as long put ladder, is a combination of a bear put spread and short put with a lower strike price than the 2 legs of the put spread. All puts have the same underlying Equity and expiration date. This strategy profits from low volatility of the underlying asset. For instance, the underlying price stays similar to its current price.

Implementation

Follow these steps to implement the bear put ladder strategy:

In the Initializeinitialize method, set the start date, end date, cash, and Option universe.

Select Language:

private Symbol _symbol;

public override void Initialize()
{
    SetStartDate(2017, 4, 1);
    SetEndDate(2017, 4, 22);
    SetCash(1000000);

    UniverseSettings.Asynchronous = true;
    var option = AddOption("GOOG", Resolution.Minute);
    _symbol = option.Symbol;
    option.SetFilter(universe => universe.IncludeWeeklys().PutLadder(30, 5, 0, -5));
}

def initialize(self) -> None:
    self.set_start_date(2017, 4, 1)
    self.set_end_date(2017, 4, 22)
    self.set_cash(1000000)

    self.universe_settings.asynchronous = True
    option = self.add_option("GOOG", Resolution.MINUTE)
    self._symbol = option.symbol
    option.set_filter(lambda universe: universe.include_weeklys().put_ladder(30, 5, 0, -5))

In the OnDataon_data method, select the expiration and strikes of the contracts in the strategy legs.

Select Language:

public override void OnData(Slice slice)
{
    if (Portfolio.Invested ||
        !slice.OptionChains.TryGetValue(_symbol, out var chain))
    {
        return;
    }

    // Select the put Option contracts with the furthest expiry
    var expiry = chain.Max(x => x.Expiry);    
    var puts = chain.Where(x => x.Expiry == expiry && x.Right == OptionRight.Put);
    if (puts.Count() == 0) return;

    // Select the strike prices from the remaining contracts
    var strikes = puts.Select(x => x.Strike).Distinct().OrderBy(x => x).ToList();
    if (strikes.Count < 3)
    {
        return;
    }
    
    var lowStrike = strikes[0];
    var middleStrike = strikes[1];
    var highStrike = strikes[2];

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

    # Get the OptionChain
    chain = slice.option_chains.get(self._symbol, None)
    if not chain:
        return
    
    # Select the put Option contracts with the furthest expiry
    expiry = max([x.expiry for x in chain])
    puts = [i for i in chain if i.expiry == expiry and i.right == OptionRight.PUT]
    if not puts:
        return

    # Select the strike prices from the remaining contracts
    strikes = sorted(set(x.strike for x in puts))
    if len(strikes) < 3:
        return
    
    low_strike = strikes[0]
    middle_strike = strikes[1]
    high_strike = strikes[2]

In the OnDataon_data method, select the contracts and place the orders.

Approach A: Put the OptionStrategies.BearPutLadderOptionStrategies.bear_put_ladder method with the details of each leg and then pass the result to the Buybuy method.

Select Language:

var optionStrategy = OptionStrategies.BearPutLadder(_symbol, highStrike, middleStrike, lowStrike, expiry);
Buy(optionStrategy, 1);

option_strategy = OptionStrategies.bear_put_ladder(self._symbol, high_strike, middle_strike, low_strike, expiry)
self.buy(option_strategy, 1)

Approach B: Create a list of Leg objects and then put the Combo Market Ordercombo_market_order, Combo Limit Ordercombo_limit_order, or Combo Leg Limit Ordercombo_leg_limit_order method.

Select Language:

var lowStrikePut = puts.Single(x => x.Strike == lowStrike);
var middleStrikePut = puts.Single(x => x.Strike == middleStrike);
var highStrikePut = puts.Single(x => x.Strike == highStrike);

var legs = new List<Leg>()
{
    Leg.Create(lowStrikePut.Symbol, -1),
    Leg.Create(middleStrikePut.Symbol, -1),
    Leg.Create(highStrikePut.Symbol, 1)
};
ComboMarketOrder(legs, 1, true);

low_strike_put = next(filter(lambda x: x.strike == low_strike, puts))
middle_strike_put = next(filter(lambda x: x.strike == middle_strike, puts))
high_strike_put = next(filter(lambda x: x.strike == high_strike, puts))

legs = [
    Leg.create(low_strike_put.symbol, -1),
    Leg.create(middle_strike_put.symbol, -1),
    Leg.create(high_strike_put.symbol, 1)
]
self.combo_market_order(legs, 1)

Strategy Payoff

The bear put ladding is an limited-profit strategy. The payoff is

$\begin{array}{rcll} P^{low}_T & = & (K^{low} - S_T)^{+}\\ P^{mid}_T & = & (K^{mid} - S_T)^{+}\\ P^{high}_T & = & (K^{high} - S_T)^{+}\\ Payoff_T & = & (P^{low}_0 - P^{low}_T + P^{mid}_0 - P^{mid}_T + P^{high}_T - P^{high}_0)\times m - fee\\ \end{array}$

$\begin{array}{rcll} \textrm{where} & P^{low}_T & = & \textrm{Lower-strike put value at time T}\\ & P^{mid}_T & = & \textrm{Middle-strike put value at time T}\\ & P^{high}_T & = & \textrm{Higher-strike put value at time T}\\ & S_T & = & \textrm{Underlying asset price at time T}\\ & K^{low} & = & \textrm{Lower-strike put strike price}\\ & K^{mid} & = & \textrm{Middle-strike put strike price}\\ & K^{high} & = & \textrm{Higher-strike put strike price}\\ & P^{low}_0 & = & \textrm{Lower-strike put value at position opening (credit received)}\\ & P^{mid}_0 & = & \textrm{Middle-strikeTM put value at position opening (debit paid)}\\ & P^{high}_0 & = & \textrm{Higher-strike put value at position opening (debit paid)}\\ & m & = & \textrm{Contract multiplier}\\ & T & = & \textrm{Time of expiration} \end{array}$

The following chart shows the payoff at expiration:

Strategy payoff decomposition and analysis of bear put ladder

The maximum profit is $K^{high} - K^{mid} + P^{low}_0 + P^{mid}_0 - P^{high}_0$ , which occurs when the underlying price is between the two lower strike prices.

