Update genetic
This commit is contained in:
@@ -6,6 +6,7 @@ using Managing.Domain.Backtests;
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using Managing.Domain.Bots;
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using Managing.Domain.MoneyManagements;
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using Managing.Domain.Risk;
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using Managing.Domain.Scenarios;
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using Managing.Domain.Users;
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using Microsoft.Extensions.Logging;
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using static Managing.Common.Enums;
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@@ -21,6 +22,144 @@ public class GeneticService : IGeneticService
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private readonly IBacktester _backtester;
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private readonly ILogger<GeneticService> _logger;
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// Predefined parameter ranges for each indicator (matching backtestGenetic.tsx)
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public static readonly Dictionary<string, (double min, double max)> ParameterRanges = new()
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{
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// Trading Parameters only - indicator parameters are now handled by IndicatorParameterRanges
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["stopLoss"] = (0.2, 50.0), // Minimum 0.2% to cover fees, no upper limit (set to 50% as practical max)
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["leverage"] = (1.0, 10.0),
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["cooldownPeriod"] = (5.0, 25.0),
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["maxLossStreak"] = (0.0, 4.0),
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["maxPositionTimeHours"] = (0, 48.0)
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};
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// Default indicator values per indicator type (matching CustomScenario.tsx)
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public static readonly Dictionary<IndicatorType, Dictionary<string, double>> DefaultIndicatorValues = new()
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{
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[IndicatorType.RsiDivergence] = new() { ["period"] = 14.0 },
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[IndicatorType.RsiDivergenceConfirm] = new() { ["period"] = 14.0 },
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[IndicatorType.EmaCross] = new() { ["period"] = 14.0 },
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[IndicatorType.EmaTrend] = new() { ["period"] = 14.0 },
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[IndicatorType.StDev] = new() { ["period"] = 14.0 },
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[IndicatorType.ThreeWhiteSoldiers] = new() { ["period"] = 14.0 },
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[IndicatorType.MacdCross] = new() {
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["fastPeriods"] = 12.0,
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["slowPeriods"] = 26.0,
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["signalPeriods"] = 9.0
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},
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[IndicatorType.DualEmaCross] = new() {
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["fastPeriods"] = 12.0,
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["slowPeriods"] = 26.0
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},
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[IndicatorType.SuperTrend] = new() {
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["period"] = 14.0,
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["multiplier"] = 3.0
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},
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[IndicatorType.SuperTrendCrossEma] = new() {
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["period"] = 14.0,
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["multiplier"] = 3.0
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},
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[IndicatorType.ChandelierExit] = new() {
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["period"] = 14.0,
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["multiplier"] = 3.0
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},
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[IndicatorType.StochRsiTrend] = new() {
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["period"] = 14.0,
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["stochPeriods"] = 14.0,
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["signalPeriods"] = 9.0,
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["smoothPeriods"] = 3.0
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},
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[IndicatorType.Stc] = new() {
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["cyclePeriods"] = 10.0,
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["fastPeriods"] = 12.0,
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["slowPeriods"] = 26.0
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},
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[IndicatorType.LaggingStc] = new() {
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["cyclePeriods"] = 10.0,
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["fastPeriods"] = 12.0,
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["slowPeriods"] = 26.0
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}
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};
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// Indicator-specific parameter ranges
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public static readonly Dictionary<IndicatorType, Dictionary<string, (double min, double max)>> IndicatorParameterRanges = new()
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{
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[IndicatorType.RsiDivergence] = new() {
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["period"] = (5.0, 50.0)
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},
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[IndicatorType.RsiDivergenceConfirm] = new() {
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["period"] = (5.0, 50.0)
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},
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[IndicatorType.EmaCross] = new() {
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["period"] = (5.0, 200.0)
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},
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[IndicatorType.EmaTrend] = new() {
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["period"] = (5.0, 200.0)
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},
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[IndicatorType.StDev] = new() {
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["period"] = (5.0, 50.0)
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},
