| Overall Statistics |
|
Total Trades 2 Average Win 14.03% Average Loss -8.66% Compounding Annual Return 4.164% Drawdown 5.800% Expectancy 0.31 Net Profit 4.16% Sharpe Ratio 0.481 Loss Rate 50% Win Rate 50% Profit-Loss Ratio 1.62 Alpha 0.062 Beta -0.061 Annual Standard Deviation 0.093 Annual Variance 0.009 Information Ratio -1.604 Tracking Error 0.15 Treynor Ratio -0.737 |
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* 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 QuantConnect.Data.Market;
using QuantConnect.Indicators;
namespace QuantConnect.Algorithm.Examples
{
/// <summary>
/// In this algorithm we'll compute/plot the ratio between coke and pepsi
/// </summary>
public class IndicatorRatioExampleAlgorithm : QCAlgorithm
{
/// <summary>
/// Our EMA of Coca cola minute close prices
/// </summary>
public ExponentialMovingAverage EMA_KO;
/// <summary>
/// Our EMA of Pepsi minute close prices
/// </summary>
public ExponentialMovingAverage EMA_PEP;
/// <summary>
/// Our ratio of the EMA of KO/PEP minute close prices
/// </summary>
public CompositeIndicator<IndicatorDataPoint> KO_Over_PEP;
/// <summary>
/// Bollinger
/// </summary>
public BollingerBands BB_Ratio;
/// <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()
{
SetStartDate(2013, 01, 01); //Set Start Date
SetEndDate(2014, 01, 01); //Set End Date
SetCash(100000); //Set Strategy Cash'
// Find more symbols here: http://quantconnect.com/data
AddSecurity(SecurityType.Equity, "KO", Resolution.Minute);
AddSecurity(SecurityType.Equity, "PEP", Resolution.Minute);
EMA_KO = EMA("KO", 14, Resolution.Daily);
EMA_PEP = EMA("PEP", 14, Resolution.Daily);
// This will create a new indicator that is the ema_ko divided by the ema_pep
KO_Over_PEP = EMA_KO.Over(EMA_PEP);
// we'll also create a bollinger band of the ratio for plotting
BB_Ratio = new BollingerBands("BB_Ratio", 14, 2).Of(KO_Over_PEP);
}
/// <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)
{
if (BB_Ratio.IsReady && !Portfolio.Invested)
{
MarketOrder("KO", -2000);
MarketOrder("PEP", (int) (2000*KO_Over_PEP));
}
// plot every afternoon
if (data.Time.Hour == (3 + 12) && data.Time.Minute == 50)
{
// wait for bollinger bands to get ready
if (BB_Ratio.IsReady)
{
Plot("Ratio", KO_Over_PEP, BB_Ratio.UpperBand, BB_Ratio.MiddleBand, BB_Ratio.LowerBand);
}
}
}
}
}