Overall Statistics
Total Trades
149
Average Win
1.41%
Average Loss
-1.90%
Compounding Annual Return
7.385%
Drawdown
18.400%
Expectancy
0.417
Net Profit
93.739%
Sharpe Ratio
0.658
Loss Rate
19%
Win Rate
81%
Profit-Loss Ratio
0.74
Alpha
0.047
Beta
0.275
Annual Standard Deviation
0.096
Annual Variance
0.009
Information Ratio
0.022
Tracking Error
0.158
Treynor Ratio
0.229
Total Fees
$555.49
using System;
using System.Collections.Concurrent;
namespace QuantConnect 
{   
    public class BasicTemplateAlgorithm : QCAlgorithm
    {
    	SecurityChanges _changes = SecurityChanges.None;
    	public const int count = 100;
    	public int CurrentMonth = 0;
    	private readonly ConcurrentDictionary<Symbol, SelectionData> _symbolsData = new ConcurrentDictionary<Symbol, SelectionData>();
        public override void Initialize() 
        {
        	UniverseSettings.Leverage = 2.0m;
			UniverseSettings.Resolution = Resolution.Daily;
            SetStartDate(2008, 1, 1);         
            SetEndDate(DateTime.Now);
            SetCash(100*1000);
            AddUniverse( coarse =>
            		{
            			return
            			( 	
            				from cf in coarse
            				let avg = _symbolsData.GetOrAdd(cf.Symbol, sym => new SelectionData())
							where cf.Price > 10.0m
							where avg.Update(cf.EndTime,cf.Price)
            				orderby cf.DollarVolume descending
            				select cf.Symbol
            			).Take(count);
            		}
            	);
        }
		
        public void OnData(TradeBars data) 
        {
			if(CurrentMonth != Time.Month)
			{	foreach(var symbol in Portfolio.Keys)
				{
					if(_symbolsData[symbol].Months < 6)
					{
						_symbolsData[symbol].Months += 1;
					}else
					{
						_symbolsData[symbol].Months = 0;
						Liquidate(symbol);	
					}
				}
				CurrentMonth = Time.Month;

				IEnumerable<Symbol> highVolatile = 	(	from sym in data.Keys 
														let info = _symbolsData[sym]
														orderby info.volatility
														select sym).Take(count/10);
				IEnumerable<Symbol> highPerforming = (	from sym in highVolatile
														let info = _symbolsData[sym]
														orderby info.momentum descending
														select sym).Take(1);
				// IEnumerable<Symbol> lowPerforming = (	from sym in highVolatile
				// 										let info = _symbolsData[sym]
				// 										orderby info.momentum
				// 										select sym).Take(1);
				foreach(var symbol in highPerforming)
				{
					if(data[symbol].Close > 10.0m)
					{
						SetHoldings(symbol,(decimal)1/6);
						_symbolsData[symbol].Months = 1;
					}
				}
				// foreach(var symbol in lowPerforming)
				// {
				// 	SetHoldings(symbol,-(decimal)1/18);
				// 	_symbolsData[symbol].Months = 1;
				// }
			}
        }
        public override void OnSecuritiesChanged(SecurityChanges changes)
        {
            _changes = changes;
        }
    }
}                        
using System;
using System.Collections.Concurrent;
using System.Linq;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Indicators;
namespace QuantConnect {
 	public class SelectionData
	{
		public int numberOfDay = 0;
		public struct timePrice
		{
			public DateTime time;
			public decimal price;
			public timePrice(DateTime _time, decimal _price)
			{
				time = _time;
				price = _price;
			}
		}
		public Queue<timePrice> weeksPrices = new Queue<timePrice>();
		public StandardDeviation volatility;
		public readonly Momentum momentum;
		private int months;
	
		public int Months
		{
			get{ return months;}
			set{ months = value;}
		}
		public bool Update(DateTime time, decimal price)
		{
			weeksPrices.Enqueue(new timePrice(time,price));
			if(numberOfDay >= 7)
			{
				timePrice previousDay = weeksPrices.Dequeue();
				return momentum.Update(previousDay.time,previousDay.price) && 
				volatility.Update(previousDay.time,previousDay.price);
			}else
			{
				numberOfDay++;
				return false;
			}
		}
		public SelectionData()
		{
			volatility = new StandardDeviation(180);
			momentum = new Momentum(180);
		}
	}
}