Overall Statistics |
Total Trades 49 Average Win 1.59% Average Loss -1.06% Compounding Annual Return 21.266% Drawdown 8.200% Expectancy 0.633 Net Profit 21.279% Sharpe Ratio 1.361 Loss Rate 35% Win Rate 65% Profit-Loss Ratio 1.50 Alpha 0.178 Beta -0.07 Annual Standard Deviation 0.12 Annual Variance 0.014 Information Ratio -0.296 Tracking Error 0.161 Treynor Ratio -2.335 Total Fees $234.16 |
/* * 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 System.Linq; using System.Net; using QuantConnect.Data.Market; using QuantConnect.Data.UniverseSelection; namespace QuantConnect.Algorithm.CSharp { /// <summary> /// In this algortihm we show how you can easily use the universe selection feature to fetch symbols /// to be traded using the AddUniverse method. This method accepts a function that will return the /// desired current set of symbols. Return Universe.Unchanged if no universe changes should be made /// </summary> public class DropboxUniverseSelectionAlgorithm : QCAlgorithm { // the changes from the previous universe selection private SecurityChanges _changes = SecurityChanges.None; // only used in backtest for caching the file results private readonly Dictionary<DateTime, List<string>> _backtestSymbolsPerDay = new Dictionary<DateTime, List<string>>(); /// <summary> /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized. /// </summary> /// <seealso cref="QCAlgorithm.SetStartDate(System.DateTime)"/> /// <seealso cref="QCAlgorithm.SetEndDate(System.DateTime)"/> /// <seealso cref="QCAlgorithm.SetCash(decimal)"/> public override void Initialize() { // this sets the resolution for data subscriptions added by our universe UniverseSettings.Resolution = Resolution.Daily; // set our start and end for backtest mode SetStartDate(2013, 01, 01); SetEndDate(2013, 12, 31); // define a new custom universe that will trigger each day at midnight AddUniverse("my-dropbox-universe", Resolution.Daily, dateTime => { const string liveUrl = @"https://www.dropbox.com/s/2az14r5xbx4w5j6/daily-stock-picker-live.csv?dl=1"; const string backtestUrl = @"https://www.dropbox.com/s/rmiiktz0ntpff3a/daily-stock-picker-backtest.csv?dl=1"; var url = LiveMode ? liveUrl : backtestUrl; using (var client = new WebClient()) { // handle live mode file format if (LiveMode) { // fetch the file from dropbox var file = client.DownloadString(url); // if we have a file for today, break apart by commas and return symbols if (file.Length > 0) return file.ToCsv(); // no symbol today, leave universe unchanged return Universe.Unchanged; } // backtest - first cache the entire file if (_backtestSymbolsPerDay.Count == 0) { // fetch the file from dropbox only if we haven't cached the result already var file = client.DownloadString(url); // split the file into lines and add to our cache foreach (var line in file.Split(new[] { '\n', '\r' }, StringSplitOptions.RemoveEmptyEntries)) { var csv = line.ToCsv(); var date = DateTime.ParseExact(csv[0], "yyyyMMdd", null); var symbols = csv.Skip(1).ToList(); _backtestSymbolsPerDay[date] = symbols; } } // if we have symbols for this date return them, else specify Universe.Unchanged List<string> result; if (_backtestSymbolsPerDay.TryGetValue(dateTime.Date, out result)) { return result; } return Universe.Unchanged; } }); } /// <summary> /// Stock data event handler /// </summary> /// <param name="data"></param> public void OnData(TradeBars data) { if (_changes == SecurityChanges.None) return; // start fresh Liquidate(); var percentage = 1m/data.Count; foreach (var tradeBar in data.Values) { SetHoldings(tradeBar.Symbol, percentage); } // reset changes _changes = SecurityChanges.None; } /// <summary> /// Event fired each time the we add/remove securities from the data feed /// </summary> /// <param name="changes"></param> public override void OnSecuritiesChanged(SecurityChanges changes) { // each time our securities change we'll be notified here _changes = changes; } } }