docs: aggiornamento Phase 5 — IV-RV gate, F+D+A, backtest, option chain

- 01-strategy-rules.md:
  * §2.8 (filtri quant: dealer gamma + liquidation risk)
  * §2.9 (IV richness gate, opt-in, default disabled)
  * §3.2 — variante delta_by_dvol step-function
  * §7-bis.1 (vol-collapse harvest D)
  * §7-bis.2 (graduated profit-take C — scaffolding)
  * §7-bis.3 (auto-pause su drawdown F)

- 05-data-model.md:
  * `system_state.auto_pause_until / _reason` (migration 0004)
  * Nuova tabella `option_chain_snapshots` (migration 0005)
  * Tabella migrations completa (1→5)

- 13-strategia-spiegata.md:
  * §4-quinquies — catena opzioni storica (Phase 5):
    cosa raccoglie, cosa sblocca, CLI `option-chain
    trigger|analyze`.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

docs/01-strategy-rules.md

@@ -41,6 +41,34 @@ sono vere:
    patrimonio totale (correlazione direzionale già alta).
 8. **Liquidità degli strike candidati** entro le soglie del §3.
 
+### 2.8 Filtri quant (introdotti in Phase 4)
+
+Due gate aggiuntivi che leggono i campi del `market_snapshot`:
+
+- **Dealer net gamma > 0** (default: `dealer_gamma_min: 0`). Long-gamma
+  regime = dealer hedge che sopprime la vol → ideale per vendere
+  credit spread. Short-gamma = vol-amplifying flow, statisticamente
+  perdente. Disattivabile via `dealer_gamma_filter_enabled: false`.
+- **Liquidation risk ≠ high** (default: `liquidation_filter_enabled:
+  true`). Salta entry quando il modulo sentiment flagga uno squeeze
+  imminente su long o short side.
+
+### 2.9 IV richness gate (introdotto in Phase 5, opt-in)
+
+Filtro a maggior impatto sul win-rate. **Disabilitato** di default
+nella golden config — abilitato esplicitamente nel profilo
+`strategy.aggressiva.yaml`:
+
+- `iv_minus_rv_filter_enabled: true|false` — master switch.
+- `iv_minus_rv_min: <pt vol>` — soglia: l'entry passa solo se la
+  IV implicita 30g supera la realized vol 30g di almeno tot punti.
+  Default 0; valori sensati 3-5 dopo calibrazione sui dati raccolti.
+
+Razionale: il selling vol nudo è strutturalmente neutro a win-rate
+70-72%. L'edge della strategia esiste solo quando il premio è
+"ricco" — IV30 > RV30 + N. Vedere `13-strategia-spiegata.md §4-quater`
+per il razionale completo.
+
 Se anche **una sola** condizione fallisce → **no entry**, log con motivo,
 ritento la settimana successiva.
 
@@ -77,6 +105,20 @@ assoluto.
 | Distanza minima OTM | 15% (anche se delta è dentro tolleranza) |
 | Distanza massima OTM | 25% |
 
+**Variante dinamica per regime DVOL (Phase 5, opt-in).** Il campo
+`short_strike.delta_by_dvol` (lista step-function) sostituisce il
+delta target singolo con bande ordinate per `dvol_under`: a DVOL
+bassa il bot prende delta più alto (più premio), a DVOL alta sceglie
+delta più basso (più safety distance). Lista vuota = comportamento
+classico col delta target sopra. Esempio bande nel profilo
+`strategy.aggressiva.yaml`:
+
+| dvol_under | delta_target | delta_min | delta_max |
+|---|---|---|---|
+| 50 | 0.15 | 0.13 | 0.17 |
+| 70 | 0.12 | 0.10 | 0.15 |
+| 90 | 0.10 | 0.08 | 0.12 |
+
 Se nessuno strike disponibile rientra in entrambe le tolleranze → no entry.
 
 ### 3.3 Strike long (protezione)
@@ -179,6 +221,49 @@ Per ogni posizione aperta, il rule engine valuta in ordine:
 
 L'ordine è importante: il primo trigger soddisfatto vince.
 
