Overall Statistics
using System;
using System.Linq;
using QuantConnect.Indicators;
using QuantConnect.Models;

namespace QuantConnect.Algorithm.Examples
{
    /// <summary>
    /// 
    /// QuantConnect University: SMA + SMA Cross
    ///
    /// In this example we look at the canonical 15/30 day moving average cross. This algorithm
    /// will go long when the 15 crosses above the 30 and will liquidate when the 15 crosses
    /// back below the 30.
    /// </summary>
    public class QCUMovingAverageCross : QCAlgorithm
    {
        private const string Symbol = "SPY";

        public override void Initialize()
        {
            // set up our analysis span
            SetStartDate(1998, 01, 01);
            SetEndDate(2016, 01, 01);

            // request SPY data with minute resolution
            AddSecurity(SecurityType.Equity, Symbol, Resolution.Minute);
        }

        private DateTime previous;
        public void OnData(TradeBars data)
        {
            // a couple things to notice in this method:
            //  1. We never need to 'update' our indicators with the data, the engine takes care of this for us
            //  2. We can use indicators directly in math expressions
            //  3. We can easily plot many indicators at the same time

            // wait for our slow ema to fully initialize

            // only once per day
            if (previous.Date == data.Time.Date) return;

            var holdings = Portfolio[Symbol].Quantity;

            // we only want to go long if we're currently short or flat
            if (holdings <= 0)
            {
                Log("BUY  >> " + Securities[Symbol].Price);
                SetHoldings(Symbol, 1.0);
            }

            Plot(Symbol, "SPY ", data[Symbol].Price);
            // Plot("Ribbon", "Price", data[Symbol].Price);

            previous = data.Time;
        }
    }
}