Overall Statistics |
Total Trades 13598 Average Win 0.13% Average Loss -0.95% Compounding Annual Return 105.716% Drawdown 12.400% Expectancy 0.023 Net Profit 323.783% Sharpe Ratio 2.611 Loss Rate 10% Win Rate 90% Profit-Loss Ratio 0.14 Alpha 0.52 Beta 0.016 Annual Standard Deviation 0.2 Annual Variance 0.04 Information Ratio 2.097 Tracking Error 0.229 Treynor Ratio 31.922 Total Fees $543.92 |
using System; using System.Collections.Generic; using System.Linq; using System.Text; using System.Threading.Tasks; using QuantConnect.Data.Market; namespace QuantConnect.Algorithm.CSharp { class ProfitTargetSignalExit : IExitSignal { private TradeProfile _tradeProfile; private decimal _targetProfitLossRatio; public ProfitTargetSignalExit() { } public ProfitTargetSignalExit(TradeProfile tradeProfile, decimal targetProfitLossRatio) { _tradeProfile = tradeProfile; _targetProfitLossRatio = targetProfitLossRatio; } public void Scan(TradeBar data) { if (_tradeProfile.ProfitLossRatio > _targetProfitLossRatio) { Signal = SignalType.Exit; } else { Signal = SignalType.NoSignal; } } public SignalType Signal { get; private set; } public ISignal ExitSignalFactory(TradeProfile tradeProfile) { return new ProfitTargetSignalExit(tradeProfile, _targetProfitLossRatio); } } }
using System; using System.Collections.Generic; using System.Linq; using System.Text; using System.Threading.Tasks; using QuantConnect.Data.Market; using QuantConnect.Securities; namespace QuantConnect.Algorithm.CSharp { class OneShotTrigger : ISignal { private ISignal _signal; private SignalType _previousSignalType; public OneShotTrigger(ISignal signal) { _signal = signal; Signal = SignalType.NoSignal; _previousSignalType = SignalType.NoSignal; } public void Scan(TradeBar data) { _signal.Scan(data); if (_signal.Signal != _previousSignalType) { Signal = _signal.Signal; } else { Signal = SignalType.NoSignal; } _previousSignalType = _signal.Signal; } public SignalType Signal { get; private set; } } }
using System; using System.Collections.Generic; using System.Security.Permissions; using QuantConnect.Data.Market; using QuantConnect.Indicators; using QuantConnect.Securities; namespace QuantConnect.Algorithm.CSharp { class RsiSignal : ISignal { private RelativeStrengthIndex _rsi; private SecurityHolding _securityHolding; public RsiSignal(RelativeStrengthIndex rsi, SecurityHolding securityHolding) { _rsi = rsi; _securityHolding = securityHolding; } public void Scan(TradeBar data) { if (_rsi > 70 && !_securityHolding.Invested) { Signal = SignalType.Short; } else if (_rsi < 30 && !_securityHolding.Invested) { Signal = SignalType.Long; } else { Signal = SignalType.NoSignal; } } public SignalType Signal { get; private set; } } }
using QuantConnect.Data.Market; namespace QuantConnect.Algorithm.CSharp { /// <summary> /// Base Signal Interface /// </summary> public interface ISignal { void Scan(TradeBar data); SignalType Signal { get; } } public interface IExitSignal : ISignal { ISignal ExitSignalFactory(TradeProfile tradeProfile); } public enum SignalType { Long = 1, Short = -1, Exit = 2, NoSignal = 0 } }
using System; using System.Collections.Generic; using System.Linq; using QuantConnect.Data.Market; using QuantConnect.Orders; using QuantConnect.Securities; namespace QuantConnect.Algorithm.CSharp { class TradingAsset { public IExitSignal ExitSignal; public ISignal EnterSignal; private decimal _risk; private Symbol _symbol; private Security _security; private decimal _maximumTradeSize; private List<TradeProfile> _tradeProfiles; private IRequiredOrderMethods _orderMethods; // private decimal _targetProfitLossRatio; /// <summary> /// Initializes each Trading Asset /// </summary> /// <param name="security"></param> /// <param name="enterSignal"></param> /// <param name="exitSignal"></param> /// <param name="risk"></param> /// <param name="maximumTradeSize"></param> /// <param name="orderMethods"></param> public TradingAsset(Security security, ISignal enterSignal, IExitSignal exitSignal, decimal risk, decimal maximumTradeSize, IRequiredOrderMethods orderMethods) { _security = security; _symbol = _security.Symbol; EnterSignal = enterSignal; ExitSignal = exitSignal; _risk = risk; _maximumTradeSize = maximumTradeSize; _orderMethods = orderMethods; _tradeProfiles = new List<TradeProfile>(); } /// <summary> /// Scan /// </summary> /// <param name="data"></param> public void Scan(TradeBar data) { foreach (var tradeProfile in _tradeProfiles) { tradeProfile.CurrentPrice = data.Close; } MarkStopTicketsFilled(); EnterTradeSignal(data); ExitTradeSignal(data); RemoveAllFinishedTrades(); } /// <summary> /// Executes all the logic when the Enter Signal is triggered /// </summary> /// <param name="data"></param> public void EnterTradeSignal(TradeBar data) { EnterSignal.Scan(data); if (EnterSignal.Signal == SignalType.Long || EnterSignal.Signal == SignalType.Short) { //Creates a new trade profile once it enters a trade var profile = new TradeProfile(_symbol, _security.VolatilityModel.Volatility, _risk, data.Close, _maximumTradeSize); profile.ExitSignal = ExitSignal.ExitSignalFactory(profile); var profileQuantity = profile.Quantity; if (profileQuantity > 0) { profile.OpenTicket = _orderMethods.MarketOrder(_symbol, (int)EnterSignal.Signal * profile.Quantity); profile.StopTicket = _orderMethods.StopMarketOrder(_symbol, -(int)EnterSignal.Signal * profile.Quantity, profile.OpenTicket.AverageFillPrice - (int)EnterSignal.Signal * profile.DeltaStopLoss); _tradeProfiles.Add(profile); } } } /// <summary> /// Executes all the logic when the Exit Signal is triggered /// </summary> /// <param name="data"></param> public void ExitTradeSignal(TradeBar data) { foreach (var tradeProfile in _tradeProfiles.Where(x => x.IsTradeFinished == false)) { tradeProfile.ExitSignal.Scan(data); if (tradeProfile.ExitSignal.Signal == SignalType.Exit) { if (tradeProfile.StopTicket.Status != OrderStatus.Filled) { tradeProfile.ExitTicket = _orderMethods.MarketOrder(_symbol, -(int)tradeProfile.OpenTicket.QuantityFilled); tradeProfile.StopTicket.Cancel(); tradeProfile.IsTradeFinished = true; } } } } /// <summary> /// Marks all the trades as finished which are completed due to hitting the stop loss /// </summary> public void MarkStopTicketsFilled() { foreach (var tradeProfile in _tradeProfiles) { if (tradeProfile.StopTicket.Status == OrderStatus.Filled) { tradeProfile.IsTradeFinished = true; } } } /// <summary> /// Removes all the completed trades from the trade profile list /// </summary> public void RemoveAllFinishedTrades() { _tradeProfiles = _tradeProfiles.Where(x => !x.IsTradeFinished).ToList(); } } }
using QuantConnect.Orders; namespace QuantConnect.Algorithm.CSharp { public class TradeProfile { //Ticket tracking the open order public OrderTicket OpenTicket, StopTicket, ExitTicket; //Keeps track of the current price and the direction of the trade public decimal CurrentPrice; public int TradeDirection; public Symbol TradeSymbol; private bool isTradeFinished; private decimal _risk; private int _maximumTradeQuantity; protected decimal _volatility; // Calclate the quantity based on the target risk in dollars. public int Quantity { get { if (_volatility == 0) return 0; long quantity = (long)(_risk / _volatility); if (quantity > _maximumTradeQuantity) return _maximumTradeQuantity; return (int)quantity; } } //What is the stoploss move from current price public decimal DeltaStopLoss { get { if (Quantity == 0) return 0m; return _risk / Quantity; } } /// <summary> /// Calculates the Profit:Loss ratio /// </summary> public decimal ProfitLossRatio { get { if(OpenTicket != null) { return OpenTicket.Quantity*(CurrentPrice - OpenTicket.AverageFillPrice) /_risk; } return 0m; } } /// <summary> /// Exit signal for each trade /// </summary> public ISignal ExitSignal { get; set; } public bool IsTradeFinished { get { return isTradeFinished; } set { isTradeFinished = value; } } /// <summary> /// Create a new tradeProfile and limit the maximum risk. /// </summary> /// <param name="symbol"></param> /// <param name="volatility"></param> /// <param name="risk"></param> /// <param name="currentPrice"></param> /// <param name="maximumTradeSize"></param> /// <param name="exitSignal"></param> public TradeProfile(Symbol symbol, decimal volatility, decimal risk, decimal currentPrice, decimal maximumTradeSize) { TradeSymbol = symbol; _volatility = volatility; _risk = risk; CurrentPrice = currentPrice; _maximumTradeQuantity = (int) (maximumTradeSize/CurrentPrice); } } }