+## 7-bis. Estensioni opzionali (Phase 5)
+
+Tre miglioramenti opt-in al decision loop. Tutti **disabled** di
+default nella golden config; il profilo `strategy.aggressiva.yaml`
+li abilita.
+
+### 7-bis.1 Vol-collapse harvest (D)
+
+Inserito tra il profit-take §7.1 e lo stop-loss §7.2:
+
+> Se `vol_harvest_dvol_decrease > 0`, siamo in profit
+> (`debit < credit`) E `DVOL_now ≤ DVOL_entry − vol_harvest_dvol_decrease`,
+> `decision = CLOSE_VOL_HARVEST`.
+
+Razionale: edge IV-RV già catturato, vol attesa rientrata, non c'è
+motivo di tenere fino al profit-take. Default disabilitato (`0`);
+profilo aggressivo: `15` punti vol.
+
+### 7-bis.2 Profit-take graduale (C — scaffolding)
+
+Schema in place per chiusure parziali; pipeline runtime di
+chiusura partial-close NON ancora wirata. Default vuoto. Quando
+popolato, ogni livello `{mark_at_pct_credit, close_pct_of_initial_contracts}`
+emette un'azione `CLOSE_PROFIT_PARTIAL` advisory che il runtime
+attualmente ignora. Il completamento richiede refactor del position
+model (contracts_open vs contracts_initial) — PR dedicato.
+
+### 7-bis.3 Auto-pause su drawdown (F)
+
+Circuit breaker sopra il kill-switch tecnico. Valutato all'inizio di
+ogni entry-cycle:
+
+> Se `auto_pause.enabled` e P/L cumulato delle ultime
+> `lookback_trades` posizioni chiuse < `−max_drawdown_pct ×
+> capitale_corrente`, l'engine si auto-mette in pausa per
+> `pause_weeks` settimane (skip-week mode).
+
+Difende dai regime change non rilevati dai filtri quant. La pausa
+si annulla automaticamente alla scadenza, oppure manualmente con
+`UPDATE system_state SET auto_pause_until = NULL`. Default
+disabilitato; profilo aggressivo: lookback 5 trade, soglia 15%, 2
+settimane di pausa.
+
 ## 8. Esecuzione di apertura
 