The maximum loss is $K^{high} - K^{mid} - K^{low} + P^{low}_0 + P^{mid}_0 - P^{high}_0$ , which occurs when the underlying price decreases to $0.

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:

Asset	Price ($)	Strike ($)
Lower-Strike put	3.80	822.50
Middle-strike put	4.70	825.00
Higher-strike put	7.80	827.50
Underlying Equity at expiration	843.25	-

Therefore, the payoff is

$\begin{array}{rcll} P^{low}_T & = & (K^{low} - S_T)^{+}\\ & = & (822.50-843.25)^{+}\\ & = & 0\\ P^{mid}_T & = & (K^{mid} - S_T)^{+}\\ & = & (825.00-843.25)^{+}\\ & = & 0\\ P^{high}_T & = & (K^{high} - S_T)^{+}\\ & = & (827.50-843.25)^{+}\\ & = & 0\\ Payoff_T & = & (P^{low}_0 - P^{low}_T + P^{mid}_0 - P^{mid}_T + P^{high}_T - P^{high}_0)\times m - fee\\ & = & (3.80 - 0 + 4.70 - 0 + 0 - 7.80)\times100-1.00\times3\\ & = & 67\\ \end{array}$

So, the strategy gains $67.

The following algorithm implements a bear put ladder Option strategy:

Select Language:

public class BearPutLadderStrategy : QCAlgorithm
{
    private Symbol _symbol;

    public override void Initialize()
    {
        SetStartDate(2017, 4, 1);
        SetEndDate(2017, 4, 23);
        SetCash(100000);

        var option = AddOption("GOOG", Resolution.Minute);
        _symbol = option.Symbol;
        option.SetFilter(universe => universe.IncludeWeeklys().PutLadder(30, 5, 0, -5));
    }

    public override void OnData(Slice slice)
    {
        if (Portfolio.Invested ||
            !slice.OptionChains.TryGetValue(_symbol, out var chain))
        {
            return;
        }

        // Select the call Option contracts with the furthest expiry
        var expiry = chain.Max(x => x.Expiry);    
        var puts = chain.Where(x => x.Expiry == expiry && x.Right == OptionRight.Put);
        if (puts.Count() == 0) return;

        // Select the strike prices from the remaining contracts
        var strikes = puts.Select(x => x.Strike).Distinct().OrderBy(x => x).ToList();
        if (strikes.Count < 3)
        {
            return;
        }
        
        var lowStrike = strikes[0];
        var middleStrike = strikes[1];
        var highStrike = strikes[2];

        // Order Strategy
        var optionStrategy = OptionStrategies.BearPutLadder(_symbol, highStrike, middleStrike, lowStrike, expiry);
        Buy(optionStrategy, 1);
    }
}

class BearPutLadderOptionStrategy(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2017, 4, 1)
        self.set_end_date(2017, 4, 23)
        self.set_cash(100000)
        
        option = self.add_option("GOOG", Resolution.MINUTE)
        self._symbol = option.symbol

        # set our strike/expiry filter for this option chain
        option.set_filter(lambda x: x.include_weeklys().put_ladder(30, 5, 0, -5))

    def on_data(self, slice) -> None:
        if self.portfolio.invested:
            return

        # Get the OptionChain
        chain = slice.option_chains.get(self._symbol, None)
        if not chain:
            return
        
        # Select the call Option contracts with the furthest expiry
        expiry = max([x.expiry for x in chain])
        puts = [i for i in chain if i.expiry == expiry and i.right == OptionRight.PUT]
        if not puts:
            return

        # Select the strike prices from the remaining contracts
        strikes = sorted(set(x.strike for x in puts))
        if len(strikes) < 3:
            return
        
        low_strike = strikes[0]
        middle_strike = strikes[1]
        high_strike = strikes[2]
    
        option_strategy = OptionStrategies.bear_put_ladder(self._symbol, high_strike, middle_strike, low_strike, expiry)
        self.buy(option_strategy, 1)

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Bear Put Ladder

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Browse

Cloud Platform

Writing Algorithms

▶Key Concepts

Initialization

▶Securities

▶Portfolio

▶Universes

▶Datasets

▶Importing Data

▶Consolidating Data

▶Historical Data

▶Trading and Orders

▶Reality Modeling

Scheduled Events

▶Indicators

Object Store

▶Optimization

▶Machine Learning

▶Algorithm Framework

Charting

Logging

▶Statistics

▶Live Trading

Strategy Library

API Reference

▶Migrations

Research Environment

Local Platform

LEAN CLI

LEAN Engine

Hello

Option Strategies

Bear Put Ladder

Introduction

Implementation

Strategy Payoff

Example

▶
Key Concepts

▶
Securities

▶
Portfolio

▶
Universes

▶
Datasets

▶
Importing Data

▶
Consolidating Data

▶
Historical Data

▶
Trading and Orders

▶
Reality Modeling

▶
Indicators

▶
Optimization

▶
Machine Learning

▶
Algorithm Framework

▶
Statistics

▶
Live Trading

▶
Migrations