feat: integra VRP01 come sleeve del portafoglio (put credit spread + gate IV-rank)

src/portfolio/sleeves.py: _vrp_combo_returns + vrp_sleeve, self-contained in src/
(pricing BS + gate causali inline, DVOL da data/raw). Settimanale->giornaliero col
lump sul giorno di scadenza (preserva lo Sharpe annualizzato, peso costante).

Registry: TP01 0.55 / XS01 0.25 / VRP01 0.20 (TP01 resta maggioranza; VRP e' un
lead modellato, non deploy pieno). TP01+VRP01 monotono: FULL 1.30->1.44, HOLD
0.31->0.40 a peso 20%. Scorrelato a TP01 (+0.01).

Test tests/test_vrp_sleeve.py (5 pass). CLAUDE.md + diario aggiornati.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

tests/test_vrp_sleeve.py

@@ -0,0 +1,61 @@
+"""Test dello sleeve VRP01 (options short-vol: put credit spread + gate IV-rank)."""
+import sys
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+import pytest
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(PROJECT_ROOT))
+
+from src.portfolio.sleeves import (
+    _bs_put, _strike_from_delta, _vrp_combo_returns, vrp_sleeve, _HL_DIR)
+
+_HAS_DVOL = (_HL_DIR / "dvol_btc.parquet").exists() and (_HL_DIR / "dvol_eth.parquet").exists()
+_skip_data = pytest.mark.skipif(not _HAS_DVOL, reason="serve data/raw/dvol_*.parquet (scripts/research/fetch_dvol.py)")
+
+
+def test_bs_put_monotonic_in_strike():
+    """Put piu' ITM (strike piu' alto) vale di piu'."""
+    S, T, sig = 100.0, 7 / 365.25, 0.6
+    vals = [_bs_put(S, K, T, sig) for K in (80, 90, 100, 110)]
+    assert all(b < a for b, a in zip(vals, vals[1:]))           # crescente nello strike
+
+
+def test_strike_from_delta_ordering():
+    """La put venduta delta -0.28 ha strike piu' alto (piu' vicino) della comprata -0.10."""
+    S, T, sig = 100.0, 7 / 365.25, 0.6
+    Ks = _strike_from_delta(S, T, sig, -0.28)
+    Kl = _strike_from_delta(S, T, sig, -0.10)
+    assert Kl < Ks < S                                          # entrambe OTM, long piu' lontana
+
+
+@_skip_data
+def test_sleeve_is_deterministic_and_daily():
+    a = vrp_sleeve().daily()
+    b = _vrp_combo_returns()
+    assert isinstance(a.index, pd.DatetimeIndex) and a.index.tz is not None
+    assert (a.index.normalize() == a.index).all()               # griglia giornaliera
+    # presente ogni giorno nel suo span (nessun buco) -> peso costante nel portafoglio
+    full = pd.date_range(a.index.min(), a.index.max(), freq="1D", tz="UTC")
+    assert len(a) == len(full)
+    np.testing.assert_array_equal(a.values, vrp_sleeve().daily().values)   # deterministico
+
+
+@_skip_data
+def test_gates_reduce_activity():
+    """I gate (IV-rank/VRP/crash-skip) devono lasciare flat parte delle settimane: i giorni con
+    rendimento != 0 sono molto meno del totale (lump settimanale + settimane saltate)."""
+    s = _vrp_combo_returns()
+    active = float((s != 0).mean())
+    assert 0.0 < active < 0.25                                  # ~1/7 (lump weekly) e meno per i gate
+
+
+@_skip_data
+def test_sleeve_positive_and_capped_tail():
+    """Lo sleeve e' profittevole e la coda e' tagliata dal long wing (worst-day moderato)."""
+    s = _vrp_combo_returns()
+    nz = s[s != 0]
+    assert s.sum() > 0                                          # somma rendimenti positiva
+    assert nz.min() > -0.15                                     # defined-risk: nessuna settimana < -15%