 1. Engine costruisce **combo order Deribit** (un solo ordine atomico

docs/05-data-model.md

@@ -202,7 +202,9 @@ CREATE TABLE system_state (
     last_kelly_calib   TEXT,
     config_version     TEXT NOT NULL,
     started_at         TEXT NOT NULL,
-    last_audit_hash    TEXT             -- aggiunto dalla migration 0002
+    last_audit_hash    TEXT,            -- aggiunto dalla migration 0002
+    auto_pause_until   TEXT,            -- aggiunto dalla migration 0004 (§7-bis.3)
+    auto_pause_reason  TEXT             -- aggiunto dalla migration 0004
 );
 ```
 
@@ -212,6 +214,54 @@ Al boot l'orchestrator confronta questo valore con il tail del file
 `audit.log`: discrepanza → kill switch CRITICAL, vedi
 `07-risk-controls.md`.
 
+I campi `auto_pause_until` / `auto_pause_reason` implementano il
+circuit breaker §7-bis.3 (pausa automatica su drawdown rolling).
+NULL = engine attivo.
+
+### `option_chain_snapshots`
+
+Snapshot della catena opzioni Deribit prelevata settimanalmente
+(cron `55 13 * * MON`, 5 minuti prima del trigger entry). Ogni
+tick contiene un quote per strumento entro la finestra
+`[dte_min, dte_max]` di config; tutti i quote prelevati nello stesso
+tick condividono ``timestamp``. Migration `0005`.
+
+```sql
+CREATE TABLE option_chain_snapshots (
+    timestamp        TEXT NOT NULL,
+    asset            TEXT NOT NULL,
+    instrument_name  TEXT NOT NULL,
+    strike           TEXT NOT NULL,
+    expiry           TEXT NOT NULL,
+    option_type      TEXT NOT NULL CHECK (option_type IN ('C','P')),
+    bid              TEXT,
+    ask              TEXT,
+    mid              TEXT,
+    iv               TEXT,
+    delta            TEXT,
+    gamma            TEXT,
+    theta            TEXT,
+    vega             TEXT,
+    open_interest    INTEGER,
+    volume_24h       INTEGER,
+    book_depth_top3  INTEGER,
+    PRIMARY KEY (timestamp, instrument_name)
+) WITHOUT ROWID;
+```
+
+Indici: `(asset, timestamp DESC)` per listing recenti, `(asset,
+expiry)` per query per scadenza specifica. ``book_depth_top3`` è
+NULL by design — il collector non chiama l'order book per ogni
+strike per non saturare l'API; lo legge il liquidity gate live solo
+sugli strike candidati al picker.
+
+**Sblocca**: il backtest non-stilizzato (modulo `core/backtest.py`
+con prezzi reali invece di Black-Scholes), la calibrazione empirica
+dello skew premium, la validazione ex-post dello strike picker.
+
+Volume atteso: ~50 strike × 3 scadenze × 1 snapshot/settimana ×
+17 colonne ≈ 12 KB/settimana, ~600 KB/anno.
+
 ## Log file
 
 Sotto `data/log/` un file per giorno: `cerbero-bite-YYYY-MM-DD.jsonl`.
@@ -289,11 +339,18 @@ da altri processi (es. CLI `state inspect`) non vedano stati parziali.
 
 ## Migrations
 
-Lo schema viene tracciato con il counter `PRAGMA user_version`. La
-prima volta `0001_init.sql` viene applicato e versione → 1; alla
-seconda esecuzione (o su DB già a versione 1) `0002_audit_anchor.sql`
-viene applicato e versione → 2. `state.db.run_migrations` è
-idempotente. Nessun rollback supportato (migrations forward-only).
+Lo schema viene tracciato con il counter `PRAGMA user_version`.
+`state.db.run_migrations` applica in ordine ogni file
+`NNNN_<name>.sql` con versione superiore a quella corrente,
+idempotente, forward-only:
+
+| Versione | File | Cosa aggiunge |
+|---|---|---|
+| 1 | `0001_init.sql` | tabelle base (positions, decisions, ...) |
+| 2 | `0002_audit_anchor.sql` | `system_state.last_audit_hash` |
+| 3 | `0003_market_snapshots.sql` | tabella `market_snapshots` |
+| 4 | `0004_auto_pause.sql` | `system_state.auto_pause_until / _reason` |
+| 5 | `0005_option_chain_snapshots.sql` | tabella `option_chain_snapshots` |
 
 ## Backup
 

docs/13-strategia-spiegata.md

@@ -532,6 +532,110 @@ quella che il sistema parte ad eseguire.
 
 ---
 
+## 4-quater. IV richness gate (§2.9): il filtro che alza il win-rate
+
+Il filtro a maggior impatto sull'edge è anche il più semplice da
+descrivere: **non vendere vol quando la IV non sta pagando un margine
+misurabile sopra la RV**. È implementato come gate hard nel
+`validate_entry`:
+
+```
+if iv_minus_rv_filter_enabled and iv_minus_rv < iv_minus_rv_min:
+    skip entry
+```
+
+con due parametri in `entry:` di `strategy.yaml`:
+
+| Parametro | Default | Effetto |
+|---|---|---|
+| `iv_minus_rv_filter_enabled` | `false` (golden) / `true` (aggressiva) | Master switch del gate |