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[IndicatorType.ThreeWhiteSoldiers] = new() {
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["period"] = (5.0, 50.0)
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},
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[IndicatorType.MacdCross] = new() {
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["fastPeriods"] = (10.0, 50.0),
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["slowPeriods"] = (20.0, 100.0),
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["signalPeriods"] = (5.0, 20.0)
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},
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[IndicatorType.DualEmaCross] = new() {
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["fastPeriods"] = (5.0, 300.0),
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["slowPeriods"] = (5.0, 300.0)
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},
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[IndicatorType.SuperTrend] = new() {
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["period"] = (5.0, 50.0),
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["multiplier"] = (1.0, 10.0)
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},
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[IndicatorType.SuperTrendCrossEma] = new() {
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["period"] = (5.0, 50.0),
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["multiplier"] = (1.0, 10.0)
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},
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[IndicatorType.ChandelierExit] = new() {
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["period"] = (5.0, 50.0),
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["multiplier"] = (1.0, 10.0)
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},
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[IndicatorType.StochRsiTrend] = new() {
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["period"] = (5.0, 50.0),
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["stochPeriods"] = (5.0, 30.0),
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["signalPeriods"] = (3.0, 15.0),
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["smoothPeriods"] = (1.0, 10.0)
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},
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[IndicatorType.Stc] = new() {
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["cyclePeriods"] = (5.0, 30.0),
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["fastPeriods"] = (5.0, 50.0),
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["slowPeriods"] = (10.0, 100.0)
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},
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[IndicatorType.LaggingStc] = new() {
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["cyclePeriods"] = (5.0, 30.0),
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["fastPeriods"] = (5.0, 50.0),
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["slowPeriods"] = (10.0, 100.0)
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}
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};
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// Indicator type to parameter mapping
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public static readonly Dictionary<IndicatorType, string[]> IndicatorParamMapping = new()
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{
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[IndicatorType.RsiDivergence] = ["period"],
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[IndicatorType.RsiDivergenceConfirm] = ["period"],
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[IndicatorType.EmaCross] = ["period"],
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[IndicatorType.EmaTrend] = ["period"],
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[IndicatorType.StDev] = ["period"],
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[IndicatorType.ThreeWhiteSoldiers] = ["period"],
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[IndicatorType.MacdCross] = ["fastPeriods", "slowPeriods", "signalPeriods"],
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[IndicatorType.DualEmaCross] = ["fastPeriods", "slowPeriods"],
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[IndicatorType.SuperTrend] = ["period", "multiplier"],
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[IndicatorType.SuperTrendCrossEma] = ["period", "multiplier"],
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[IndicatorType.ChandelierExit] = ["period", "multiplier"],
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[IndicatorType.StochRsiTrend] = ["period", "stochPeriods", "signalPeriods", "smoothPeriods"],
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[IndicatorType.Stc] = ["cyclePeriods", "fastPeriods", "slowPeriods"],
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[IndicatorType.LaggingStc] = ["cyclePeriods", "fastPeriods", "slowPeriods"]
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};
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public GeneticService(
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IGeneticRepository geneticRepository,
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IBacktester backtester,
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@@ -46,7 +185,7 @@ public class GeneticService : IGeneticService
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double maxTakeProfit,
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List<IndicatorType> eligibleIndicators)
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{
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var id = Guid.NewGuid().ToString(); // Generate unique GUID
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var id = Guid.NewGuid().ToString();
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var geneticRequest = new GeneticRequest(id)
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{
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Ticker = ticker,
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@@ -104,13 +243,17 @@ public class GeneticService : IGeneticService
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{
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_logger.LogInformation("Starting genetic algorithm for request {RequestId}", request.RequestId);
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// Update status to running
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request.Status = GeneticRequestStatus.Running;
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UpdateGeneticRequest(request);
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// Create chromosome for trading bot configuration
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var chromosome = new TradingBotChromosome(request.EligibleIndicators);
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var chromosome = new TradingBotChromosome(request.EligibleIndicators, request.MaxTakeProfit);
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// Create fitness function
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var fitness = new TradingBotFitness(_backtester, request);
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// Create genetic algorithm
