feat(eval): VaR breach rate metric (#12) + HMM regime detector (#13) — rq-04 prep

#12 — VaR_breach_rate_99_oos_regime_cond metric:
- internal/eval/var.go: VaRBreachRate() + kupiecPOF() + LinearProbePredict() (stdlib math only)
- internal/eval/var_test.go: 8 golden tests (zero/all breach, perfect calibration, boundary)
- cmd/eval/main.go: -metric var flag (no-leakage probe → VaR → Kupiec P)
- scripts/var_breach.py: Python equivalent with METRIC_KEY constant (13 TDD tests)
- train.py LOCKED VaR EVAL BLOCK: writes VaR_breach_rate_99_oos_regime_cond + kupiec_p to metrics.json
- Fixed bug: train.py used bare 'os' before import; now uses module-level '_os' consistently

#13 — HMM regime detector + JEPA conditioning seam:
- scripts/prepare_regime.py: GaussianHMM (diag, 3-state) on realized_vol; states sorted by mean vol
  (0=calm, 1=stressed, 2=crisis); deterministic (random_state=42); outputs eurusd_regime.parquet
- tests/test_regime.py: 11 TDD tests (dtype, states, determinism, vol sort, daily fallback)
- train.py: JEPA_ENABLE_REGIME toggle + REGIME CONDITIONING SEAM (concat baseline, agent-editable)
- requirements.txt: hmmlearn>=0.3, scikit-learn>=1.4

78 Python + all Go tests green.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

cmd/eval/main.go

@@ -83,6 +83,32 @@ func main() {
 		fmt.Printf(`{"metric":"effective_rank","value":%.6f}`+"\n", er)
 		log.Info("effective rank", "erank", fmt.Sprintf("%.2f", er))
 
+	case "var":
+		// Parametric 99% VaR breach rate from probe predictions vs actual realized vol.
+		// Requires train_embeddings (for no-leakage probe fit) and realized_vol (OOS).
+		if len(d.RealizedVol) == 0 {
+			log.Error("var requires realized_vol in embeddings.json")
+			os.Exit(1)
+		}
+		var predVol []float64
+		if len(d.TrainEmbeddings) > 0 {
+			trEmb, mu, sd := standardiseCompute(d.TrainEmbeddings)
+			oosEmb := applyStandardise(d.Embeddings, mu, sd)
+			predVol = eval.LinearProbePredict(trEmb, d.TrainRealizedVol, oosEmb, 1e-3)
+		} else {
+			oosEmb, mu, sd := standardiseCompute(d.Embeddings)
+			n70 := int(float64(len(oosEmb)) * 0.7)
+			oos70 := applyStandardise(d.Embeddings[n70:], mu, sd)
+			predVol = eval.LinearProbePredict(oosEmb[:n70], d.RealizedVol[:n70], oos70, 1e-3)
+			d.RealizedVol = d.RealizedVol[n70:]
+		}
+		const z99 = 2.326
+		breachRate, kupiecP := eval.VaRBreachRate(predVol, d.RealizedVol, z99)
+		fmt.Printf(`{"metric":"VaR_breach_rate_99_oos_regime_cond","value":%.6f,"kupiec_p":%.6f}`+"\n",
+			breachRate, kupiecP)
+		log.Info("VaR breach rate 99%", "breach_rate", fmt.Sprintf("%.4f", breachRate),
+			"kupiec_p", fmt.Sprintf("%.4f", kupiecP))
+
 	default:
 		log.Error("unknown metric", "metric", *metric)
 		os.Exit(1)