Implement Trader V4 training artifact pipeline
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package com.quantai.trader.artifact;
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import java.math.BigDecimal;
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import java.util.Map;
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public record TraderReplayModelFixture(
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DirectionFixture direction,
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EntryFixture entry,
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ContinueFixture continuation,
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ExitFixture exit,
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RiskFixture risk,
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BigDecimal uncertainty,
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BigDecimal oodScore,
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String featureSchemaHash,
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String featureOrderHash,
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String outputSchemaHash
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) {
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public record DirectionFixture(
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BigDecimal longProbWhenMarkGteIndex,
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BigDecimal longProbWhenMarkLtIndex,
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BigDecimal neutralProb
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) {
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}
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public record EntryFixture(
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BigDecimal longEntryProb,
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BigDecimal shortEntryProb,
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BigDecimal longExpectedNetEdgeBps,
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BigDecimal shortExpectedNetEdgeBps
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) {
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}
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public record ContinueFixture(
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BigDecimal longContinueProb,
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BigDecimal shortContinueProb,
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BigDecimal longExpectedContinueEdgeBps,
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BigDecimal shortExpectedContinueEdgeBps
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) {
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}
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public record ExitFixture(
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BigDecimal longExitProb,
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BigDecimal shortExitProb,
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BigDecimal longAdverseMoveBps,
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BigDecimal shortAdverseMoveBps,
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Map<String, BigDecimal> exitReasonScores
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) {
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public ExitFixture {
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exitReasonScores = Map.copyOf(exitReasonScores == null ? Map.of() : exitReasonScores);
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}
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}
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public record RiskFixture(
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BigDecimal marketRiskProb,
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BigDecimal longPositionRiskProb,
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BigDecimal shortPositionRiskProb,
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BigDecimal marketPathRiskBps,
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BigDecimal longPositionPathRiskBps,
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BigDecimal shortPositionPathRiskBps,
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Map<String, BigDecimal> riskReasonScores
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) {
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public RiskFixture {
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riskReasonScores = Map.copyOf(riskReasonScores == null ? Map.of() : riskReasonScores);
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}
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}
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}
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