/* * 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.Algorithm.Framework.Alphas; using QuantConnect.Data.Market; using QuantConnect.Indicators; using QuantConnect.Interfaces; namespace QuantConnect.Algorithm.CSharp { /// /// Demonstration algorithm showing how to easily convert an old algorithm into the framework. /// /// 1. When making orders, also create insights for the correct direction (up/down/flat), can also set insight prediction period/magnitude/direction /// 2. Emit insights before placing any trades /// 3. Profit :) /// /// /// /// public class ConvertToFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private MovingAverageConvergenceDivergence _macd; private readonly string _symbol = "SPY"; public readonly int FastEmaPeriod = 12; public readonly int SlowEmaPeriod = 26; /// /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized. /// public override void Initialize() { SetStartDate(2004, 01, 01); SetEndDate(2015, 01, 01); AddSecurity(SecurityType.Equity, _symbol, Resolution.Daily); // define our daily macd(12,26) with a 9 day signal _macd = MACD(_symbol, FastEmaPeriod, SlowEmaPeriod, 9, MovingAverageType.Exponential, Resolution.Daily); } /// /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. /// /// TradeBars IDictionary object with your stock data public void OnData(TradeBars data) { // wait for our indicator to be ready if (!_macd.IsReady) return; var holding = Portfolio[_symbol]; var signalDeltaPercent = (_macd - _macd.Signal) / _macd.Fast; var tolerance = 0.0025m; // if our macd is greater than our signal, then let's go long if (holding.Quantity <= 0 && signalDeltaPercent > tolerance) { // 1. Call EmitInsights with insights created in correct direction, here we're going long // The EmitInsights method can accept multiple insights separated by commas EmitInsights( // Creates an insight for our symbol, predicting that it will move up within the fast ema period number of days Insight.Price(_symbol, TimeSpan.FromDays(FastEmaPeriod), InsightDirection.Up) ); // longterm says buy as well SetHoldings(_symbol, 1.0); } // if our macd is less than our signal, then let's go short else if (holding.Quantity >= 0 && signalDeltaPercent < -tolerance) { // 1. Call EmitInsights with insights created in correct direction, here we're going short // The EmitInsights method can accept multiple insights separated by commas EmitInsights( // Creates an insight for our symbol, predicting that it will move down within the fast ema period number of days Insight.Price(_symbol, TimeSpan.FromDays(FastEmaPeriod), InsightDirection.Down) ); // shortterm says sell as well SetHoldings(_symbol, -1.0); } // if we wanted to liquidate our positions // 1. Call EmitInsights with insights create in the correct direction -- Flat // EmitInsights( // Creates an insight for our symbol, predicting that it will move down or up within the fast ema period number of days, depending on our current position // Insight.Price(_symbol, TimeSpan.FromDays(FastEmaPeriod), InsightDirection.Flat); // ); // Liquidate(); // plot both lines Plot("MACD", _macd, _macd.Signal); Plot(_symbol, "Open", data[_symbol].Open); Plot(_symbol, _macd.Fast, _macd.Slow); } /// /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm. /// public bool CanRunLocally { get; } = true; /// /// This is used by the regression test system to indicate which languages this algorithm is written in. /// public Language[] Languages { get; } = { Language.CSharp, Language.Python }; /// /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm /// public Dictionary ExpectedStatistics => new Dictionary { {"Total Trades", "85"}, {"Average Win", "4.85%"}, {"Average Loss", "-4.21%"}, {"Compounding Annual Return", "-3.105%"}, {"Drawdown", "52.900%"}, {"Expectancy", "-0.053"}, {"Net Profit", "-29.335%"}, {"Sharpe Ratio", "-0.084"}, {"Loss Rate", "56%"}, {"Win Rate", "44%"}, {"Profit-Loss Ratio", "1.15"}, {"Alpha", "-0.006"}, {"Beta", "-0.093"}, {"Annual Standard Deviation", "0.181"}, {"Annual Variance", "0.033"}, {"Information Ratio", "-0.396"}, {"Tracking Error", "0.278"}, {"Treynor Ratio", "0.164"}, {"Total Fees", "$755.20"}, {"Total Insights Generated", "85"}, {"Total Insights Closed", "85"}, {"Total Insights Analysis Completed", "85"}, {"Long Insight Count", "42"}, {"Short Insight Count", "43"}, {"Long/Short Ratio", "97.67%"}, {"Estimated Monthly Alpha Value", "$-607698.1"}, {"Total Accumulated Estimated Alpha Value", "$-81395260"}, {"Mean Population Estimated Insight Value", "$-957591.3"}, {"Mean Population Direction", "50.5882%"}, {"Mean Population Magnitude", "0%"}, {"Rolling Averaged Population Direction", "46.5677%"}, {"Rolling Averaged Population Magnitude", "0%"} }; } }