Phase Segmentation: Full implementation with improved RegimeClassifier
Complete market regime classification and phase-specific metrics calculation. Files: - src/KArtSell.Modules.ModelOperations/ShadowRun/RegimeClassifier.cs (improved) Threshold-based trend detection (Bull >2%, Bear <-2%, Sideways within band) Deterministic PIT-safe classification, no lookahead bias - src/KArtSell.Modules.ModelOperations/ShadowRun/PhaseMetricsCalculator.cs (new) Per-phase metrics: Sharpe (annualized), Calmar, Max DD, Win Rate Stateless calculation using only provided daily returns - src/KArtSell.Modules.ModelOperations/ShadowRun/PhaseSegmentation.cs (new) Orchestrator combining RegimeClassifier + PhaseMetricsCalculator Groups returns by regime, calculates per-phase metrics Returns PhaseBreakdownDto with all four market conditions - tests/KArtSell.Integration.Tests/PhaseSegmentationTests.cs (updated) Removed temporary implementations, now uses module classes Test status: 8/8 PASSING AGENTS.md v16.0: ✅ Pattern: Vertical component, single responsibility per class ✅ Simplicity: Clear threshold-based trend detection ✅ Maturity: Contract-first, test-first, implementation verified ✅ Necessity: Supports "복수 국면 OOS" requirement from README Next: Integrate PhaseSegmentation into ShadowRunJob workflow. Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
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@@ -5,13 +5,14 @@ namespace KArtSell.Integration.Tests;
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/// <summary>
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/// Phase segmentation tests: regime classification + metrics per phase.
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/// Tests use production implementations from ShadowRun module.
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/// </summary>
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public sealed class PhaseSegmentationTests
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{
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[Fact]
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public void RegimeClassifier_BullTrend_ClassifiesAllAsBull()
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{
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// Arrange: Simulate bull market (30-day MA trending up)
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// Arrange: Simulate bull market (5% increase)
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var bars = new List<(DateOnly, decimal)>
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{
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(new DateOnly(2024, 1, 2), 100m),
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@@ -26,13 +27,13 @@ public sealed class PhaseSegmentationTests
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var regimes = RegimeClassifier.Classify(bars);
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// Assert
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Assert.All(regimes, regime => Assert.Equal(MarketRegime.Bull, regime.regime));
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Assert.All(regimes, regime => Assert.Equal(MarketRegime.Bull, regime.Regime));
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}
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[Fact]
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public void RegimeClassifier_BearTrend_ClassifiesAllAsBear()
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{
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// Arrange: Simulate bear market (30-day MA trending down)
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// Arrange: Simulate bear market (4.76% decrease)
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var bars = new List<(DateOnly, decimal)>
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{
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(new DateOnly(2024, 1, 2), 105m),
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@@ -47,13 +48,13 @@ public sealed class PhaseSegmentationTests
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var regimes = RegimeClassifier.Classify(bars);
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// Assert
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Assert.All(regimes, regime => Assert.Equal(MarketRegime.Bear, regime.regime));
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Assert.All(regimes, regime => Assert.Equal(MarketRegime.Bear, regime.Regime));
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}
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[Fact]
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public void RegimeClassifier_Sideways_ClassifiesAllAsSideways()
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{
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// Arrange: Simulate sideways market (price oscillates ±5% around MA)
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// Arrange: Simulate sideways market (0% net change)
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var bars = new List<(DateOnly, decimal)>
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{
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(new DateOnly(2024, 1, 2), 100m),
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@@ -68,28 +69,28 @@ public sealed class PhaseSegmentationTests
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var regimes = RegimeClassifier.Classify(bars);
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// Assert
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Assert.All(regimes, regime => Assert.Equal(MarketRegime.Sideways, regime.regime));
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Assert.All(regimes, regime => Assert.Equal(MarketRegime.Sideways, regime.Regime));
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}
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[Fact]
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public void PhaseMetrics_BullPhase_CalculatesCorrectMetrics()
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{
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// Arrange
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var dailyReturns = new List<decimal> { 0.01m, 0.02m, 0.01m, -0.005m, 0.015m };
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// Arrange: 5 winning days
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var dailyReturns = new List<decimal> { 0.01m, 0.02m, 0.01m, 0.005m, 0.015m };
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// Act
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var metrics = PhaseMetricsCalculator.Calculate(dailyReturns);
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// Assert
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Assert.True(metrics.TradingDays == 5);
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Assert.True(metrics.WinRate > 0 && metrics.WinRate <= 1, $"WinRate should be [0,1], got {metrics.WinRate}");
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Assert.Equal(5, metrics.TradingDays);
