jepa-fx-risk/internal/eval/var_test.go

package eval_test

import (
	"math"
	"testing"

	"gitea.d-ma.be/mathias/jepa-fx-risk/internal/eval"
)

// ── VaRBreachRate golden tests ──────────────────────────────────────────────
//
// VaR_99_t  = predVol[t] × z99   (parametric 99% normal VaR)
// breach_t  = actualVol[t] > VaR_99_t
// breachRate = mean(breach_t)
// kupiecP   = Kupiec POF p-value (chi²(1) test, H0: breach rate = 1%)

func TestVaRBreachRate_ZeroBreaches(t *testing.T) {
	// 0.02 < 0.01×2.326=0.02326 → no breaches
	pred := []float64{0.01, 0.01, 0.01}
	act := []float64{0.02, 0.02, 0.02}
	rate, _ := eval.VaRBreachRate(pred, act, 2.326)
	if rate != 0 {
		t.Fatalf("want rate=0, got %.4f", rate)
	}
}

func TestVaRBreachRate_AllBreach(t *testing.T) {
	// 0.03 > 0.02326 → all breach
	pred := []float64{0.01, 0.01}
	act := []float64{0.03, 0.03}
	rate, _ := eval.VaRBreachRate(pred, act, 2.326)
	if math.Abs(rate-1.0) > 1e-9 {
		t.Fatalf("want rate=1.0, got %.4f", rate)
	}
}

func TestVaRBreachRate_Golden(t *testing.T) {
	// n=10, 2 breaches at indices 0 and 2 → rate=0.2
	// Kupiec: p_hat=0.2 vs p0=0.01 → strongly reject H0 (p < 0.05)
	pred := make([]float64, 10)
	act := make([]float64, 10)
	for i := range pred {
		pred[i] = 0.01
		act[i] = 0.01 // no breach: 0.01 < 0.02326
	}
	act[0] = 0.03 // breach
	act[2] = 0.03 // breach

	rate, kupiecP := eval.VaRBreachRate(pred, act, 2.326)

	if math.Abs(rate-0.2) > 1e-9 {
		t.Fatalf("breach rate: want 0.2, got %.4f", rate)
	}
	if kupiecP > 0.05 {
		t.Fatalf("kupiec p-value: want <0.05 (strong reject H0), got %.4f", kupiecP)
	}
}

func TestVaRBreachRate_PerfectCalibration(t *testing.T) {
	// n=100, exactly 1 breach → p_hat=0.01=p0 → LR=0 → kupiecP≈1.0
	n := 100
	pred := make([]float64, n)
	act := make([]float64, n)
	for i := range pred {
		pred[i] = 0.01
		act[i] = 0.015 // < 0.02326, no breach
	}
	act[0] = 0.025 // > 0.02326, breach

	rate, kupiecP := eval.VaRBreachRate(pred, act, 2.326)

	if math.Abs(rate-0.01) > 1e-9 {
		t.Fatalf("breach rate: want 0.01, got %.4f", rate)
	}
	if kupiecP < 0.9 {
		t.Fatalf("kupiec p-value: want ≈1.0 (well calibrated), got %.4f", kupiecP)
	}
}

func TestVaRBreachRate_EmptyInput(t *testing.T) {
	rate, kupiecP := eval.VaRBreachRate(nil, nil, 2.326)
	if rate != 0 || kupiecP != 1 {
		t.Fatalf("empty: want (0,1), got (%.4f,%.4f)", rate, kupiecP)
	}
}

func TestVaRBreachRate_LenMismatch(t *testing.T) {
	rate, kupiecP := eval.VaRBreachRate([]float64{0.01}, []float64{0.01, 0.02}, 2.326)
	if rate != 0 || kupiecP != 1 {
		t.Fatalf("mismatch: want (0,1), got (%.4f,%.4f)", rate, kupiecP)
	}
}

func TestVaRBreachRate_Z99Default(t *testing.T) {
	// z99=2.326 is the canonical value; test that boundary case works
	// VaR = 0.01 × 2.326 = 0.02326
	// actual = 0.02326 → NOT a breach (strict >)
	pred := []float64{0.01}
	act := []float64{0.02326}
	rate, _ := eval.VaRBreachRate(pred, act, 2.326)
	if rate != 0 {
		t.Fatalf("boundary: exactly at VaR is not a breach; want rate=0, got %.4f", rate)
	}
}

// ── LinearProbePredict ──────────────────────────────────────────────────────

func TestLinearProbePredict_PerfectLinear(t *testing.T) {
	// y = x; predictions should match targets closely
	n := 20
	trainEmb := make([][]float64, n)
	trainY := make([]float64, n)
	testEmb := make([][]float64, 5)
	testY := []float64{5, 10, 15, 20, 25}
	for i := range trainEmb {
		trainEmb[i] = []float64{float64(i)}
		trainY[i] = float64(i)
	}
	for i := range testEmb {
		testEmb[i] = []float64{testY[i]}
	}
	preds := eval.LinearProbePredict(trainEmb, trainY, testEmb, 1e-3)
	if len(preds) != len(testEmb) {
		t.Fatalf("len: want %d, got %d", len(testEmb), len(preds))
	}
	for i, p := range preds {
		if math.Abs(p-testY[i]) > 1.0 {
			t.Fatalf("pred[%d]: want ≈%.1f, got %.4f", i, testY[i], p)
		}
	}
}

func TestLinearProbePredict_EmptyTrain(t *testing.T) {
	preds := eval.LinearProbePredict(nil, nil, [][]float64{{1.0}}, 1e-3)
	if len(preds) != 0 {
		t.Fatalf("empty train: want nil/empty preds, got len=%d", len(preds))
	}
}