+| `iv_minus_rv_min` | `0` (golden) / `3` (aggressiva) | Soglia in punti vol che IV30g − RV30g deve eccedere |
+
+Il dato è già raccolto in `market_snapshots.iv_minus_rv` ogni 15
+minuti. Il gate consulta l'ultimo tick disponibile al momento
+dell'entry cycle (non un percentile rolling — quello è il prossimo
+step di calibrazione, vedi §4-quinquies in roadmap).
+
+**Profili di default ragionati.**
+
+- **Conservativa / golden config**: `enabled=false, min=0`. Tutti i
+  setup passano questo gate, anche con IV-RV negativa. Motivo: nei
+  primi 8 turni di lunedì non si hanno abbastanza tick per stabilire
+  che soglia ha senso nel proprio regime. Lasciamo la pagina
+  `📐 Calibrazione` mostrare la distribuzione e poi alziamo
+  manualmente.
+- **Aggressiva**: `enabled=true, min=3`. Il profilo aggressivo già di
+  suo prende size più grande; pretendere `IV-RV ≥ 3 vol points` come
+  prerequisito è coerente — se stai betting più grosso, vuoi
+  win-rate più alto. La soglia 3 è conservativa; la letteratura
+  short-vol systematic suggerisce 5 dopo calibrazione.
+
+**Cosa cambia nel P/L atteso quando attivi il gate.**
+
+Il gate **riduce** il numero di entry (saltiamo settimane con premio
+magro) ma **alza** la qualità di quelle che passano (premio ricco =
+win-rate empirico più alto). Effetto netto sul P/L annuo:
+
+- Trade/anno: 18 → 12-14 (skip più aggressivo)
+- Win-rate atteso: 0.72 → 0.78-0.80
+- E[trade] netto: +0.6 USD → +4-6 USD per contratto
+- **P/L annuo proiettato sale anche se i trade scendono**, perché
+  ogni trade ha edge più alto.
+
+La pagina `📚 Strategia` ha lo slider win-rate già coerente con
+questa logica: muovi da 0.72 a 0.78 e vedi l'APR scattare.
+
+**Roadmap di hardening (passi successivi al merge di questo PR).**
+
+1. **Soglia adattiva**: sostituire `iv_minus_rv_min: 3` con un valore
+   calcolato a runtime come `P25 rolling 60d` di `market_snapshots.iv_minus_rv`.
+2. **Vol-of-vol guard**: bloccare entry quando `dvol` è cambiato di
+   ≥5 punti nelle ultime 24h, anche se `iv_minus_rv` è alto (regime
+   instabile).
+3. **Multi-asset (ETH+BTC)**: come da §4-ter, sblocca il
+   moltiplicatore 2× sulle opportunità a parità di filtri.
+
+## 4-quinquies. Catena opzioni storica (Phase 5)
+
+In aggiunta a `market_snapshots` (cron `*/15`), il bot raccoglie
+ora una seconda fonte di dati: la **catena opzioni Deribit completa**
+ogni lunedì alle 13:55 UTC (5 minuti prima del trigger entry).
+
+Tabella `option_chain_snapshots` — vedi `05-data-model.md` per lo
+schema. Cosa registra per ogni strumento entro la finestra
+`[dte_min, dte_max]`:
+
+| Campo | Cosa misura | A che serve |
+|---|---|---|
+| `bid` / `ask` / `mid` | Prezzi reali Deribit in ETH | P/L reale per backtest |
+| `iv` | IV implicita allo strike | Calibrazione skew premium |
+| `delta`/`gamma`/`theta`/`vega` | Greeks | Sizing + risk monitoring |
+| `open_interest` / `volume_24h` | Liquidità | Validazione gate §4 |
+
+**Cosa sblocca:**
+
+- **Backtest non-stilizzato**: il modulo `core/backtest.py` può
+  sostituire la stima Black-Scholes (con `skew_premium` hardcoded a
+  1.5×) leggendo i `mid` reali. Numeri da "stime ex-ante per
+  ranking" a "P/L empirico per dimensionare capitale".
+- **Calibrazione empirica dello skew**: rapporto fra prezzi
+  Deribit reali e BS pulito → valore data-driven invece di stima a
+  istinto. Va fatto dopo 4-8 settimane di accumulo.
+- **Validazione ex-post strike picker**: "il delta-0.12 era davvero
+  a 25% OTM in quella settimana?" diventa una `SELECT`.
+
+**Strumenti CLI:**
+
+- `cerbero-bite option-chain trigger` — esegue UNA volta il
+  collector senza aspettare il cron. Utile per test e per popolare
+  prima del primo lunedì utile.
+- `cerbero-bite option-chain analyze [--bias bull_put|bear_call]` —
+  legge l'ultimo snapshot, simula il selector di strike con la
+  strategy passata e stampa: short/long strike, delta, width,
+  credito reale, ratio credit/width, PASS/FAIL del gate
+  `credit_to_width_ratio_min`. Risponde in tempo reale: "il rule
+  engine aprirebbe un trade adesso?".
+
 ## 5. Come leggere il dato giorno per giorno
 
 Tre euristiche operative sui campi raccolti:

src/cerbero_bite/cli.py

@@ -13,7 +13,7 @@ import asyncio
 import os
 import sys
 from collections.abc import Callable
-from datetime import UTC, datetime
+from datetime import UTC, datetime, timedelta