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Assert.True(metrics.WinRate > 0 && metrics.WinRate <= 1);
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Assert.True(metrics.Return > 0, "Bull phase should have positive return");
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}
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[Fact]
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public void PhaseMetrics_EmptyPhase_ReturnsZeros()
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{
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// Arrange
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// Arrange: No returns
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var dailyReturns = new List<decimal>();
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// Act
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@@ -117,7 +118,7 @@ public sealed class PhaseSegmentationTests
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[Fact]
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public void PhaseBreakdown_MultiPhase_SumsDaysCorrectly()
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{
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// Arrange: Create a multi-phase scenario
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// Arrange: Multi-phase portfolio (bull days + bear days)
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var dailyReturns = new List<(DateOnly, decimal)>
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{
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(new DateOnly(2024, 1, 2), 0.01m),
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@@ -127,14 +128,10 @@ public sealed class PhaseSegmentationTests
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(new DateOnly(2024, 1, 8), -0.01m),
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};
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var classifier = new RegimeClassifier();
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var metricsCalc = new PhaseMetricsCalculator();
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var segmenter = new PhaseSegmentation(classifier, metricsCalc);
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// Act
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var breakdown = PhaseSegmentation.StaticSegment(dailyReturns, classifier, metricsCalc);
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var breakdown = PhaseSegmentation.Segment(dailyReturns);
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// Assert: Sum of trading days should equal total
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// Assert: Sum of trading days equals input count
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var totalDays = breakdown.BullMarket.TradingDays
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+ breakdown.BearMarket.TradingDays
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+ breakdown.Sideways.TradingDays
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@@ -145,7 +142,7 @@ public sealed class PhaseSegmentationTests
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[Fact]
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public void Segmentation_ReturnsValidMetrics_AllFieldsPopulated()
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{
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// Arrange
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// Arrange: Minimal multi-day scenario
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var dailyReturns = new List<(DateOnly, decimal)>
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{
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(new DateOnly(2024, 1, 2), 0.01m),
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@@ -153,131 +150,16 @@ public sealed class PhaseSegmentationTests
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(new DateOnly(2024, 1, 4), -0.005m),
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};
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var classifier = new RegimeClassifier();
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var metricsCalc = new PhaseMetricsCalculator();
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var segmenter = new PhaseSegmentation(classifier, metricsCalc);
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// Act
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var breakdown = PhaseSegmentation.StaticSegment(dailyReturns, classifier, metricsCalc);
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var breakdown = PhaseSegmentation.Segment(dailyReturns);
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// Assert: All metrics non-null
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// Assert: All metrics non-null and valid
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Assert.NotNull(breakdown.BullMarket);
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Assert.NotNull(breakdown.BearMarket);
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Assert.NotNull(breakdown.Sideways);
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Assert.NotNull(breakdown.HighVolatility);
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// Assert: Metric fields valid
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Assert.True(breakdown.BullMarket.WinRate >= 0 && breakdown.BullMarket.WinRate <= 1);
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Assert.True(breakdown.BullMarket.Sharpe >= -5 && breakdown.BullMarket.Sharpe <= 5);
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}
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}
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/// <summary>
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/// Regime classifier: Bull, Bear, Sideways, HighVolatility
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/// </summary>
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public sealed class RegimeClassifier
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{
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public static List<(DateOnly Date, MarketRegime regime)> Classify(List<(DateOnly, decimal)> prices)
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{
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var result = new List<(DateOnly, MarketRegime)>();
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if (prices.Count < 30)
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return prices.Select(p => (p.Item1, MarketRegime.Sideways)).ToList();
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// Simplified: classify based on trend
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var avgPrice = prices.Average(p => p.Item2);
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var recentAvg = prices.TakeLast(5).Average(p => p.Item2);
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foreach (var (date, price) in prices)
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{
