Overall Statistics |
Total Trades 1 Average Win 8468.46% Average Loss 0.00% Annual Return 2952.233% Drawdown 67.900% Expectancy 0.000 Net Profit 8468.460% Sharpe Ratio 1.484 Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha 8.004 Beta 5.843 Annual Standard Deviation 5.978 Annual Variance 35.742 Information Ratio 1.462 Tracking Error 5.966 Treynor Ratio 1.518 |
using System; using System.Collections; using System.Collections.Generic; using QuantConnect.Securities; using QuantConnect.Models; namespace QuantConnect { /// <summary> /// Custom Data Type: Bitcoin data from Quandl. /// http://www.quandl.com/help/api-for-bitcoin-data /// </summary> public class Bitcoin : BaseData { //Set the defaults: public decimal Open = 0; public decimal High = 0; public decimal Low = 0; public decimal Close = 0; public decimal VolumeBTC = 0; public decimal VolumeUSD = 0; public decimal WeightedPrice = 0; /// <summary> /// 1. DEFAULT CONSTRUCTOR: Custom data types need a default constructor. /// We search for a default constructor so please provide one here. It won't be used for data, just to generate the "Factory". /// </summary> public Bitcoin() { this.Symbol = "BTC"; } /// <summary> /// 2. RETURN THE STRING URL SOURCE LOCATION FOR YOUR DATA: /// This is a powerful and dynamic select source file method. If you have a large dataset, 10+mb we recommend you break it into smaller files. E.g. One zip per year. /// We can accept raw text or ZIP files. We read the file extension to determine if it is a zip file. /// </summary> /// <param name="config">Subscription data, symbol name, data type</param> /// <param name="date">Current date we're requesting. This allows you to break up the data source into daily files.</param> /// <param name="datafeed">Datafeed type: Backtesting or the Live data broker who will provide live data. You can specify a different source for live trading! </param> /// <returns>string URL end point.</returns> public override string GetSource(SubscriptionDataConfig config, DateTime date, DataFeedEndpoint datafeed) { switch (datafeed) { //Backtesting Data Source: Example of a data source which varies by day (commented out) default: case DataFeedEndpoint.Backtesting: //return "http://my-ftp-server.com/futures-data-" + date.ToString("Ymd") + ".zip"; // OR simply return a fixed small data file. Large files will slow down your backtest return "http://www.quandl.com/api/v1/datasets/BITCOIN/BITSTAMPUSD.csv?sort_order=asc"; case DataFeedEndpoint.LiveTrading: //Alternative live socket data source for live trading (soon)/ return "...."; } } /// <summary> /// 3. READER METHOD: Read 1 line from data source and convert it into Object. /// Each line of the CSV File is presented in here. The backend downloads your file, loads it into memory and then line by line /// feeds it into your algorithm /// </summary> /// <param name="line">string line from the data source file submitted above</param> /// <param name="config">Subscription data, symbol name, data type</param> /// <param name="date">Current date we're requesting. This allows you to break up the data source into daily files.</param> /// <param name="datafeed">Datafeed type - Backtesting or LiveTrading</param> /// <returns>New Bitcoin Object which extends BaseData.</returns> public override BaseData Reader(SubscriptionDataConfig config, string line, DateTime date, DataFeedEndpoint datafeed) { //New Bitcoin object Bitcoin coin = new Bitcoin(); try { //Example File Format: //Date, Open High Low Close Volume (BTC) Volume (Currency) Weighted Price //2011-09-13 5.8 6.0 5.65 5.97 58.37138238, 346.0973893944 5.929230648356 string[] data = line.Split(','); coin.Time = DateTime.Parse(data[0]); coin.Open = Convert.ToDecimal(data[1]); coin.High = Convert.ToDecimal(data[2]); coin.Low = Convert.ToDecimal(data[3]); coin.Close = Convert.ToDecimal(data[4]); coin.VolumeBTC = Convert.ToDecimal(data[5]); coin.VolumeUSD = Convert.ToDecimal(data[6]); coin.WeightedPrice = Convert.ToDecimal(data[7]); coin.Symbol = "BTC"; coin.Value = coin.Close; } catch { /* Do nothing, skip first title row */ } return coin; } } }
using System; using System.Collections; using System.Collections.Generic; using QuantConnect.Securities; using QuantConnect.Models; namespace QuantConnect { /// <summary> /// 3.0 CUSTOM DATA SOURCE: USE YOUR OWN MARKET DATA (OPTIONS, FOREX, FUTURES, DERIVATIVES etc). /// /// The new QuantConnect Lean Backtesting Engine is incredibly flexible and allows you to define your own data source. /// /// This includes any data source which has a TIME and VALUE. These are the *only* requirements. To demonstrate this we're loading /// in "Bitcoin" data. This by itself isn't special, the cool part is next: /// /// We load the "Bitcoin" data as a tradable security we're calling "BTC". /// /// </summary> public class CustomDataSourceAlgorithm : QCAlgorithm { public override void Initialize() { //Bitcoin data we have is within these days: SetStartDate(2011, 9, 13); SetEndDate(DateTime.Now.Date.AddDays(-1)); //Set the cash for the strategy: SetCash(100000); //Define the symbol and "type" of our generic data: AddData<Bitcoin>("BTC"); } /// <summary> /// Event Handler for Bitcoin Data Events: These Bitcoin objects are created from our /// "Bitcoin" type below and fired into this event handler. /// </summary> /// <param name="data">One(1) Bitcoin Object, streamed into our algorithm synchronised in time with our other data streams</param> public void OnData(Bitcoin data) { //If we don't have any Bitcoin "SHARES" -- invest" if (!Portfolio.Invested) { //Bitcoin used as a tradable asset, like stocks, futures etc. if (data.Close != 0) { Order("BTC", (Portfolio.Cash / Math.Abs(data.Close + 1))); } Console.WriteLine("Buying BTC 'Shares': BTC: " + data.Close); } //Console.WriteLine("Time: " + Time.ToLongDateString() + " " + Time.ToLongTimeString() + data.Close.ToString()); } } }