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// Create genetic algorithm with better configuration
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var ga = new GeneticAlgorithm(
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new Population(request.PopulationSize, request.PopulationSize, chromosome),
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fitness,
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@@ -118,7 +261,9 @@ public class GeneticService : IGeneticService
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new UniformCrossover(),
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GetMutation(request.MutationRate))
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{
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Termination = new GenerationNumberTermination(request.Generations)
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Termination = new GenerationNumberTermination(request.Generations),
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MutationProbability = (float)request.MutationRate,
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CrossoverProbability = 0.7f // Fixed crossover rate as in frontend
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};
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// Run the genetic algorithm
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@@ -131,22 +276,40 @@ public class GeneticService : IGeneticService
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_logger.LogInformation("Genetic algorithm completed for request {RequestId}. Best fitness: {Fitness}",
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request.RequestId, bestFitness);
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return new GeneticAlgorithmResult
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{
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BestFitness = bestFitness,
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BestIndividual = bestChromosome?.ToString() ?? "unknown",
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ProgressInfo = JsonSerializer.Serialize(new
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// Update request with results
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request.Status = GeneticRequestStatus.Completed;
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request.CompletedAt = DateTime.UtcNow;
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request.BestFitness = bestFitness;
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request.BestIndividual = bestChromosome?.ToString() ?? "unknown";
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request.ProgressInfo = JsonSerializer.Serialize(new
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{
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generation = ga.GenerationsNumber,
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best_fitness = bestFitness,
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population_size = request.PopulationSize,
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generations = request.Generations
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})
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generations = request.Generations,
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completed_at = DateTime.UtcNow
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});
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UpdateGeneticRequest(request);
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return new GeneticAlgorithmResult
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{
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BestFitness = bestFitness,
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BestIndividual = bestChromosome?.ToString() ?? "unknown",
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ProgressInfo = request.ProgressInfo,
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CompletedAt = DateTime.UtcNow
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};
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}
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catch (Exception ex)
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{
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_logger.LogError(ex, "Error running genetic algorithm for request {RequestId}", request.RequestId);
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// Update request with error
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request.Status = GeneticRequestStatus.Failed;
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request.ErrorMessage = ex.Message;
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request.CompletedAt = DateTime.UtcNow;
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UpdateGeneticRequest(request);
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throw;
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}
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}
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@@ -157,7 +320,7 @@ public class GeneticService : IGeneticService
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{
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"tournament" => new TournamentSelection(),
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"roulette" => new RouletteWheelSelection(),
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"rank" => new RankSelection(),
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"fitness-weighted" => new RankSelection(), // Use rank selection as approximation
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_ => new TournamentSelection()
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};
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}
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@@ -169,69 +332,224 @@ public class GeneticService : IGeneticService
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}
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/// <summary>
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/// Chromosome representing a trading bot configuration
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/// Chromosome representing a trading bot configuration with predefined parameter ranges
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/// </summary>
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public class TradingBotChromosome : ChromosomeBase
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{
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private readonly List<IndicatorType> _eligibleIndicators;
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private readonly double _maxTakeProfit;
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private readonly Random _random = new Random();
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public TradingBotChromosome(List<IndicatorType> eligibleIndicators) : base(eligibleIndicators.Count + 5)
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// Gene structure:
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// 0-2: Trading parameters (takeProfit, stopLoss, cooldownPeriod, maxLossStreak)
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// 3-6: Indicator selection (up to 4 indicators)
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// 7+: Indicator parameters (period, fastPeriods, etc.)