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var regime = recentAvg > avgPrice
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? MarketRegime.Bull
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: recentAvg < avgPrice
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? MarketRegime.Bear
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: MarketRegime.Sideways;
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result.Add((date, regime));
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}
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return result;
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}
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}
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/// <summary>
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/// Calculate metrics for a single phase
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/// </summary>
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public sealed class PhaseMetricsCalculator
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{
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public static PhaseMetricsDto Calculate(List<decimal> returns)
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{
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if (returns.Count == 0)
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return new PhaseMetricsDto(0, 0m, 0m, 0m, 0m);
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var totalReturn = (decimal)(returns.Aggregate(1.0, (acc, r) => acc * (double)(1 + r)) - 1);
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var winRate = (decimal)returns.Count(r => r > 0) / returns.Count;
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var mean = returns.Average();
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var variance = returns.Average(r => (r - mean) * (r - mean));
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var stdDev = (decimal)Math.Sqrt((double)variance);
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var sharpe = stdDev > 0 ? (mean / stdDev) * (decimal)Math.Sqrt(252) : 0m;
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// Simplified max drawdown
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var cumulative = 1m;
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var peak = 1m;
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var maxDD = 0m;
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foreach (var r in returns)
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{
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cumulative *= (1 + r);
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if (cumulative > peak) peak = cumulative;
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var dd = (cumulative - peak) / peak;
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if (dd < maxDD) maxDD = dd;
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}
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return new PhaseMetricsDto(
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TradingDays: returns.Count,
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Return: totalReturn,
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Sharpe: sharpe,
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WinRate: winRate,
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MaxDrawdown: Math.Abs(maxDD));
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}
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}
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/// <summary>
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/// Orchestrates phase segmentation: classify regimes + calculate per-phase metrics
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/// </summary>
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public sealed class PhaseSegmentation
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{
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private readonly RegimeClassifier _classifier;
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private readonly PhaseMetricsCalculator _metricsCalc;
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public PhaseSegmentation(RegimeClassifier classifier, PhaseMetricsCalculator metricsCalc)
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{
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_classifier = classifier;
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_metricsCalc = metricsCalc;
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}
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public static PhaseBreakdownDto StaticSegment(List<(DateOnly, decimal)> dailyReturns, RegimeClassifier classifier, PhaseMetricsCalculator metricsCalc)
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{
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var regimes = RegimeClassifier.Classify(dailyReturns.Select(r => (r.Item1, (decimal)100)).ToList());
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var byRegime = new Dictionary<MarketRegime, List<decimal>>();
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for (int i = 0; i < dailyReturns.Count; i++)
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{
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var regime = regimes[i].regime;
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if (!byRegime.ContainsKey(regime))
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byRegime[regime] = new List<decimal>();
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byRegime[regime].Add(dailyReturns[i].Item2);
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}
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return new PhaseBreakdownDto(
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BullMarket: PhaseMetricsCalculator.Calculate(byRegime.GetValueOrDefault(MarketRegime.Bull, new())),
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BearMarket: PhaseMetricsCalculator.Calculate(byRegime.GetValueOrDefault(MarketRegime.Bear, new())),
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Sideways: PhaseMetricsCalculator.Calculate(byRegime.GetValueOrDefault(MarketRegime.Sideways, new())),
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HighVolatility: PhaseMetricsCalculator.Calculate(byRegime.GetValueOrDefault(MarketRegime.HighVolatility, new())));
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}
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}
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public enum MarketRegime { Bull, Bear, Sideways, HighVolatility }
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public record PhaseMetricsDto(int TradingDays, decimal Return, decimal Sharpe, decimal WinRate, decimal MaxDrawdown);
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public record PhaseBreakdownDto(PhaseMetricsDto BullMarket, PhaseMetricsDto BearMarket, PhaseMetricsDto Sideways, PhaseMetricsDto HighVolatility);
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