/* * 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 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 BaseData custom data system in combination with the AddUniverse{T} method. /// AddUniverse{T} requires a function that will return the symbols to be traded. /// /// /// /// public class DropboxBaseDataUniverseSelectionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { // the changes from the previous universe selection private SecurityChanges _changes = SecurityChanges.None; /// /// 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() { UniverseSettings.Resolution = Resolution.Daily; SetStartDate(2017, 07, 04); SetEndDate(2018, 07, 04); AddUniverse("my-stock-data-source", stockDataSource => { return stockDataSource.SelectMany(x => x.Symbols); }); } /// /// 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; } /// /// Our custom data type that defines where to get and how to read our backtest and live data. /// class StockDataSource : BaseData { private const string LiveUrl = @"https://www.dropbox.com/s/2l73mu97gcehmh7/daily-stock-picker-live.csv?dl=1"; private const string BacktestUrl = @"https://www.dropbox.com/s/ae1couew5ir3z9y/daily-stock-picker-backtest.csv?dl=1"; /// /// The symbols to be selected /// public List Symbols { get; set; } /// /// Required default constructor /// public StockDataSource() { // initialize our list to empty Symbols = new List(); } /// /// Return the URL string source of the file. This will be converted to a stream /// /// Configuration object /// Date of this source file /// true if we're in live mode, false for backtesting mode /// String URL of source file. public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode) { var url = isLiveMode ? LiveUrl : BacktestUrl; return new SubscriptionDataSource(url, SubscriptionTransportMedium.RemoteFile); } /// /// Reader converts each line of the data source into BaseData objects. Each data type creates its own factory method, and returns a new instance of the object /// each time it is called. The returned object is assumed to be time stamped in the config.ExchangeTimeZone. /// /// Subscription data config setup object /// Line of the source document /// Date of the requested data /// true if we're in live mode, false for backtesting mode /// Instance of the T:BaseData object generated by this line of the CSV public override BaseData Reader(SubscriptionDataConfig config, string line, DateTime date, bool isLiveMode) { try { // create a new StockDataSource and set the symbol using config.Symbol var stocks = new StockDataSource {Symbol = config.Symbol}; // break our line into csv pieces var csv = line.ToCsv(); if (isLiveMode) { // our live mode format does not have a date in the first column, so use date parameter stocks.Time = date; stocks.Symbols.AddRange(csv); } else { // our backtest mode format has the first column as date, parse it stocks.Time = DateTime.ParseExact(csv[0], "yyyyMMdd", null); // any following comma separated values are symbols, save them off stocks.Symbols.AddRange(csv.Skip(1)); } return stocks; } // return null if we encounter any errors catch { return null; } } } /// /// 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", "6441"}, {"Average Win", "0.07%"}, {"Average Loss", "-0.07%"}, {"Compounding Annual Return", "13.331%"}, {"Drawdown", "10.700%"}, {"Expectancy", "0.061"}, {"Net Profit", "13.331%"}, {"Sharpe Ratio", "0.963"}, {"Probabilistic Sharpe Ratio", "46.232%"}, {"Loss Rate", "46%"}, {"Win Rate", "54%"}, {"Profit-Loss Ratio", "0.97"}, {"Alpha", "0.124"}, {"Beta", "-0.066"}, {"Annual Standard Deviation", "0.121"}, {"Annual Variance", "0.015"}, {"Information Ratio", "0.006"}, {"Tracking Error", "0.171"}, {"Treynor Ratio", "-1.761"}, {"Total Fees", "$8669.41"}, {"Fitness Score", "0.675"}, {"Kelly Criterion Estimate", "0"}, {"Kelly Criterion Probability Value", "0"}, {"Sortino Ratio", "1.127"}, {"Return Over Maximum Drawdown", "1.246"}, {"Portfolio Turnover", "1.64"}, {"Total Insights Generated", "0"}, {"Total Insights Closed", "0"}, {"Total Insights Analysis Completed", "0"}, {"Long Insight Count", "0"}, {"Short Insight Count", "0"}, {"Long/Short Ratio", "100%"}, {"Estimated Monthly Alpha Value", "$0"}, {"Total Accumulated Estimated Alpha Value", "$0"}, {"Mean Population Estimated Insight Value", "$0"}, {"Mean Population Direction", "0%"}, {"Mean Population Magnitude", "0%"}, {"Rolling Averaged Population Direction", "0%"}, {"Rolling Averaged Population Magnitude", "0%"}, {"OrderListHash", "-75671425"} }; } }