/*

* 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 System;

using System.Collections.Generic;

using QuantConnect.Algorithm.Framework.Alphas;

using QuantConnect.Data.Market;

using QuantConnect.Indicators;

using QuantConnect.Interfaces;

namespace QuantConnect.Algorithm.CSharp

{

/// <summary>

/// Demonstration algorithm showing how to easily convert an old algorithm into the framework.

///

/// 1. When making orders, also create insights for the correct direction (up/down/flat), can also set insight prediction period/magnitude/direction

/// 2. Emit insights before placing any trades

/// 3. Profit :)

/// </summary>

/// <meta name="tag" content="indicators" />

/// <meta name="tag" content="indicator classes" />

/// <meta name="tag" content="plotting indicators" />

public class ConvertToFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition

{

private MovingAverageConvergenceDivergence _macd;

private readonly string _symbol = "SPY";

public readonly int FastEmaPeriod = 12;

public readonly int SlowEmaPeriod = 26;

/// <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(2004, 01, 01);

SetEndDate(2015, 01, 01);

AddSecurity(SecurityType.Equity, _symbol, Resolution.Daily);

// define our daily macd(12,26) with a 9 day signal

_macd = MACD(_symbol, FastEmaPeriod, SlowEmaPeriod, 9, MovingAverageType.Exponential, Resolution.Daily);

}

/// <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)

{

// wait for our indicator to be ready

if (!_macd.IsReady) return;

var holding = Portfolio[_symbol];

var signalDeltaPercent = (_macd - _macd.Signal) / _macd.Fast;

var tolerance = 0.0025m;

// if our macd is greater than our signal, then let's go long

if (holding.Quantity <= 0 && signalDeltaPercent > tolerance)

{

// 1. Call EmitInsights with insights created in correct direction, here we're going long

// The EmitInsights method can accept multiple insights separated by commas

EmitInsights(

// Creates an insight for our symbol, predicting that it will move up within the fast ema period number of days

Insight.Price(_symbol, TimeSpan.FromDays(FastEmaPeriod), InsightDirection.Up)

);

// longterm says buy as well

SetHoldings(_symbol, 1.0);

}

// if our macd is less than our signal, then let's go short

else if (holding.Quantity >= 0 && signalDeltaPercent < -tolerance)

{

// 1. Call EmitInsights with insights created in correct direction, here we're going short

// The EmitInsights method can accept multiple insights separated by commas

EmitInsights(

// Creates an insight for our symbol, predicting that it will move down within the fast ema period number of days

Insight.Price(_symbol, TimeSpan.FromDays(FastEmaPeriod), InsightDirection.Down)

);

// shortterm says sell as well

SetHoldings(_symbol, -1.0);

}

// if we wanted to liquidate our positions

// 1. Call EmitInsights with insights create in the correct direction -- Flat

// EmitInsights(

// Creates an insight for our symbol, predicting that it will move down or up within the fast ema period number of days, depending on our current position

// Insight.Price(_symbol, TimeSpan.FromDays(FastEmaPeriod), InsightDirection.Flat);

// );

// Liquidate();

// plot both lines

Plot("MACD", _macd, _macd.Signal);

Plot(_symbol, "Open", data[_symbol].Open);

Plot(_symbol, _macd.Fast, _macd.Slow);

}

/// <summary>

/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.

/// </summary>

public bool CanRunLocally { get; } = true;

/// <summary>

/// This is used by the regression test system to indicate which languages this algorithm is written in.

/// </summary>

public Language[] Languages { get; } = { Language.CSharp, Language.Python };

/// <summary>

/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm

/// </summary>

public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>

{

{"Total Trades", "85"},

{"Average Win", "4.85%"},

{"Average Loss", "-4.21%"},

{"Compounding Annual Return", "-3.100%"},

{"Drawdown", "52.900%"},

{"Expectancy", "-0.052"},

{"Net Profit", "-29.298%"},

{"Sharpe Ratio", "-0.076"},

{"Probabilistic Sharpe Ratio", "0.004%"},

{"Loss Rate", "56%"},

{"Win Rate", "44%"},

{"Profit-Loss Ratio", "1.15"},

{"Alpha", "-0.013"},

{"Beta", "0.009"},

{"Annual Standard Deviation", "0.164"},

{"Annual Variance", "0.027"},

{"Information Ratio", "-0.391"},

{"Tracking Error", "0.239"},

{"Treynor Ratio", "-1.416"},

{"Total Fees", "$755.29"},

{"Fitness Score", "0.024"},

{"Kelly Criterion Estimate", "-0.84"},

{"Kelly Criterion Probability Value", "0.53"},

{"Sortino Ratio", "-0.224"},

{"Return Over Maximum Drawdown", "-0.058"},

{"Portfolio Turnover", "0.05"},

{"Total Insights Generated", "85"},

{"Total Insights Closed", "85"},

{"Total Insights Analysis Completed", "85"},

{"Long Insight Count", "42"},

{"Short Insight Count", "43"},

{"Long/Short Ratio", "97.67%"},

{"Estimated Monthly Alpha Value", "$-617339.2"},

{"Total Accumulated Estimated Alpha Value", "$-82686580"},

{"Mean Population Estimated Insight Value", "$-972783.3"},

{"Mean Population Direction", "51.7647%"},

{"Mean Population Magnitude", "0%"},

{"Rolling Averaged Population Direction", "48.2217%"},

{"Rolling Averaged Population Magnitude", "0%"},

{"OrderListHash", "1370210213"}

};

}

}