 from decimal import Decimal
 from pathlib import Path
 from typing import Any
@@ -679,6 +679,155 @@ def replay(date_from: str, date_to: str, capital: float, dry_run: bool) -> None:
     )
 
 
+@main.command()
+@click.option(
+    "--strategy",
+    "strategy_path",
+    type=click.Path(path_type=Path),
+    default=Path("strategy.yaml"),
+    show_default=True,
+    help="Path al file di strategia (golden, conservativa, aggressiva, ...).",
+)
+@click.option(
+    "--db",
+    "db_path",
+    type=click.Path(path_type=Path),
+    default=_DEFAULT_DB_PATH,
+    show_default=True,
+    help="SQLite con `market_snapshots` storiche.",
+)
+@click.option(
+    "--from",
+    "date_from",
+    type=click.DateTime(formats=["%Y-%m-%d"]),
+    default=None,
+    help="ISO date YYYY-MM-DD (default: 90 giorni fa).",
+)
+@click.option(
+    "--to",
+    "date_to",
+    type=click.DateTime(formats=["%Y-%m-%d"]),
+    default=None,
+    help="ISO date YYYY-MM-DD (default: oggi).",
+)
+@click.option(
+    "--capital",
+    type=float,
+    default=1500.0,
+    show_default=True,
+    help="Capitale di partenza per il backtest, in USD.",
+)
+@click.option(
+    "--asset",
+    type=str,
+    default="ETH",
+    show_default=True,
+    help="Asset di riferimento per le snapshot.",
+)
+@click.option(
+    "--no-enforce-hash",
+    is_flag=True,
+    default=False,
+    help="Salta la verifica del config_hash (utile per profili sperimentali).",
+)
+def backtest(
+    strategy_path: Path,
+    db_path: Path,
+    date_from: datetime | None,
+    date_to: datetime | None,
+    capital: float,
+    asset: str,
+    no_enforce_hash: bool,
+) -> None:
+    """Esegue il backtest stilizzato su `market_snapshots` storiche.
+
+    Usa lo stesso `validate_entry` del live per i filtri (rigoroso) e
+    un modello Black-Scholes con skew premium per stimare credito ed
+    exit P/L (stilizzato — vedi docstring di `core/backtest.py`).
+    """
+    from cerbero_bite.config.loader import load_strategy  # noqa: PLC0415
+    from cerbero_bite.core.backtest import run_backtest  # noqa: PLC0415
+
+    console = Console()
+    if date_to is None:
+        date_to = datetime.now(UTC)
+    if date_from is None:
+        date_from = date_to - timedelta(days=90)
+    date_from = date_from.replace(tzinfo=UTC) if date_from.tzinfo is None else date_from
+    date_to = date_to.replace(tzinfo=UTC) if date_to.tzinfo is None else date_to
+
+    loaded = load_strategy(strategy_path, enforce_hash=not no_enforce_hash)
+    cfg = loaded.config
+
+    conn = connect_state(db_path)
+    try:
+        repo = Repository()
+        snapshots = repo.list_market_snapshots(
+            conn,
+            asset=asset.upper(),
+            start=date_from,
+            end=date_to,
+            limit=10000,
+        )
+    finally:
+        conn.close()
+
+    if not snapshots:
+        console.print(
+            f"[yellow]Nessuno snapshot {asset} trovato fra {date_from.date()} "
+            f"e {date_to.date()}.[/yellow]"
+        )
+        sys.exit(1)
+
+    console.print(
+        f"[green]Caricate {len(snapshots)} snapshot {asset} "
+        f"({snapshots[-1].timestamp.date()} → {snapshots[0].timestamp.date()})[/green]"
+    )
+
+    report = run_backtest(snapshots, cfg, capital_usd=Decimal(str(capital)))
+
+    table = Table(title=f"Backtest report — {strategy_path.name}")
+    table.add_column("Metrica", style="cyan")
+    table.add_column("Valore", style="bold")
+    table.add_row("Picks (lunedì 14:00)", str(report.n_picks))
+    table.add_row(
+        "Accettati dai filtri",
+        f"{report.n_accepted} ({report.n_accepted / max(1, report.n_picks):.0%})",
+    )
+    table.add_row("Saltati per dato mancante", str(report.n_skipped_data))
+    table.add_row("Trade completati (con P/L)", str(report.n_completed))
+    table.add_row("Vincenti", f"{report.n_winners} ({report.win_rate:.0%})")
+    table.add_row("P/L cumulato (USD)", f"{report.cumulative_pnl_usd:+.2f}")
+    table.add_row(
+        "P/L su capitale", f"{report.cumulative_pnl_pct_of_capital:+.2%}"
+    )
+    table.add_row(
+        "Max drawdown", f"−{report.max_drawdown_usd:.0f} USD "
+        f"({report.max_drawdown_pct:.1%})",
+    )
+    table.add_row(
+        "Sharpe (annualized)",
+        f"{report.sharpe_annualized}" if report.sharpe_annualized is not None
+        else "—",
+    )
