/*

* 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.Algorithm.Framework.Execution;

using QuantConnect.Algorithm.Framework.Portfolio;

using QuantConnect.Algorithm.Framework.Selection;

using QuantConnect.Interfaces;

namespace QuantConnect.Algorithm.CSharp

{

/// <summary>

/// Test algorithm using <see cref="InsightWeightingPortfolioConstructionModel"/> and <see cref="ConstantAlphaModel"/>

/// generating a constant <see cref="Insight"/> with a 0.25 weight

/// </summary>

public class InsightWeightingFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition

{

/// <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 requested data resolution

UniverseSettings.Resolution = Resolution.Minute;

SetStartDate(2013, 10, 07); //Set Start Date

SetEndDate(2013, 10, 11); //Set End Date

SetCash(100000); //Set Strategy Cash

// set algorithm framework models

SetUniverseSelection(new ManualUniverseSelectionModel(QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA)));

SetAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromMinutes(20), 0.025, null, 0.25));

SetPortfolioConstruction(new InsightWeightingPortfolioConstructionModel());

SetExecution(new ImmediateExecutionModel());

}

public override void OnEndOfAlgorithm()

{

if (// holdings value should be 0.25 - to avoid price fluctuation issue we compare with 0.28 and 0.23

Portfolio.TotalHoldingsValue > Portfolio.TotalPortfolioValue * 0.28m

||

Portfolio.TotalHoldingsValue < Portfolio.TotalPortfolioValue * 0.23m)

{

throw new Exception($"Unexpected Total Holdings Value: {Portfolio.TotalHoldingsValue}");

}

}

/// <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", "6"},

{"Average Win", "0.00%"},

{"Average Loss", "0.00%"},

{"Compounding Annual Return", "37.905%"},

{"Drawdown", "0.600%"},

{"Expectancy", "-0.495"},

{"Net Profit", "0.412%"},

{"Sharpe Ratio", "4.344"},

{"Loss Rate", "67%"},

{"Win Rate", "33%"},

{"Profit-Loss Ratio", "0.52"},

{"Alpha", "0.001"},

{"Beta", "18.742"},

{"Annual Standard Deviation", "0.048"},

{"Annual Variance", "0.002"},

{"Information Ratio", "4.118"},

{"Tracking Error", "0.048"},

{"Treynor Ratio", "0.011"},

{"Total Fees", "$6.00"},

{"Total Insights Generated", "100"},

{"Total Insights Closed", "99"},

{"Total Insights Analysis Completed", "99"},

{"Long Insight Count", "100"},

{"Short Insight Count", "0"},

{"Long/Short Ratio", "100%"},

{"Estimated Monthly Alpha Value", "$158418.3850"},

{"Total Accumulated Estimated Alpha Value", "$25522.9620"},

{"Mean Population Estimated Insight Value", "$257.8077"},

{"Mean Population Direction", "54.5455%"},

{"Mean Population Magnitude", "54.5455%"},

{"Rolling Averaged Population Direction", "59.8056%"},

{"Rolling Averaged Population Magnitude", "59.8056%"}

};

}

}