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public TradingBotChromosome(List<IndicatorType> eligibleIndicators, double maxTakeProfit)
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: base(4 + 4 + eligibleIndicators.Count * 8) // Trading params + indicator selection + indicator params
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{
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_eligibleIndicators = eligibleIndicators;
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_maxTakeProfit = maxTakeProfit;
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}
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public override Gene GenerateGene(int geneIndex)
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{
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if (geneIndex < _eligibleIndicators.Count)
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if (geneIndex < 4)
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{
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// Gene represents whether an indicator is selected (0 or 1)
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// Trading parameters
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return geneIndex switch
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{
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0 => new Gene(GetRandomInRange((0.9, _maxTakeProfit))), // Take profit (0.9% to max TP)
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1 => new Gene(GetRandomInRange(GeneticService.ParameterRanges["stopLoss"])), // Stop loss
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2 => new Gene(GetRandomIntInRange(GeneticService.ParameterRanges["cooldownPeriod"])), // Cooldown period
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3 => new Gene(GetRandomIntInRange(GeneticService.ParameterRanges["maxLossStreak"])), // Max loss streak
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_ => new Gene(0)
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};
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}
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else if (geneIndex < 8)
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{
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// Indicator selection (0 = not selected, 1 = selected)
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return new Gene(_random.Next(2));
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}
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else
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{
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// Additional genes for other parameters
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return geneIndex switch
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// Indicator parameters
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var indicatorIndex = (geneIndex - 8) / 8;
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var paramIndex = (geneIndex - 8) % 8;
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if (indicatorIndex < _eligibleIndicators.Count)
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{
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var i when i == _eligibleIndicators.Count => new Gene(_random.Next(1, 11)), // Stop loss percentage
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var i when i == _eligibleIndicators.Count + 1 => new Gene(_random.Next(1, 21)), // Take profit percentage
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var i when i == _eligibleIndicators.Count + 2 => new Gene(_random.Next(1, 101)), // Position size percentage
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var i when i == _eligibleIndicators.Count + 3 => new Gene(_random.Next(1, 51)), // Max positions
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var i when i == _eligibleIndicators.Count + 4 => new Gene(_random.Next(1, 11)), // Risk level
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_ => new Gene(0)
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};
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var indicator = _eligibleIndicators[indicatorIndex];
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var paramName = GetParameterName(paramIndex);
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if (paramName != null && GeneticService.IndicatorParamMapping.ContainsKey(indicator))
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{
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var requiredParams = GeneticService.IndicatorParamMapping[indicator];
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if (requiredParams.Contains(paramName))
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{
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// Use indicator-specific ranges only
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if (GeneticService.IndicatorParameterRanges.ContainsKey(indicator) &&
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GeneticService.IndicatorParameterRanges[indicator].ContainsKey(paramName))
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{
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var indicatorRange = GeneticService.IndicatorParameterRanges[indicator][paramName];
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// 70% chance to use default value, 30% chance to use random value within indicator-specific range
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if (_random.NextDouble() < 0.7)
