wehub-resource-sync
121 lines
5.2 KiB
C#
121 lines
5.2 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using QuantConnect.Algorithm.Framework.Alphas;
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using QuantConnect.Algorithm.Framework.Execution;
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using QuantConnect.Algorithm.Framework.Portfolio;
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using QuantConnect.Algorithm.Framework.Risk;
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using QuantConnect.Algorithm.Framework.Selection;
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using QuantConnect.Data;
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using QuantConnect.Orders.Fees;
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using System;
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using System.Collections.Generic;
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using System.Linq;
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namespace QuantConnect.Algorithm.CSharp.Alphas
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{
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/// <summary>
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/// In a perfect market, you could buy 100 EUR worth of USD, sell 100 EUR worth of GBP,
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/// and then use the GBP to buy USD and wind up with the same amount in USD as you received when
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/// you bought them with EUR. This relationship is expressed by the Triangle Exchange Rate, which is
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///
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/// Triangle Exchange Rate = (A/B) * (B/C) * (C/A)
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///
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/// where (A/B) is the exchange rate of A-to-B. In a perfect market, TER = 1, and so when
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/// there is a mispricing in the market, then TER will not be 1 and there exists an arbitrage opportunity.
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///
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/// This alpha is part of the Benchmark Alpha Series created by QuantConnect which are open sourced so the community and client funds can see an example of an alpha.
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/// </summary>
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public class TriangleExchangeRateArbitrageAlpha : QCAlgorithm
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{
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public override void Initialize()
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{
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SetStartDate(2019, 2, 1);
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SetCash(100000);
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// Set zero transaction fees
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SetSecurityInitializer(security => security.FeeModel = new ConstantFeeModel(0));
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// Select trio of currencies to trade where
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// Currency A = USD
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// Currency B = EUR
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// Currency C = GBP
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var symbols = new[] { "EURUSD", "EURGBP", "GBPUSD" }
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.Select(x => QuantConnect.Symbol.Create(x, SecurityType.Forex, Market.Oanda));
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// Set requested data resolution
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UniverseSettings.Resolution = Resolution.Minute;
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SetUniverseSelection(new ManualUniverseSelectionModel(symbols));
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// Use ForexTriangleArbitrageAlphaModel to establish insights
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SetAlpha(new ForexTriangleArbitrageAlphaModel(symbols, Resolution.Minute));
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// Equally weigh securities in portfolio, based on insights
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SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
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// Set Immediate Execution Model
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SetExecution(new ImmediateExecutionModel());
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// Set Null Risk Management Model
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SetRiskManagement(new NullRiskManagementModel());
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}
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private class ForexTriangleArbitrageAlphaModel : AlphaModel
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{
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private readonly Symbol[] _symbols;
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private readonly TimeSpan _insightPeriod;
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public ForexTriangleArbitrageAlphaModel(
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IEnumerable<Symbol> symbols,
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Resolution resolution = Resolution.Minute)
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{
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_symbols = symbols.ToArray();
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_insightPeriod = resolution.ToTimeSpan().Multiply(5);
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}
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public override IEnumerable<Insight> Update(QCAlgorithm algorithm, Slice data)
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{
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// Check to make sure all currency symbols are present
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if (data.QuoteBars.Count < 3)
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{
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return Enumerable.Empty<Insight>();
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}
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// Extract QuoteBars for all three Forex securities
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var barA = data[_symbols[0]];
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var barB = data[_symbols[1]];
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var barC = data[_symbols[2]];
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// Calculate the triangle exchange rate
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// Bid(Currency A -> Currency B) * Bid(Currency B -> Currency C) * Bid(Currency C -> Currency A)
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// If exchange rates are priced perfectly, then this yield 1.If it is different than 1, then an arbitrage opportunity exists
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var triangleRate = barA.Ask.Close / barB.Bid.Close / barC.Ask.Close;
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// If the triangle rate is significantly different than 1, then emit insights
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if (triangleRate > 1.0005m)
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{
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return Insight.Group(new[]
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{
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Insight.Price(_symbols[0], _insightPeriod, InsightDirection.Up, 0.0001),
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Insight.Price(_symbols[1], _insightPeriod, InsightDirection.Down, 0.0001),
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Insight.Price(_symbols[2], _insightPeriod, InsightDirection.Up, 0.0001)
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});
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}
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return Enumerable.Empty<Insight>();
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}
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}
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}
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} |