Overall Statistics |
Total Trades 225 Average Win 0.75% Average Loss -0.70% Compounding Annual Return 4.255% Drawdown 23.700% Expectancy 0.164 Net Profit 12.927% Sharpe Ratio 0.38 Loss Rate 44% Win Rate 56% Profit-Loss Ratio 1.08 Alpha 0.045 Beta 0.036 Annual Standard Deviation 0.132 Annual Variance 0.017 Information Ratio -0.546 Tracking Error 0.178 Treynor Ratio 1.388 Total Fees $382.96 |
using System; using System.Collections.Generic; using System.Linq; using QuantConnect.Data.Market; using QuantConnect.Data.UniverseSelection; namespace QuantConnect.Algorithm.CSharp { // In this algorithm we show how you can easily define a // universe using our coarse selection data. This data includes // a few properties, including the daily DollarVolume, the daily Volume // and also the daily closing price via the Value property. public class CoarseFundamentalTop5Algorithm : QCAlgorithm { // initialize our security changes to nothing SecurityChanges _changes = SecurityChanges.None; public override void Initialize() { // this sets the resolution for securities added via universe selection UniverseSettings.Resolution = Resolution.Minute; SetStartDate(2013, 1, 1); SetEndDate(2015, 12, 1); SetCash(50000); // this add universe method accepts a single parameter that is a function that // accepts an IEnumerable<CoarseFundamental> and returns IEnumerable<Symbol> AddUniverse(coarse => { // Properties available on the CoarseFundamental type 'stock' // stock.DollarVollume // stock.Value (daily close) // stock.Volume // stock.Market // return (from stock in coarse orderby stock.DollarVolume descending select stock.Symbol).Take(5); }); } // sort the data by daily dollar volume and take the top 5 symbols public static IEnumerable<Symbol> CoarseSelectionFunction(IEnumerable<CoarseFundamental> coarse) { // sort descending by daily dollar volume var sortedByDollarVolume = coarse.OrderByDescending(x => x.DollarVolume); // take the top 5 entries from our sorted collection var top5 = sortedByDollarVolume.Take(5); // we need to return only the symbols return top5.Select(x => x.Symbol); } //Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol. public void OnData(TradeBars data) { // if we have no changes, do nothing if (_changes == SecurityChanges.None) return; // liquidate removed securities foreach (var security in _changes.RemovedSecurities) { if (security.Invested) { Liquidate(security.Symbol); } } // we want 25% allocation in each security in our universe (total of 150% invested) foreach (var security in _changes.AddedSecurities) { SetHoldings(security.Symbol, 0.25m); } // reset our changes _changes = SecurityChanges.None; } // this event fires whenever we have changes to our universe public override void OnSecuritiesChanged(SecurityChanges changes) { _changes = changes; } } }