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Introduction

Implementation

Strategy Payoff

Example

Option Strategies

Bear Call Ladder

Introduction

Bear call ladder, also known as short call ladder, is a combination of a bear call spread and a long call with a higher strike price than the 2 legs of the call spread. All calls have the same underlying Equity and expiration date. This strategy profits from increasing volatility of the underlying asset. For instance, the underlying price moves away from its current price.

Implementation

Follow these steps to implement the bear call 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().CallLadder(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().call_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 call Option contracts with the furthest expiry
    var expiry = chain.Max(x => x.Expiry);    
    var calls = chain.Where(x => x.Expiry == expiry && x.Right == OptionRight.Call);
    if (calls.Count() == 0) return;

    // Select the strike prices from the remaining contracts
    var strikes = calls.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 call Option contracts with the furthest expiry
    expiry = max([x.expiry for x in chain])
    calls = [i for i in chain if i.expiry == expiry and i.right == OptionRight.CALL]
    if not calls:
        return

    # Select the strike prices from the remaining contracts
    strikes = sorted(set(x.strike for x in calls))
    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: Call the OptionStrategies.BearCallLadderOptionStrategies.bear_call_ladder method with the details of each leg and then pass the result to the Buybuy method.

Select Language:

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

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

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

Select Language:

var lowStrikeCall = calls.Single(x => x.Strike == lowStrike);
var middleStrikeCall = calls.Single(x => x.Strike == middleStrike);
var highStrikeCall = calls.Single(x => x.Strike == highStrike);

var legs = new List<Leg>()
{
    Leg.Create(lowStrikeCall.Symbol, -1),
    Leg.Create(middleStrikeCall.Symbol, 1),
    Leg.Create(highStrikeCall.Symbol, 1)
};
ComboMarketOrder(legs, 1, true);

low_strike_call = next(filter(lambda x: x.strike == low_strike, calls))
middle_strike_call = next(filter(lambda x: x.strike == middle_strike, calls))
high_strike_call = next(filter(lambda x: x.strike == high_strike, calls))

legs = [
    Leg.create(low_strike_call.symbol, -1),
    Leg.create(middle_strike_call.symbol, 1),
    Leg.create(high_strike_call.symbol, 1)
]
self.combo_market_order(legs, 1)

Strategy Payoff

The bear call ladding is an unlimited-profit-limited-risk strategy. The payoff is

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

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

The following chart shows the payoff at expiration:

Strategy payoff decomposition and analysis of bear call ladder

The maximum profit is unlimited, which occurs when the underlying price increases indefinitely.

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

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 call	13.80	822.50
Middle-strike call	15.10	825.00
Higher-strike call	13.10	827.50
Underlying Equity at expiration	843.25	-

Therefore, the payoff is

$\begin{array}{rcll} C^{low}_T & = & (S_T - K^{low})^{+}\\ & = & (843.25-822.50)^{+}\\ & = & 20.75\\ C^{mid}_T & = & (S_T - K^{mid})^{+}\\ & = & (843.25-825.00)^{+}\\ & = & 18.25\\ C^{high}_T & = & (S_T - K^{high})^{+}\\ & = & (843.25-827.50)^{+}\\ & = & 15.75\\ Payoff_T & = & (C^{low}_0 - C^{low}_T + C^{mid}_T - C^{mid}_0 + C^{high}_T - C^{high}_0)\times m - fee\\ & = & (13.80 - 20.75 + 18.25 - 15.10 + 15.75 - 13.10)\times100-1.00\times3\\ & = & -118\\ \end{array}$

So, the strategy loses $118.

The following algorithm implements a bear call ladder Option strategy:

Select Language:

public class BearCallLadderStrategy : 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().CallLadder(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 calls = chain.Where(x => x.Expiry == expiry && x.Right == OptionRight.Call);
        if (calls.Count() == 0) return;

        // Select the strike prices from the remaining contracts
        var strikes = calls.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.BearCallLadder(_symbol, lowStrike, middleStrike, highStrike, expiry);
        Buy(optionStrategy, 1);
    }
}

class BearCallLadderOptionStrategy(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().call_ladder(30, 5, 0, -5))

    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 call Option contracts with the furthest expiry
        expiry = max([x.expiry for x in chain])
        calls = [i for i in chain if i.expiry == expiry and i.right == OptionRight.CALL]
        if not calls:
            return

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

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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 Call 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