Overall Statistics
namespace QuantConnect 
	public enum Decision { Long, Short, Neutral };
	// quick demo of the RollingWindow<T> class
    public class RollingWindowAlgorithm : QCAlgorithm
    	// keep 5 of the last data points, max index of 4
    	public RollingWindow<TradeBar> History = new RollingWindow<TradeBar>(5);
    	// we want 3 decisions in a row to be the same
    	public RollingWindow<Decision> RecentDecisions = new RollingWindow<Decision>(2);
    	// define some indicators
    	public ExponentialMovingAverage Fast;
    	public ExponentialMovingAverage Slow;
    	// these will hold the history of our indicators
    	public RollingWindow<decimal> FastEmaHistory = new RollingWindow<decimal>(10);
    	public RollingWindow<decimal> SlowEmaHistory = new RollingWindow<decimal>(10);
        //Initialize the data and resolution you require for your strategy:
        public override void Initialize() 
            //Start and End Date range for the backtest:
            SetStartDate(2013, 1, 1);         
            //Cash allocation
            //Add as many securities as you like. All the data will be passed into the event handler:
            AddSecurity(SecurityType.Equity, "SPY", Resolution.Daily);
            Fast = EMA("SPY", 10);
            Slow = EMA("SPY", 30);
            // plot the fast ema, the slow ema, and the close price
            PlotIndicator("SPY", Fast, Slow, Identity("SPY"));
        decimal tolerance = 0.005m;

        //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) 
        	// Add the data from this time step to our rolling windows
        	// wait for our history to be ready
        	if (!History.IsReady) return;
        	//if ( close of the previous bar > low of the bar that occurred 2 bars ago)
        	//if (History[1].Close > History[2].Close)
            // you can access the rolling window using indexing,
            // History[0] is the piece of data we just put in
            // History[1] is the piece of data we put in last time step
            // History[n] is the piece of data we put in n time steps ago
        	//if (10 period EMA > 30 period EMA for 3 bars in a row)
            if (Fast > Slow*(1+tolerance))
            else if (Fast < Slow*(1-tolerance))
            // determine if all the decisions are the same by dropping
            // them into a hash, if they're all unique then th count is 1
            var hash = RecentDecisions.ToHashSet();
            if (hash.Count != 1)
            	// inconclusive decisions
            	// grab the only decision
            	var decision = hash.Single();
            	decimal percentage = 0;
            	switch (decision)
            		case Decision.Long:
            			percentage = 1.5m;
            		case Decision.Short:
            			percentage = -1.5m;
            		case Decision.Neutral:
            			percentage = 0m;
            	SetHoldings("SPY", percentage);