Overall Statistics Total Trades 158 Average Win 4.88% Average Loss -2.22% Compounding Annual Return 2.775% Drawdown 35.700% Expectancy 0.334 Net Profit 63.732% Sharpe Ratio 0.298 Loss Rate 58% Win Rate 42% Profit-Loss Ratio 2.19 Alpha 0.035 Beta -0.017 Annual Standard Deviation 0.113 Annual Variance 0.013 Information Ratio -0.194 Tracking Error 0.23 Treynor Ratio -1.932 Total Fees \$834.20
```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";

private SimpleMovingAverage fast;
private SimpleMovingAverage slow;

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);

// create a 15 day exponential moving average
fast = SMA(Symbol, 5, Resolution.Daily);

// create a 30 day exponential moving average
slow = SMA(Symbol, 50, Resolution.Daily);
}

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
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 * (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 (holdings > 0 && fast < slow)
{
Log("SELL >> " + Securities[Symbol].Price);
Order(Symbol, -holdings);
// Liquidate(Symbol);
}

Plot(Symbol, "SPY ", data[Symbol].Price);
// Plot("Ribbon", "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 = data.Time;
}
}
}                        ```