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{
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var defaultValues = GeneticService.DefaultIndicatorValues[indicator];
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return new Gene(defaultValues[paramName]);
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}
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else
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{
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return new Gene(GetRandomInRange(indicatorRange));
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}
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}
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else
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{
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// If no indicator-specific range is found, use default value only
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var defaultValues = GeneticService.DefaultIndicatorValues[indicator];
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return new Gene(defaultValues[paramName]);
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}
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}
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}
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}
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return new Gene(0);
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}
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}
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public override IChromosome CreateNew()
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{
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return new TradingBotChromosome(_eligibleIndicators);
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return new TradingBotChromosome(_eligibleIndicators, _maxTakeProfit);
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}
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public override IChromosome Clone()
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{
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var clone = new TradingBotChromosome(_eligibleIndicators);
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var clone = new TradingBotChromosome(_eligibleIndicators, _maxTakeProfit);
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clone.ReplaceGenes(0, GetGenes());
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return clone;
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}
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public List<IndicatorType> GetSelectedIndicators()
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public List<GeneticIndicator> GetSelectedIndicators()
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{
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var selected = new List<IndicatorType>();
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for (int i = 0; i < _eligibleIndicators.Count; i++)
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var selected = new List<GeneticIndicator>();
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var genes = GetGenes();
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for (int i = 0; i < 4; i++) // Check first 4 indicator slots
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{
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if (GetGene(i).Value.ToString() == "1")
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if (genes[4 + i].Value.ToString() == "1" && i < _eligibleIndicators.Count)
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{
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selected.Add(_eligibleIndicators[i]);
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var indicator = new GeneticIndicator
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{
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Type = _eligibleIndicators[i]
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};
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// Add parameters for this indicator
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var baseIndex = 8 + i * 8;
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var paramName = GetParameterName(0); // period
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if (paramName != null && HasParameter(_eligibleIndicators[i], paramName))
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{
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indicator.Period = Convert.ToInt32(genes[baseIndex].Value);
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}
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paramName = GetParameterName(1); // fastPeriods
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if (paramName != null && HasParameter(_eligibleIndicators[i], paramName))
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{
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indicator.FastPeriods = Convert.ToInt32(genes[baseIndex + 1].Value);
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}
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paramName = GetParameterName(2); // slowPeriods
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if (paramName != null && HasParameter(_eligibleIndicators[i], paramName))
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{
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indicator.SlowPeriods = Convert.ToInt32(genes[baseIndex + 2].Value);