/* * 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.Collections.Generic; using QuantConnect.Data.Market; using QuantConnect.Indicators; using QuantConnect.Orders; using QuantConnect.Orders.Fees; using QuantConnect.Securities; namespace QuantConnect.Algorithm.CSharp { /// <summary> /// Basic template algorithm simply initializes the date range and cash /// </summary> public class BasicTemplateAlgorithm : QCAlgorithm, IRequiredOrderMethods { //Configure which securities you'd like to use: public string[] Symbols = { "EURUSD" , "GBPUSD", "NZDUSD", "AUDUSD"}; // Single asset //public string[] Symbols = { "EURUSD" }; //Risk in dollars per trade ($ or the quote currency of the assets) public decimal RiskPerTrade = 40; //Sets the profit to loss ratio we want to hit before we exit public decimal TargetProfitLossRatio = 0.1m; //Cap the investment maximum size ($). public decimal MaximumTradeSize = 10000; private Resolution _dataResolution = Resolution.Minute; private Dictionary<Symbol, TradingAsset> _tradingAssets; //List to store the RSI value for each asset private RelativeStrengthIndex _rsi; public override void Initialize() { SetStartDate(2014, 1, 1); SetEndDate(2016, 1, 1); SetCash(2000); _tradingAssets = new Dictionary<Symbol, TradingAsset>(); //Add as many securities as you like. All the data will be passed into the event handler: foreach (var symbol in Symbols) { AddSecurity(SecurityType.Forex, symbol, _dataResolution); Securities[symbol].FeeModel = new ConstantFeeModel(0.04m); //SetBrokerageModel(BrokerageName.FxcmBrokerage); _rsi = RSI(symbol, 60, MovingAverageType.Exponential, _dataResolution); var tradeBarHistory = History(symbol, TimeSpan.FromDays(2), _dataResolution); foreach (var tradeBar in tradeBarHistory) { _rsi.Update(tradeBar.EndTime, tradeBar.Close); } Securities[symbol].VolatilityModel = new ThreeSigmaVolatilityModel(STD(symbol, 390, _dataResolution)); _tradingAssets.Add(symbol, new TradingAsset(Securities[symbol], new OneShotTrigger(new RsiSignal(_rsi, Portfolio[symbol])), new ProfitTargetSignalExit(null, TargetProfitLossRatio), RiskPerTrade, MaximumTradeSize, this )); } } /// <summary> /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. /// </summary> public void OnData(TradeBars data) { foreach (var symbol in Symbols) { //Create a trading asset package for each symbol _tradingAssets[symbol].Scan(data[symbol]); } } public override void OnEndOfDay() { foreach (var symbol in Symbols) { Plot("Charts", "Holdings", Portfolio[symbol].Quantity); Plot("Charts", "RSI", _rsi); } } } /// <summary> /// Interface for the two types of orders required to make the trade /// </summary> public interface IRequiredOrderMethods { OrderTicket StopMarketOrder(Symbol symbol, int quantity, decimal stopPrice, string tag = ""); OrderTicket MarketOrder(Symbol symbol, int quantity, bool asynchronous = false, string tag = ""); } }
/* * 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 MathNet.Numerics.Statistics; using QuantConnect.Data; using QuantConnect.Indicators; namespace QuantConnect.Securities { /// <summary> /// Provides an implementation of <see cref="IVolatilityModel"/> that computes the /// relative standard deviation as the volatility of the security /// </summary> public class ThreeSigmaVolatilityModel : IVolatilityModel { private StandardDeviation _standardDeviation; /// <summary> /// Gets the volatility of the security as a percentage /// </summary> public decimal Volatility { get { return _standardDeviation*2.5m; } } /// <summary> /// Initializes a new instance of the <see cref="QuantConnect.Securities.RelativeStandardDeviationVolatilityModel"/> class /// </summary> /// <param name="periodSpan">The time span representing one 'period' length</param> /// <param name="periods">The nuber of 'period' lengths to wait until updating the value</param> public ThreeSigmaVolatilityModel(StandardDeviation standardDeviation) { _standardDeviation = standardDeviation; } /// <summary> /// Updates this model using the new price information in /// the specified security instance /// </summary> /// <param name="security">The security to calculate volatility for</param> /// <param name="data"></param> public void Update(Security security, BaseData data) { } } }