Overall Statistics
Total Trades
239
Average Win
0.79%
Average Loss
-0.24%
Compounding Annual Return
-95.145%
Drawdown
17.300%
Expectancy
-0.476
Net Profit
-11.278%
Sharpe Ratio
-6.541
Loss Rate
88%
Win Rate
12%
Profit-Loss Ratio
3.30
Alpha
-2.648
Beta
-0.011
Annual Standard Deviation
0.405
Annual Variance
0.164
Information Ratio
-7.048
Tracking Error
0.425
Treynor Ratio
242.135
Total Fees
$1223.75
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 20/50 day moving average cross. This algorithm
    /// will go long when the 20 crosses above the 50 and will liquidate when the 20 crosses
    /// back below the 50.
    
    // -------VATS CHANGES -----------
    // 1) Intraday - Hourly
    // 2) 1/50 period SMA cross
    // 
    // -------VATS CHANGES -----------
    
    /// </summary>
    
    public class QCUMovingAverageCross : QCAlgorithm
    {
        private const string Symbol = "USO";

        private SimpleMovingAverage fast;
        private SimpleMovingAverage slow;

        TradeBar _spyMinutes;
        
        public override void Initialize()
        {

            SetStartDate(2015, 07, 01);
            SetEndDate(2015, 07, 15);
			SetCash(10000);
            AddSecurity(SecurityType.Equity, Symbol, Resolution.Minute);
            
            // define our daily trade bar consolidator. we can access the daily bar
            // from the DataConsolidated events
            var minConsolidator = new TradeBarConsolidator(TimeSpan.FromMinutes(5));
            
            // attach our event handler. the event handler is a function that will be called each time we produce
            // a new consolidated piece of data.
            minConsolidator.DataConsolidated += OnDataMinutes;

            // this call adds our daily consolidator to the manager to receive updates from the engine
            SubscriptionManager.AddConsolidator(Symbol, minConsolidator);
            
            
            fast = SMA(Symbol, 1, Resolution.Minute);
            slow = SMA(Symbol, 50, Resolution.Minute);
            //SetRunMode(RunMode.Series);
        }
        

        private void OnDataMinutes(object sender, TradeBar consolidated)
        {
            _spyMinutes = consolidated;
            //Log(consolidated.Time.ToString("o") + " >> " + Symbol  + ">> LONG  >> 100 >> " + Portfolio[Symbol].Quantity);
        }
        

        private DateTime previous;
        public void OnData(TradeBars data)
        {
            
            
            if (!slow.IsReady) return;

            // only once per day 
            // Commented the following line to simulate intraday - Vats
            //if (previous.Date == data.Time.Date) return;
            
           // Debug (System.DateTime.Now.Hour.ToString()) ;
           // if (System.DateTime.Now.Hour <= 10 && System.DateTime.Now.Hour > 12) return;
 

            const decimal tolerance = 0.00010m;
            var holdings = Portfolio[Symbol].Quantity;


            
            
            {
                if (fast > slow * (1 + tolerance))
                {
                    if (holdings <= 0)
                    {
                        Log (System.DateTime.Now.Hour.ToString()) ;
                        Log("BUY  >> " + holdings + "@ price " + Securities[Symbol].Price);
                        SetHoldings(Symbol, 0.95);
                        Log("NET POSITION BEFORE NEXT TRANSACTION >> " + holdings);
                    }
                }
    
       
                if (fast < slow)
                {
                    if (holdings > 0)
                    {
                       Log (System.DateTime.Now.Hour.ToString()) ;
                       Log("SELL >> " + holdings + "@ price " + Securities[Symbol].Price);
                       SetHoldings(Symbol, -0.95);
                    }
                }
            }

            Plot(Symbol, "Price", data[Symbol].Price);
            Plot(Symbol, fast, slow);
            previous = data.Time;
        }
    }
}