Overall Statistics
Total Trades
9
Average Win
1.97%
Average Loss
-1.50%
Compounding Annual Return
-6.585%
Drawdown
1.100%
Expectancy
-0.074
Net Profit
-1.107%
Sharpe Ratio
-3.299
Probabilistic Sharpe Ratio
0.217%
Loss Rate
60%
Win Rate
40%
Profit-Loss Ratio
1.32
Alpha
-0.04
Beta
-0.057
Annual Standard Deviation
0.014
Annual Variance
0
Information Ratio
-2.325
Tracking Error
0.068
Treynor Ratio
0.813
Total Fees
$6.00
Estimated Strategy Capacity
$25000.00
Lowest Capacity Asset
GOOCV WKNGGL4W0OYU|GOOCV VP83T1ZUHROL
#region imports
    using System;
    using System.Collections;
    using System.Collections.Generic;
    using System.Linq;
    using System.Globalization;
    using System.Drawing;
    using QuantConnect;
    using QuantConnect.Algorithm.Framework;
    using QuantConnect.Algorithm.Framework.Selection;
    using QuantConnect.Algorithm.Framework.Alphas;
    using QuantConnect.Algorithm.Framework.Portfolio;
    using QuantConnect.Algorithm.Framework.Execution;
    using QuantConnect.Algorithm.Framework.Risk;
    using QuantConnect.Parameters;
    using QuantConnect.Benchmarks;
    using QuantConnect.Brokerages;
    using QuantConnect.Util;
    using QuantConnect.Interfaces;
    using QuantConnect.Algorithm;
    using QuantConnect.Indicators;
    using QuantConnect.Data;
    using QuantConnect.Data.Consolidators;
    using QuantConnect.Data.Custom;
    using QuantConnect.DataSource;
    using QuantConnect.Data.Fundamental;
    using QuantConnect.Data.Market;
    using QuantConnect.Data.UniverseSelection;
    using QuantConnect.Notifications;
    using QuantConnect.Orders;
    using QuantConnect.Orders.Fees;
    using QuantConnect.Orders.Fills;
    using QuantConnect.Orders.Slippage;
    using QuantConnect.Scheduling;
    using QuantConnect.Securities;
    using QuantConnect.Securities.Equity;
    using QuantConnect.Securities.Future;
    using QuantConnect.Securities.Option;
    using QuantConnect.Securities.Forex;
    using QuantConnect.Securities.Crypto;
    using QuantConnect.Securities.Interfaces;
    using QuantConnect.Storage;
    using QuantConnect.Data.Custom.AlphaStreams;
    using QCAlgorithmFramework = QuantConnect.Algorithm.QCAlgorithm;
    using QCAlgorithmFrameworkBridge = QuantConnect.Algorithm.QCAlgorithm;
#endregion

namespace QuantConnect.Algorithm.CSharp
{
    public class BearPutSpreadStrategy : QCAlgorithm
    {
        private Symbol _symbol;

        public override void Initialize()
        {
            SetStartDate(2017, 4, 1);
            SetEndDate(2017, 5, 30);
            SetCash(150000);

            var option = AddOption("GOOG", Resolution.Minute);
            _symbol = option.Symbol;
            option.SetFilter(-9, 9, TimeSpan.FromDays(30), TimeSpan.FromDays(60));
        }

        public override void OnData(Slice slice)
        {
            // avoid extra orders
            if (Portfolio.Invested) return;

            // Get the OptionChain of the symbol
            var chain = slice.OptionChains.get(_symbol, null);
            if (chain == null || chain.Count() == 0) return;

            // sorted the optionchain by expiration date and choose the furthest date
            var expiry = chain.OrderBy(x => x.Expiry).Last().Expiry;
            // filter the call options from the contracts expires on that date
            var calls = chain.Where(x => x.Expiry == expiry && x.Right == OptionRight.Call);
            // sorted the contracts according to their strike prices
            var callContracts = calls.OrderBy(x => x.Strike);
            if (callContracts.Count() == 0) return;

            // choose OTM call
            var otmCall = callContracts.Last();
            // choose ITM call
            var itmCall = callContracts.First();
            // choose ATM call
            var atmCall = callContracts.OrderBy(x => Math.Abs(chain.Underlying.Price - x.Strike)).First();

            Sell(atmCall.Symbol, 2);
            Buy(itmCall.Symbol, 1);
            Buy(otmCall.Symbol, 1);
        }
    }
}