namespace QuantConnect 
{   
    /*
    *   QuantConnect University: Full Basic Template:
    *
    *   The underlying QCAlgorithm class is full of helper methods which enable you to use QuantConnect.
    *   We have explained some of these here, but the full algorithm can be found at:
    *   https://github.com/QuantConnect/QCAlgorithm/blob/master/QuantConnect.Algorithm/QCAlgorithm.cs
    */
    public class BasicTemplateAlgorithm : QCAlgorithm
    {
    	
    	string symbol = "SPY";
    	
    	VolumeMovingAverage vma = new VolumeMovingAverage(14);
        //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);         
            SetEndDate(DateTime.Now.Date.AddDays(-1));
            
            //Cash allocation
            SetCash(25000);
            
            //Add as many securities as you like. All the data will be passed into the event handler:
            AddSecurity(SecurityType.Equity, symbol, Resolution.Minute);
            RegisterIndicator(symbol, vma, Resolution.Minute, null);
            PlotIndicator(string.Format("VMA{0}", symbol), vma);
        }

        //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) 
        {   
        	//vma.Update(data["SPY"]);
        	//Debug(string.Format("VMA{0}", vma.Current));
            // "TradeBars" object holds many "TradeBar" objects: it is a dictionary indexed by the symbol:
            // 
            //  e.g.  data["MSFT"] data["GOOG"]
            
            if (!Portfolio.HoldStock) 
            {
                int quantity = (int)Math.Floor(Portfolio.Cash / data["SPY"].Close);
                
                //Order function places trades: enter the string symbol and the quantity you want:
                Order("SPY",  quantity);
                
                //Debug sends messages to the user console: "Time" is the algorithm time keeper object 
                Debug("Purchased SPY on " + Time.ToShortDateString());
                
                //You can also use log to send longer messages to a file. You are capped to 10kb
                //Log("This is a longer message send to log.");
            }
        }
    }
}

using QuantConnect.Data.Market;
using System.Linq;

namespace QuantConnect.Indicators {

	/// <summary>
	///     Represents the traditional exponential moving average indicator (EMA)
	/// </summary>
	public class VolumeMovingAverage : IndicatorBase<TradeBar> {
		private readonly int _period;


		private RollingWindow<TradeBar> _tradeBars;
		/// <summary>Initializes a new instance of the VolumeMovingAverage class with the specified name and period
		/// </summary>
		/// <param name="name">The name of this indicator</param>
		/// <param name="period">The period of the EMA</param>
		public VolumeMovingAverage(string name, int period)
			: base(name) {
			_period = period;
			_tradeBars = new RollingWindow<TradeBar>(period);
		}


		/// <summary>
		///     Initializes a new instance of the ExponentialMovingAverage class with the default name and period
		/// </summary>
		/// <param name="period">The period of the EMA</param>
		public VolumeMovingAverage(int period)
			: this("VMA" + period, period) {
		}


		/// <summary>
		///     Gets a flag indicating when this indicator is ready and fully initialized
		/// </summary>
		public override bool IsReady {
			get { return Samples >= _period; }
		}

		/// <summary>
		///     Computes the next value of this indicator from the given state
		/// </summary>
		/// <param name="input">The input given to the indicator</param>
		/// <returns>A new value for this indicator</returns>
		protected override decimal ComputeNextValue(TradeBar input) {
			_tradeBars.Add(input);

			decimal totalVolume = _tradeBars.Select(x => x.Volume).Sum();

			// our first data point just return identity
			if (Samples == 1 || totalVolume == 0) {
				return input.Close;
			}

			decimal volume = input.Volume;

			return ((Current * (totalVolume - volume)) / totalVolume) + ((volume * input.Price) / totalVolume);
		}
	}
}