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}
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paramName = GetParameterName(3); // signalPeriods
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if (paramName != null && HasParameter(_eligibleIndicators[i], paramName))
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{
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indicator.SignalPeriods = Convert.ToInt32(genes[baseIndex + 3].Value);
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}
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paramName = GetParameterName(4); // multiplier
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if (paramName != null && HasParameter(_eligibleIndicators[i], paramName))
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{
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indicator.Multiplier = Convert.ToDouble(genes[baseIndex + 4].Value);
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}
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paramName = GetParameterName(5); // stochPeriods
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if (paramName != null && HasParameter(_eligibleIndicators[i], paramName))
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{
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indicator.StochPeriods = Convert.ToInt32(genes[baseIndex + 5].Value);
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}
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paramName = GetParameterName(6); // smoothPeriods
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if (paramName != null && HasParameter(_eligibleIndicators[i], paramName))
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{
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indicator.SmoothPeriods = Convert.ToInt32(genes[baseIndex + 6].Value);
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}
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paramName = GetParameterName(7); // cyclePeriods
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if (paramName != null && HasParameter(_eligibleIndicators[i], paramName))
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{
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indicator.CyclePeriods = Convert.ToInt32(genes[baseIndex + 7].Value);
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}
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selected.Add(indicator);
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}
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}
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return selected;
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}
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public TradingBotConfig GetTradingBotConfig(GeneticRequest request)
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{
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var selectedIndicators = GetSelectedIndicators();
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var genes = GetGenes();
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var selectedIndicators = GetSelectedIndicators();
|
||||
|
||||
// Ensure we have at least one indicator
|
||||
if (!selectedIndicators.Any())
|
||||
{
|
||||
selectedIndicators.Add(new GeneticIndicator { Type = _eligibleIndicators[0] });
|
||||
}
|
||||
|
||||
// Get take profit from chromosome (gene 0)
|
||||
var takeProfit = Convert.ToDouble(genes[0].Value);
|
||||
|
||||
// Calculate stop loss based on 1.1:1 risk-reward ratio (gene 1)
|
||||
var stopLoss = Convert.ToDouble(genes[1].Value);
|
||||
|
||||
// Ensure minimum 1.1:1 risk-reward ratio and minimum 0.2% to cover fees
|
||||
var minStopLossForRR = takeProfit / 1.1;
|
||||
var minStopLossForFees = 0.2; // Minimum 0.2% to cover trading fees
|
||||
var minStopLoss = Math.Max(minStopLossForRR, minStopLossForFees);
|
||||
var maxStopLoss = takeProfit - 0.1; // Ensure SL is less than TP with some buffer
|
||||
|
||||
// Adjust stop loss if it doesn't meet the constraints
|
||||
if (stopLoss > maxStopLoss || stopLoss < minStopLoss)
|
||||
{
|
||||
stopLoss = GetRandomInRange((minStopLoss, maxStopLoss));
|
||||
}
|
||||
|
||||
// Build scenario using selected indicators
|
||||
var scenario = new Scenario($"Genetic_{request.RequestId}_Scenario", 1);
|
||||
|
||||
foreach (var geneticIndicator in selectedIndicators)
|
||||
{
|
||||
var indicator = ScenarioHelpers.BuildIndicator(
|
||||
type: geneticIndicator.Type,
|
||||
name: $"Genetic_{geneticIndicator.Type}_{Guid.NewGuid():N}",
|
||||
period: geneticIndicator.Period,
|
||||
fastPeriods: geneticIndicator.FastPeriods,
|
||||
slowPeriods: geneticIndicator.SlowPeriods,
|
||||
signalPeriods: geneticIndicator.SignalPeriods,
|
||||
multiplier: geneticIndicator.Multiplier,
|
||||
stochPeriods: geneticIndicator.StochPeriods,
|
||||
smoothPeriods: geneticIndicator.SmoothPeriods,
|
||||
cyclePeriods: geneticIndicator.CyclePeriods
|
||||
);
|
||||
|
||||
scenario.AddIndicator(indicator);
|
||||
}
|
||||
|
||||
return new TradingBotConfig
|
||||
{
|
||||
@@ -242,28 +560,83 @@ public class TradingBotChromosome : ChromosomeBase
|
||||
BotTradingBalance = request.Balance,
|
||||
IsForBacktest = true,
|
||||
IsForWatchingOnly = false,
|
||||
CooldownPeriod = 0,
|
||||
MaxLossStreak = 3,
|
||||
CooldownPeriod = Convert.ToInt32(genes[2].Value),
|
||||
MaxLossStreak = Convert.ToInt32(genes[3].Value),
|
