namespace QuantConnect.Algorithm.CSharp
{
    /// <summary>
    /// This algorithm will go long when the 50 crosses above the 200 and will short 
    /// when the 50 crosses back below the 200.
    /// </summary>
    public class MovingAverageCrossAlgorithm : QCAlgorithm
    {
        
        
        
        
        private string _symbol = "SPY";
        private DateTime _previous;
        private SimpleMovingAverage _fast;
        private SimpleMovingAverage _slow;
//        private SimpleMovingAverage[] _ribbon;

        /// <summary>
        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
        /// </summary>
        public override void Initialize()
        {
			
			
            // set up our analysis span
            SetStartDate(1998, 01, 02);
            //SetEndDate(2017, 07, 01);
            SetCash(100000);
            

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

            // create a 50 day exponential moving average
            _fast = SMA(_symbol, 50, Resolution.Daily);

            // create a 200 day exponential moving average
            _slow = SMA(_symbol, 200, Resolution.Daily);
            
            

//            var ribbonCount = 4;
//            var ribbonInterval = 50;
//            _ribbon = Enumerable.Range(0, ribbonCount).Select(x => SMA(_symbol, (x + 1)*ribbonInterval, Resolution.Daily)).ToArray();
        }


        /// <summary>
        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
        /// </summary>
        /// <param name="data">TradeBars IDictionary object with your stock data</param>
        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
            if (!_slow.IsReady) return;

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

            // define a small tolerance on our checks to avoid bouncing
            const decimal tolerance = 0.00015m;
            var holdings = Portfolio[_symbol].Quantity;
            var profitloss = Portfolio[_symbol].UnrealizedProfit;

            // we only want to go long if we're currently short or flat
            if (holdings <= 0)
            {
                // if the fast is greater than the slow, we'll go long
                if (_fast > _slow * (1 + tolerance))
                {
                    Log("BUY  >> " + Securities[_symbol].Price);
                    SetHoldings(_symbol, 1.0);
                }
            }

            // we only want to liquidate if we're currently long
            // if the fast is less than the slow we'll liquidate our long
            //if (_fast < _slow)
            if (holdings > 0 && _fast < _slow)
            {
                Log("SELL >> " + Securities[_symbol].Price);
                SetHoldings(_symbol, -1.0);
                //Liquidate(_symbol);
            }
            
            if (profitloss <= -2000)
            {
                //Log("SELL >> " + Securities[_symbol].Price);
                //SetHoldings(_symbol, -1.0);
                Liquidate(_symbol);
            }
            

            Plot(_symbol, "Price", data[_symbol].Price);

            // easily plot indicators, the series name will be the name of the indicator
            Plot(_symbol, _fast, _slow);
            //Plot("Ribbon", _ribbon);
            
            
            

            _previous = Time;
        }
    }
}