Overall Statistics |
Total Trades 110 Average Win 0.46% Average Loss -0.57% Compounding Annual Return -72.769% Drawdown 8.700% Expectancy -0.206 Net Profit -6.492% Sharpe Ratio -3.551 Loss Rate 56% Win Rate 44% Profit-Loss Ratio 0.82 Alpha 0 Beta 0 Annual Standard Deviation 0.286 Annual Variance 0.082 Information Ratio 0 Tracking Error 0 Treynor Ratio 0 Total Fees $1078.56 |
/* * 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 System.Threading.Tasks; using QuantConnect.Data.Market; using QuantConnect.Data.UniverseSelection; using Newtonsoft.Json; 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 { public DateTime current_date; // 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.Minute; // set our start and end for backtest mode SetStartDate(2012, 7, 15); SetEndDate(2012, 8, 02); // define a new custom universe that will trigger each day at midnight AddUniverse("my-dropbox-universe", Resolution.Minute, 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/kzo2kdu2v7q7qc1/dataforqc.csv?dl=1"; var url = LiveMode ? liveUrl : backtestUrl; using (var client = new WebClient()) { // handle live mode file format n 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; //foreach (var symbol in symbols){ // Console.Write(Time.ToString()+ " " +symbol); //} } } // 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 (Time.TimeOfDay.TotalHours > 15.9){ Liquidate(); } if (_changes == SecurityChanges.None || current_date == Time.Date) return; //var timeout = Task.Delay(TimeSpan.FromSeconds(20)); //var work = Task.Run(() => { // start fresh var percentage = 1m/data.Count; foreach (var tradeBar in data.Values) { SetHoldings(tradeBar.Symbol, percentage); } // reset changes _changes = SecurityChanges.None; current_date = Time.Date; //}); //Task.WaitAny(timeout, work); } public override void OnEndOfDay(string symbol) { } /// <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; } public static void SetBlackList(params string[] tickers) { var joined = string.Join(",", tickers); using (var wc = new WebClient()) { wc.DownloadString("http://signalbackend.azurewebsites.net/Signal/SetBlackList?tickers=" + joined); } } public static List<SignalStock> GetSignal(DateTime date, int count = 10) { using (var wc = new WebClient()) { var str = wc.DownloadString(string.Format("http://signalbackend.azurewebsites.net/Signal/Signal?year={0}&month={1}&day={2}&count={3}", date.Year, date.Month, date.Day, count)); return JsonConvert.DeserializeObject<List<SignalStock>>(str); } } } public class SignalStock { public string Ticker; public List<InsiderTransaction> Transactions; public double StockSignal; public StockDetails Details; public InsiderTransaction MainTransaction; } public class InsiderTransaction { public int? ExpertRank { get; set; } public DateTime Date { get; set; } public string OperationRatingString { get; set; } public string InsiderOperationType { get; set; } public string Ticker { get; set; } public string StockDisplayName { get; set; } public bool IsDirector { get; set; } public bool IsOfficer { get; set; } public string OfficerName { get; set; } public bool IsTenPercentOwner { get; set; } public decimal? Value { get; set; } public bool IsInformative { get; set; } public long? MarketCap { get; set; } public long InsiderOperationId { get; set; } public string InsiderName { get; set; } public double Signal { get; set; } } public class StockDetails { public string yLow; public string ticker { get; set; } public string pe { get; set; } public string marketCap { get; set; } public string openPrice { get; set; } public string eps { get; set; } public string divPerYield { get; set; } public string fiscalDiv { get; set; } public string beta { get; set; } public string shares { get; set; } public string market { get; set; } public string instOwn { get; set; } public string low { get; set; } public string high { get; set; } public string price { get; set; } public string yHigh { get; set; } public string range { get; set; } public string changeAmount { get; set; } public string changePercent { get; set; } public string average { get; set; } public string volume { get; set; } public string volumeAndAvg { get; set; } public string prevClose { get; set; } public string bid { get; set; } public string ask { get; set; } public string oneYearTargetEst { get; set; } public DateTime? nextEarningDate { get; set; } public string daysRange { get; set; } public string range52Weeks { get; set; } public string low52Weeks { get; set; } public string high52Weeks { get; set; } public string avgVol3Months { get; set; } } }