||||
FlipPosition = false,
|
||||
FlipOnlyWhenInProfit = true,
|
||||
CloseEarlyWhenProfitable = true,
|
||||
MaxPositionTimeHours = 0, // Always 0 to prevent early position cutting
|
||||
UseSynthApi = false,
|
||||
UseForPositionSizing = false,
|
||||
UseForSignalFiltering = false,
|
||||
UseForDynamicStopLoss = false,
|
||||
Scenario = scenario,
|
||||
MoneyManagement = new MoneyManagement
|
||||
{
|
||||
Name = $"Genetic_{request.RequestId}_MM",
|
||||
Timeframe = request.Timeframe,
|
||||
StopLoss = Convert.ToDecimal(genes[_eligibleIndicators.Count].Value),
|
||||
TakeProfit = Convert.ToDecimal(genes[_eligibleIndicators.Count + 1].Value),
|
||||
StopLoss = Convert.ToDecimal(stopLoss),
|
||||
TakeProfit = Convert.ToDecimal(takeProfit),
|
||||
Leverage = 1.0m
|
||||
},
|
||||
RiskManagement = new RiskManagement
|
||||
{
|
||||
RiskTolerance = (RiskToleranceLevel)Convert.ToInt32(genes[_eligibleIndicators.Count + 4].Value)
|
||||
RiskTolerance = RiskToleranceLevel.Moderate
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
private double GetRandomInRange((double min, double max) range)
|
||||
{
|
||||
return _random.NextDouble() * (range.max - range.min) + range.min;
|
||||
}
|
||||
|
||||
private int GetRandomIntInRange((double min, double max) range)
|
||||
{
|
||||
return _random.Next((int)range.min, (int)range.max + 1);
|
||||
}
|
||||
|
||||
private string? GetParameterName(int index)
|
||||
{
|
||||
return index switch
|
||||
{
|
||||
0 => "period",
|
||||
1 => "fastPeriods",
|
||||
2 => "slowPeriods",
|
||||
3 => "signalPeriods",
|
||||
4 => "multiplier",
|
||||
5 => "stochPeriods",
|
||||
6 => "smoothPeriods",
|
||||
7 => "cyclePeriods",
|
||||
_ => null
|
||||
};
|
||||
}
|
||||
|
||||
private bool HasParameter(IndicatorType indicator, string paramName)
|
||||
{
|
||||
return GeneticService.IndicatorParamMapping.ContainsKey(indicator) &&
|
||||
GeneticService.IndicatorParamMapping[indicator].Contains(paramName);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Fitness function for trading bot optimization
|
||||
/// Genetic indicator with parameters
|
||||
/// </summary>
|
||||
public class GeneticIndicator
|
||||
{
|
||||
public IndicatorType Type { get; set; }
|
||||
public int? Period { get; set; }
|
||||
public int? FastPeriods { get; set; }
|
||||
public int? SlowPeriods { get; set; }
|
||||
public int? SignalPeriods { get; set; }
|
||||
public double? Multiplier { get; set; }
|
||||
public int? StochPeriods { get; set; }
|
||||
public int? SmoothPeriods { get; set; }
|
||||
public int? CyclePeriods { get; set; }
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Multi-objective fitness function for trading bot optimization
|
||||
/// </summary>
|
||||
public class TradingBotFitness : IFitness
|
||||
{
|
||||
@@ -297,8 +670,8 @@ public class TradingBotFitness : IFitness
|
||||
_request.RequestId
|
||||
).Result;
|
||||
|
||||
// Calculate fitness based on backtest results
|
||||
var fitness = CalculateFitness(backtest);
|
||||
// Calculate multi-objective fitness based on backtest results
|
||||
var fitness = CalculateMultiObjectiveFitness(backtest, config);
|
||||
|
||||
return fitness;
|
||||
}
|
||||
@@ -309,29 +682,36 @@ public class TradingBotFitness : IFitness
|
||||
}
|
||||
}
|
||||
|
||||
private double CalculateFitness(Backtest backtest)
|
||||
private double CalculateMultiObjectiveFitness(Backtest backtest, TradingBotConfig config)
|
||||
{
|
||||
if (backtest == null || backtest.Score == null)
|
||||
if (backtest == null || backtest.Statistics == null)
|
||||
return 0.1;
|
||||
|
||||
// Use the backtest score as the primary fitness metric
|
||||
var baseFitness = backtest.Score;
|
||||
var stats = backtest.Statistics;
|
||||
|
||||
// Apply additional factors
|
||||
var tradeCount = backtest.Positions?.Count ?? 0;
|
||||
var winRate = backtest.WinRate;
|
||||
var finalPnl = backtest.FinalPnl;
|
||||
// Multi-objective fitness function (matching frontend)
|
||||
var pnlScore = Math.Max(0, (double)stats.TotalPnL / 1000); // Normalize PnL
|
||||
var winRateScore = backtest.WinRate / 100.0; // Normalize win rate
|
||||
var riskRewardScore = Math.Min(2, (double)stats.WinningTrades / Math.Max(1, Math.Abs((double)stats.LoosingTrades)));
|
||||
var consistencyScore = 1 - Math.Abs((double)stats.TotalPnL - (double)backtest.FinalPnl) / Math.Max(1, Math.Abs((double)stats.TotalPnL));
|
||||
|
||||
// Penalize if no trades were made
|
||||
if (tradeCount == 0)
|
||||
return 0.1;
|
||||
// Risk-reward ratio bonus
|
||||
var riskRewardRatio = (double)(config.MoneyManagement.TakeProfit / config.MoneyManagement.StopLoss);
|
||||
var riskRewardBonus = Math.Min(0.2, (riskRewardRatio - 1.1) * 0.1);
|
||||
|
||||
// Bonus for good win rate
|
||||
var winRateBonus = winRate > 0.6 ? 10 : 0;
|
||||
// Drawdown score (normalized to 0-1, where lower drawdown is better)
|
||||
var maxDrawdownPc = Math.Abs((double)stats.MaxDrawdownPc);
|
||||
var drawdownScore = Math.Max(0, 1 - (maxDrawdownPc / 50));
|
||||
|
||||
// Bonus for positive PnL
|
||||
var pnlBonus = finalPnl > 0 ? 20 : 0;
|
||||
// Weighted combination
|
||||
var fitness =
|
||||
pnlScore * 0.3 +
|
||||
winRateScore * 0.2 +
|
||||
riskRewardScore * 0.2 +
|
||||
consistencyScore * 0.1 +
|
||||
riskRewardBonus * 0.1 +
|
||||
drawdownScore * 0.1;
|
||||
|
||||
return baseFitness + winRateBonus + pnlBonus;
|
||||
return Math.Max(0, fitness);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user