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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.

* Licensed under the Apache License, Version 2.0 (the "License");

* you may not use this file except in compliance with the License.

* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0

* Unless required by applicable law or agreed to in writing, software

* distributed under the License is distributed on an "AS IS" BASIS,

* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

* See the License for the specific language governing permissions and

* limitations under the License.

using System;

using System.Linq;

using QuantConnect.Data.Market;

using QuantConnect.Indicators;

namespace QuantConnect.Algorithm.Examples

{

/// <summary>

/// 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 MovingAverageCrossAlgorithm : QCAlgorithm

{

private const string Symbol = "SPY";

private DateTime previous;

private ExponentialMovingAverage fast;

private ExponentialMovingAverage 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(2009, 01, 01);

SetEndDate(2015, 01, 01);

// request SPY data with minute resolution

AddSecurity(SecurityType.Equity, Symbol, Resolution.Minute);

// create a 15 day exponential moving average

fast = EMA(Symbol, 15, Resolution.Daily);

// create a 30 day exponential moving average

slow = EMA(Symbol, 30, Resolution.Daily);

int ribbonCount = 8;

int ribbonInterval = 15;

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;

// 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);

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;

}

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