Overall Statistics
Total Trades
4372
Average Win
0.16%
Average Loss
-0.13%
Compounding Annual Return
-17.757%
Drawdown
19.200%
Expectancy
-0.065
Net Profit
-17.757%
Sharpe Ratio
-1.093
Loss Rate
59%
Win Rate
41%
Profit-Loss Ratio
1.31
Alpha
0.481
Beta
-33.652
Annual Standard Deviation
0.163
Annual Variance
0.027
Information Ratio
-1.212
Tracking Error
0.163
Treynor Ratio
0.005
Total Fees
$10506.52
using System.Collections.Concurrent;

namespace QuantConnect.Algorithm.CSharp
{
    public class RsiCrossUniverseSelectionAlgorithm : QCAlgorithm
    {
        // holds our coarse fundamental indicators by symbol
        private readonly ConcurrentDictionary<Symbol, SelectionData> _averages = new ConcurrentDictionary<Symbol, SelectionData>();
		private const int Count = 10;
        private SecurityChanges _changes = SecurityChanges.None;
        
        public override void Initialize()
        {
            UniverseSettings.Leverage = 2.0m;
            UniverseSettings.Resolution = Resolution.Daily;

            SetStartDate(2018, 1, 1);
            SetEndDate(2019, 1, 1);
            SetCash(100000);

            AddUniverse(coarse =>
            {
                return (from cf in coarse
                        // grab th SelectionData instance for this symbol
                        let avg = _averages.GetOrAdd(cf.Symbol, sym => new SelectionData())
                        // Update returns true when the indicators are ready, so don't accept until they are
                        where avg.Update(cf.EndTime, cf.AdjustedPrice)
                        // Cross up and price must be greater than 10
                        where avg.IsCrossUp && cf.Price > 10
                        // prefer symbols with a larger dollar volume
                        orderby cf.DollarVolume
                        // we only need to return the symbol and return 'Count' symbols
                        select cf.Symbol).Take(Count);
            });
        }

        public override void OnData(Slice slice)
        {
            if (_changes == SecurityChanges.None) return;

            // we'll simply go long each security we added to the universe
            foreach (var security in _changes.AddedSecurities)
            {
            	if (security.Price > 0)
            	{
            		var symbol = security.Symbol;
            		//Log($"{_averages[symbol]} of {symbol}");
                    SetHoldings(symbol, 1m/Count);
            	}
            }
        }

        public override void OnSecuritiesChanged(SecurityChanges changes)
        {
        	// liquidate securities removed from our universe
            foreach (var security in changes.RemovedSecurities)
            {
                if (security.Invested)
                {
                    Liquidate(security.Symbol);
                }
            }
            _changes = changes;
        }
        
        // class used to improve readability of the coarse selection function
        private class SelectionData
        {
            private readonly RelativeStrengthIndex _present;
            private readonly Delay _past;

			public bool IsCrossUp => _past.IsReady && _past < 30 && _present > 30;

            public SelectionData()
            {
            	_present = new RelativeStrengthIndex(14);
            	_past = new Delay(1);
                _past.Of(_present);
            }

            public bool Update(DateTime time, decimal value)
            {
            	_present.Update(time, value);
                return _past.IsReady;
            }
            
            public override string ToString()
            {
            	var time = _present.Current.Time;
            	return $"{time} :: Past: {_past} Present: {_present}";
            }
        }
    }
}