Overall Statistics
Total Trades
19
Average Win
0.38%
Average Loss
-0.18%
Compounding Annual Return
6.849%
Drawdown
3.800%
Expectancy
0.392
Net Profit
0.343%
Sharpe Ratio
0.745
Loss Rate
56%
Win Rate
44%
Profit-Loss Ratio
2.13
Alpha
0.083
Beta
0.078
Annual Standard Deviation
0.081
Annual Variance
0.007
Information Ratio
1.744
Tracking Error
0.199
Treynor Ratio
0.774
Total Fees
$23.52
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using System.Globalization;
using System.Text;
using System.Threading.Tasks;
using QuantConnect.Data;
using QuantConnect.Data.Consolidators;

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;
        
        TradeBar open;
        // we'll set the close at the end of each day
        TradeBar close;

        public override void Initialize()
        {
        	// this sets the resolution for securities added via universe selection
            UniverseSettings.Resolution = Resolution.Minute;

            SetStartDate(2016, 2, 1);
            SetEndDate(DateTime.Now.Date.AddDays(-1));
            SetCash(5000);

            // this add universe method accepts a single parameter that is a function that
            // accepts an IEnumerable<CoarseFundamental> and returns IEnumerable<Symbol>
            AddUniverse(CoarseSelectionFunction);
            
            
        }

        // 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.OrderBy(x => x.Price);
            // take the top 5 entries from our sorted collection
            //var top5 = sortedByDollarVolume.Take(1);
            // we need to return only the symbols
            //return top5.Select(x => x.Symbol);

            return (from stock in coarse
            	orderby stock.Price descending
                where stock.Price < 5
            	select stock.Symbol).Take(1);
        }
        

        //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);
                Log("BUY  >> " + security.Symbol + " " + security.Price);
            }
            
            // reset our changes
            _changes = SecurityChanges.None;
        }

        // this event fires whenever we have changes to our universe
        public override void OnSecuritiesChanged(SecurityChanges changes)
        {
            _changes = changes;
        }
    }
}