Overall Statistics
Total Trades
19
Average Win
21.20%
Average Loss
-6.70%
Compounding Annual Return
44.445%
Drawdown
36.000%
Expectancy
0.388
Net Profit
44.736%
Sharpe Ratio
0.783
Loss Rate
67%
Win Rate
33%
Profit-Loss Ratio
3.16
Alpha
0.32
Beta
0.501
Annual Standard Deviation
0.453
Annual Variance
0.206
Information Ratio
0.63
Tracking Error
0.453
Treynor Ratio
0.708
Total Fees
$0.00
using System;
using System.Linq;
using QuantConnect.Indicators;
using QuantConnect.Models;

namespace QuantConnect.Algorithm.Examples
{
    /// <summary>
    /// 
    /// QuantConnect University: EMA + 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 = "XAUUSD";

        private ExponentialMovingAverage fast;
        private ExponentialMovingAverage slow;
     

        public override void Initialize()
        {
            // set up our analysis span
            SetStartDate(2016, 01, 01);
            SetEndDate(2017, 01, 01);
             SetCash(5000);
             
            SetBrokerageModel(BrokerageName.OandaBrokerage);
             
            // request SPY data with minute resolution
            AddSecurity( SecurityType.Cfd,Symbol, Resolution.Minute);

            // create a 15 day exponential moving average
            fast = EMA(Symbol, 12, Resolution.Daily);

            // create a 30 day exponential moving average
            slow = EMA(Symbol, 26, Resolution.Daily);

            
        
        }

        private DateTime previous;
        public void OnData(QuoteBars 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 == data.Time.Date) return;

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

            // 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 )
                {
                	// Liquidate(Symbol);
                   // Log("BUY  >> " + Securities[Symbol].Price);
                   // SetHoldings(Symbol, 100);
                   MarketOrder(Symbol, 20, false,  "buy 100 EURUSD");
                  
                }
                
            }
            
              if (holdings >= 0)
            {
                // if the fast is greater than the slow, we'll go long
                if (fast < slow )
                {
                	// Liquidate(Symbol);    
                //    Log("SELL  >> " + Securities[Symbol].Price);
                 MarketOrder(Symbol,-20, false,  "sell 100 EURUSD");
                 
                }
                
            }

            // we only want to liquidate if we're currently long
            // if the fast is less than the slow we'll liquidate our long
            
 
           
            previous = data.Time;
        }
    }
}