/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using System;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using System.Collections.Generic;
using QuantConnect.Securities.Option.StrategyMatcher;
namespace QuantConnect.Algorithm.CSharp
{
///
/// Regression algorithm exercising an equity Short Box Spread option strategy and asserting it's being detected by Lean and works as expected
///
public class OptionEquityShortBoxSpreadRegressionAlgorithm : OptionEquityBaseStrategyRegressionAlgorithm
{
///
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
///
/// Slice object keyed by symbol containing the stock data
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{
OptionChain chain;
if (IsMarketOpen(_optionSymbol) && slice.OptionChains.TryGetValue(_optionSymbol, out chain))
{
var contracts = chain.GroupBy(x => x.Expiry)
.First()
.OrderBy(x => x.Strike)
.ToList();
var buySidePut = contracts.Last(contract => contract.Right == OptionRight.Put);
var sellSidePut = contracts.First(contract => contract.Right == OptionRight.Put
&& contract.Expiry == buySidePut.Expiry
&& contract.Strike < buySidePut.Strike);
var buySideCall = contracts.First(contract => contract.Right == OptionRight.Call
&& contract.Expiry == buySidePut.Expiry
&& contract.Strike == buySidePut.Strike);
var sellSideCall = contracts.First(contract => contract.Right == OptionRight.Call
&& contract.Expiry == buySidePut.Expiry
&& contract.Strike == sellSidePut.Strike);
var initialMargin = Portfolio.MarginRemaining;
MarketOrder(buySideCall.Symbol, +10);
MarketOrder(buySidePut.Symbol, -10);
MarketOrder(sellSideCall.Symbol, -10);
MarketOrder(sellSidePut.Symbol, +10);
AssertOptionStrategyIsPresent(OptionStrategyDefinitions.ShortBoxSpread.Name, 10);
var freeMarginPostTrade = Portfolio.MarginRemaining;
var commissionFees = 10m * 0.65m * 4m;
var orderCosts = sellSideCall.AskPrice - buySideCall.BidPrice + buySidePut.AskPrice - sellSidePut.BidPrice;
var closeCost = commissionFees + orderCosts * 1000m;
var strikeDifference = buySideCall.Strike - sellSideCall.Strike;
var expectedMarginUsage = Math.Max(1.02m * closeCost, strikeDifference * 1000m);
if (expectedMarginUsage != Portfolio.TotalMarginUsed)
{
throw new RegressionTestException("Unexpect margin used!");
}
// we payed the ask and value using the assets price
var priceSpreadDifference = GetPriceSpreadDifference(buySidePut.Symbol, buySideCall.Symbol,
sellSidePut.Symbol, sellSideCall.Symbol);
if (initialMargin != (freeMarginPostTrade + expectedMarginUsage + _paidFees - priceSpreadDifference))
{
throw new RegressionTestException("Unexpect margin remaining!");
}
}
}
}
///
/// Data Points count of all timeslices of algorithm
///
public override long DataPoints => 15023;
///
/// Data Points count of the algorithm history
///
public override int AlgorithmHistoryDataPoints => 0;
///
/// Final status of the algorithm
///
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
///
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
///
public override Dictionary ExpectedStatistics => new Dictionary
{
{"Total Orders", "4"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "200000"},
{"End Equity", "197924"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0"},
{"Annual Variance", "0"},
{"Information Ratio", "0"},
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$26.00"},
{"Estimated Strategy Capacity", "$23000.00"},
{"Lowest Capacity Asset", "GOOCV W78ZERHAOVVQ|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "28.04%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "f91f438caebb667dda197418168eadd3"}
};
}
}