Overall Statistics |
Total Trades 67 Average Win 3.48% Average Loss -4.67% Compounding Annual Return 9.792% Drawdown 20.500% Expectancy 0.269 Net Profit 45.369% Sharpe Ratio 0.71 Loss Rate 27% Win Rate 73% Profit-Loss Ratio 0.75 Alpha 0.168 Beta -3.158 Annual Standard Deviation 0.147 Annual Variance 0.022 Information Ratio 0.574 Tracking Error 0.147 Treynor Ratio -0.033 Total Fees $302.26 |
/* * 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 QuantConnect.Data.Market; namespace QuantConnect.Algorithm.CSharp { /// <summary> /// Algorithm demonstrating custom charting support in QuantConnect. /// The entire charting system of quantconnect is adaptable. You can adjust it to draw whatever you'd like. /// Charts can be stacked, or overlayed on each other. Series can be candles, lines or scatter plots. /// Even the default behaviours of QuantConnect can be overridden. /// </summary> /// <meta name="tag" content="charting" /> /// <meta name="tag" content="adding charts" /> /// <meta name="tag" content="series types" /> /// <meta name="tag" content="plotting indicators" /> public class CustomChartingAlgorithm : QCAlgorithm { private decimal _fastMa; private decimal _slowMa; private decimal _lastPrice; private DateTime _resample; private TimeSpan _resamplePeriod; private readonly DateTime _startDate = new DateTime(2010, 3, 3); private readonly DateTime _endDate = new DateTime(2014, 3, 3); /// <summary> /// Called at the start of your algorithm to setup your requirements: /// </summary> public override void Initialize() { //Set the date range you want to run your algorithm: SetStartDate(_startDate); SetEndDate(_endDate); //Set the starting cash for your strategy: SetCash(100000); //Add any stocks you'd like to analyse, and set the resolution: // Find more symbols here: http://quantconnect.com/data AddSecurity(SecurityType.Equity, "SPY"); //Chart - Master Container for the Chart: var stockPlot = new Chart("Trade Plot"); //On the Trade Plotter Chart we want 3 series: trades and price: var buyOrders = new Series("Buy", SeriesType.Scatter, 0); var sellOrders = new Series("Sell", SeriesType.Scatter, 0); var assetPrice = new Series("Price", SeriesType.Line, 0); stockPlot.AddSeries(buyOrders); stockPlot.AddSeries(sellOrders); stockPlot.AddSeries(assetPrice); AddChart(stockPlot); var avgCross = new Chart("Strategy Equity"); var fastMa = new Series("FastMA", SeriesType.Line, 1); var slowMa = new Series("SlowMA", SeriesType.Line, 1); avgCross.AddSeries(fastMa); avgCross.AddSeries(slowMa); AddChart(avgCross); _resamplePeriod = TimeSpan.FromMinutes((_endDate - _startDate).TotalMinutes / 2000); } /// <summary> /// OnEndOfDay Event Handler - At the end of each trading day we fire this code. /// To avoid flooding, we recommend running your plotting at the end of each day. /// </summary> public override void OnEndOfDay() { //Log the end of day prices: Plot("Trade Plot", "Price", _lastPrice); } /// <summary> /// On receiving new tradebar data it will be passed into this function. The general pattern is: /// "public void OnData( CustomType name ) {...s" /// </summary> /// <param name="data">TradeBars data type synchronized and pushed into this function. The tradebars are grouped in a dictionary.</param> public void OnData(TradeBars data) { _lastPrice = data["SPY"].Close; if (_fastMa == 0) _fastMa = _lastPrice; if (_slowMa == 0) _slowMa = _lastPrice; _fastMa = (0.01m * _lastPrice) + (0.99m * _fastMa); _slowMa = (0.001m * _lastPrice) + (0.999m * _slowMa); if (Time > _resample) { _resample = Time.Add(_resamplePeriod); Plot("Strategy Equity", "FastMA", _fastMa); Plot("Strategy Equity", "SlowMA", _slowMa); } //On the 5th days when not invested buy: if (!Portfolio.Invested && Time.Day % 13 == 0) { Order("SPY", (int)(Portfolio.MarginRemaining / data["SPY"].Close)); Plot("Trade Plot", "Buy", _lastPrice); } else if (Time.Day % 21 == 0 && Portfolio.Invested) { Plot("Trade Plot", "Sell", _lastPrice); Liquidate(); } } } }