/* * 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.Text; using QuantConnect.Data; using QuantConnect.Data.UniverseSelection; using QuantConnect.Interfaces; namespace QuantConnect.Algorithm.CSharp { /// /// 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 /// /// /// /// public class DropboxUniverseSelectionAlgorithm : QCAlgorithm//, IRegressionAlgorithmDefinition { // Regression algorithm disabled due to file missing from dropbox // the changes from the previous universe selection private SecurityChanges _changes = SecurityChanges.None; // only used in backtest for caching the file results private readonly Dictionary> _backtestSymbolsPerDay = new Dictionary>(); /// /// 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() { // 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 => { // handle live mode file format if (LiveMode) { // fetch the file from dropbox var file = Download(@"https://www.dropbox.com/s/2az14r5xbx4w5j6/daily-stock-picker-live.csv?dl=1"); // 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) { // No need for headers for authorization with dropbox, these two lines are for example purposes var byteKey = Encoding.ASCII.GetBytes($"UserName:Password"); // The headers must be passed to the Download method as list of key/value pair. var headers = new List> { new KeyValuePair("Authorization", $"Basic ({Convert.ToBase64String(byteKey)})") }; var file = Download(@"https://www.dropbox.com/s/rmiiktz0ntpff3a/daily-stock-picker-backtest.csv?dl=1", headers); // 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 result; if (_backtestSymbolsPerDay.TryGetValue(dateTime.Date, out result)) { return result; } return Universe.Unchanged; }); } /// /// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event /// /// /// TradeBars bars = slice.Bars; /// Ticks ticks = slice.Ticks; /// TradeBar spy = slice["SPY"]; /// List{Tick} aaplTicks = slice["AAPL"] /// Quandl oil = slice["OIL"] /// dynamic anySymbol = slice[symbol]; /// DataDictionary{Quandl} allQuandlData = slice.Get{Quand} /// Quandl oil = slice.Get{Quandl}("OIL") /// /// The current slice of data keyed by symbol string public override void OnData(Slice slice) { if (slice.Bars.Count == 0) return; if (_changes == SecurityChanges.None) return; // start fresh Liquidate(); var percentage = 1m/slice.Bars.Count; foreach (var tradeBar in slice.Bars.Values) { SetHoldings(tradeBar.Symbol, percentage); } // reset changes _changes = SecurityChanges.None; } /// /// Event fired each time the we add/remove securities from the data feed /// /// public override void OnSecuritiesChanged(SecurityChanges changes) { // each time our securities change we'll be notified here _changes = changes; } /// /// 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", "66"}, {"Average Win", "1.06%"}, {"Average Loss", "-0.50%"}, {"Compounding Annual Return", "18.511%"}, {"Drawdown", "7.100%"}, {"Expectancy", "0.810"}, {"Net Profit", "18.511%"}, {"Sharpe Ratio", "1.439"}, {"Loss Rate", "42%"}, {"Win Rate", "58%"}, {"Profit-Loss Ratio", "2.12"}, {"Alpha", "-0.011"}, {"Beta", "0.673"}, {"Annual Standard Deviation", "0.1"}, {"Annual Variance", "0.01"}, {"Information Ratio", "-1.065"}, {"Tracking Error", "0.081"}, {"Treynor Ratio", "0.213"}, {"Total Fees", "$193.75"} }; } }