/// <summary>
/// Initializes this alpha handler to accept insights from the specified algorithm
/// </summary>
/// <param name="job">The algorithm job</param>
/// <param name="algorithm">The algorithm instance</param>
/// <param name="messagingHandler">Handler used for sending insights</param>
/// <param name="api">Api instance</param>
public virtual void Initialize(AlgorithmNodePacket job, IAlgorithm algorithm, IMessagingHandler messagingHandler, IApi api)
{
// initializing these properties just in case, doesn't hurt to have them populated
Job = job;
Algorithm = algorithm;
MessagingHandler = messagingHandler;
_fitnessScore = new FitnessScoreManager();
_insights = new List <Insight>();
_securityValuesProvider = new AlgorithmSecurityValuesProvider(algorithm);
InsightManager = CreateInsightManager();
var statistics = new StatisticsInsightManagerExtension(algorithm);
RuntimeStatistics = statistics.Statistics;
InsightManager.AddExtension(statistics);
AddInsightManagerCustomExtensions(statistics);
// when insight is generated, take snapshot of securities and place in queue for insight manager to process on alpha thread
algorithm.InsightsGenerated += (algo, collection) =>
{
lock (_insights)
{
_insights.AddRange(collection.Insights);
}
};
}
/// <summary>
/// Initializes this alpha handler to accept insights from the specified algorithm
/// </summary>
/// <param name="job">The algorithm job</param>
/// <param name="algorithm">The algorithm instance</param>
/// <param name="messagingHandler">Handler used for sending insights</param>
/// <param name="api">Api instance</param>
public virtual void Initialize(AlgorithmNodePacket job, IAlgorithm algorithm, IMessagingHandler messagingHandler, IApi api)
{
// initializing these properties just in case, doens't hurt to have them populated
Job = job;
Algorithm = algorithm;
MessagingHandler = messagingHandler;
_fitnessScore = new FitnessScoreManager();
_securityValuesProvider = new AlgorithmSecurityValuesProvider(algorithm);
InsightManager = CreateInsightManager();
// send scored insights to messaging handler
InsightManager.AddExtension(CreateAlphaResultPacketSender());
var statistics = new StatisticsInsightManagerExtension(algorithm);
RuntimeStatistics = statistics.Statistics;
InsightManager.AddExtension(statistics);
_charting = new ChartingInsightManagerExtension(algorithm, statistics);
InsightManager.AddExtension(_charting);
// when insight is generated, take snapshot of securities and place in queue for insight manager to process on alpha thread
algorithm.InsightsGenerated += (algo, collection) => InsightManager.Step(collection.DateTimeUtc, CreateSecurityValuesSnapshot(), collection);
}
public void ValueIsCalculatedCorrectly()
{
var algorithm = new QCAlgorithm();
var initialDate = new DateTime(2018, 1, 1);
algorithm.SetStartDate(initialDate);
algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(algorithm));
algorithm.AddEquity("SPY");
var fitnessScore = new FitnessScoreManager();
fitnessScore.Initialize(algorithm);
algorithm.SetDateTime(initialDate.AddDays(1));
IncreaseCashAmount(algorithm, 0.05);
IncreaseSalesVolumeAmount(algorithm);
fitnessScore.UpdateScores();
var score = fitnessScore.FitnessScore;
// FitnessScore: 1 * (5 + 5)
Assert.AreEqual(1m, score);
algorithm.SetDateTime(initialDate.AddDays(1));
IncreaseCashAmount(algorithm, -0.20);
fitnessScore.UpdateScores();
algorithm.SetDateTime(initialDate.AddDays(1));
IncreaseCashAmount(algorithm, -0.20);
// FitnessScore: 0.333 * (-3.299 + -5)
fitnessScore.UpdateScores();
score = fitnessScore.FitnessScore;
Assert.AreEqual(0.028m, score);
}
public void ZeroStartingPortfolioValueAlgorithm()
{
var algorithm = new QCAlgorithm();
var initialDate = new DateTime(2018, 1, 1);
algorithm.SetStartDate(initialDate);
algorithm.SetCash(0);
var fitnessScore = new FitnessScoreManager();
fitnessScore.Initialize(algorithm);
decimal score = 0;
for (var i = 0; i < 10; i++)
{
algorithm.SetDateTime(initialDate.AddDays(i));
fitnessScore.UpdateScores();
score = fitnessScore.FitnessScore;
}
Assert.AreEqual(0m, score);
}
/// <summary>
/// Initializes this alpha handler to accept insights from the specified algorithm
/// </summary>
/// <param name="job">The algorithm job</param>
/// <param name="algorithm">The algorithm instance</param>
/// <param name="messagingHandler">Handler used for sending insights</param>
/// <param name="api">Api instance</param>
/// <param name="transactionHandler">Algorithms transaction handler</param>
public virtual void Initialize(AlgorithmNodePacket job, IAlgorithm algorithm, IMessagingHandler messagingHandler, IApi api, ITransactionHandler transactionHandler)
{
// initializing these properties just in case, doesn't hurt to have them populated
Job = job;
Algorithm = algorithm;
MessagingHandler = messagingHandler;
_fitnessScore = new FitnessScoreManager();
_insights = new List <Insight>();
_securityValuesProvider = new AlgorithmSecurityValuesProvider(algorithm);
InsightManager = CreateInsightManager();
var statistics = new StatisticsInsightManagerExtension(algorithm);
RuntimeStatistics = statistics.Statistics;
InsightManager.AddExtension(statistics);
AddInsightManagerCustomExtensions(statistics);
var baseDirectory = Config.Get("results-destination-folder", Directory.GetCurrentDirectory());
var directory = Path.Combine(baseDirectory, AlgorithmId);
if (!Directory.Exists(directory))
{
Directory.CreateDirectory(directory);
}
_alphaResultsPath = Path.Combine(directory, "alpha-results.json");
// when insight is generated, take snapshot of securities and place in queue for insight manager to process on alpha thread
algorithm.InsightsGenerated += (algo, collection) =>
{
lock (_insights)
{
_insights.AddRange(collection.Insights);
}
};
}
public void ExtremePerformanceAlgorithm(double returnFactor)
{
var algorithm = new QCAlgorithm();
var initialDate = new DateTime(2018, 1, 1);
algorithm.SetStartDate(initialDate);
algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(algorithm));
algorithm.AddEquity("SPY");
var fitnessScore = new FitnessScoreManager();
fitnessScore.Initialize(algorithm);
decimal score = 0;
for (var i = 0; i < 10; i++)
{
algorithm.SetDateTime(initialDate.AddDays(i));
fitnessScore.UpdateScores();
score = fitnessScore.FitnessScore;
IncreaseCashAmount(algorithm, returnFactor);
IncreaseSalesVolumeAmount(algorithm);
}
Assert.AreEqual(returnFactor < 1 ? 0.174m : 1m, score);
}
public void SigmoidalScaleWorks(decimal input, decimal expectedResult)
{
var result = FitnessScoreManager.SigmoidalScale(input);
Assert.AreEqual(expectedResult, Math.Round(result, 2));
}