+    console.print(table)
+
+    if report.skip_reasons:
+        skip_table = Table(title="Motivi di skip aggregati")
+        skip_table.add_column("Motivo")
+        skip_table.add_column("Settimane", justify="right")
+        for reason, count in sorted(
+            report.skip_reasons.items(), key=lambda kv: -kv[1]
+        ):
+            skip_table.add_row(reason, str(count))
+        console.print(skip_table)
+
+    console.print(
+        "[dim]Il modello P/L è stilizzato: BS + skew premium 1.5×. "
+        "Numeri ottimi per ranking config, non per promesse operative.[/dim]"
+    )
+
+
 @main.group()
 def config() -> None:
     """Strategy configuration utilities."""
@@ -812,6 +961,241 @@ def state_inspect(db: Path) -> None:
     console.print(table)
 
 
+@main.group(name="option-chain")
+def option_chain() -> None:
+    """Strumenti per la catena opzioni storica (`option_chain_snapshots`)."""
+
+
+@option_chain.command(name="trigger")
+@click.option(
+    "--strategy",
+    "strategy_path",
+    type=click.Path(exists=True, dir_okay=False, path_type=Path),
+    default=_DEFAULT_STRATEGY_PATH,
+    show_default=True,
+)
+@click.option(
+    "--db",
+    "db_path",
+    type=click.Path(dir_okay=False, path_type=Path),
+    default=_DEFAULT_DB_PATH,
+    show_default=True,
+)
+@click.option(
+    "--audit",
+    "audit_path",
+    type=click.Path(dir_okay=False, path_type=Path),
+    default=_DEFAULT_AUDIT_PATH,
+    show_default=True,
+)
+@click.option(
+    "--token",
+    type=str,
+    default=None,
+    help="MCP bearer token (override su CERBERO_BITE_MCP_TOKEN).",
+)
+@click.option("--asset", default="ETH", show_default=True)
+def option_chain_trigger(
+    strategy_path: Path,
+    db_path: Path,
+    audit_path: Path,
+    token: str | None,
+    asset: str,
+) -> None:
+    """Esegue UNA volta il collector della catena opzioni e persiste in DB.
+
+    Utile per popolare i dati senza aspettare il cron settimanale del
+    job ``option_chain_snapshot``. Riusa esattamente la stessa pipeline
+    schedulata.
+    """
+    from cerbero_bite.runtime.dependencies import build_runtime  # noqa: PLC0415
+    from cerbero_bite.runtime.option_chain_snapshot_cycle import (  # noqa: PLC0415
+        collect_option_chain_snapshot,
+    )
+
+    cfg = load_strategy(strategy_path).config
+    ctx = build_runtime(
+        cfg=cfg,
+        endpoints=load_endpoints(),
+        token=load_token(value=token),
+        db_path=db_path,
+        audit_path=audit_path,
+        bot_tag=load_bot_tag(),
+    )
+    n = asyncio.run(collect_option_chain_snapshot(ctx, asset=asset))
+    console.print(
+        f"[green]Persisted {n} option chain quote(s) for {asset}[/green]"
+        if n > 0
+        else f"[yellow]No quotes persisted (chain empty or fetch failed)[/yellow]"
+    )
+
+
+@option_chain.command(name="analyze")
+@click.option(
+    "--strategy",
+    "strategy_path",
+    type=click.Path(exists=True, dir_okay=False, path_type=Path),
+    default=_DEFAULT_STRATEGY_PATH,
+    show_default=True,
+)
+@click.option(
+    "--db",
+    "db_path",
+    type=click.Path(dir_okay=False, path_type=Path),
+    default=_DEFAULT_DB_PATH,
+    show_default=True,
+)
+@click.option("--asset", default="ETH", show_default=True)
+@click.option(
+    "--bias",
+    type=click.Choice(["bull_put", "bear_call"], case_sensitive=False),
+    default="bull_put",
+    show_default=True,
+    help="Direzione da simulare (il rule engine lo deciderebbe da trend×funding).",
+)
+def option_chain_analyze(
+    strategy_path: Path,
+    db_path: Path,
+    asset: str,
+    bias: str,
+) -> None:
+    """Analizza l'ultimo snapshot di catena salvato.
+
+    Per la strategia indicata, simula la selezione strike (delta
+    target, OTM range, width 4%, credit/width ratio min) e mostra:
+      * lo strike che il rule engine sceglierebbe come short e long,
+      * credito atteso, larghezza, rapporto credit/width,
+      * pass/fail del gate `credit_to_width_ratio_min`.
+    """
+    from cerbero_bite.core.combo_builder import select_strikes  # noqa: PLC0415
+    from cerbero_bite.core.types import OptionQuote  # noqa: PLC0415
+
+    cfg = load_strategy(strategy_path).config
+
+    conn = connect_state(db_path)
+    try:
+        repo = Repository()
+        latest_ts = repo.latest_option_chain_timestamp(conn, asset=asset.upper())
+        if latest_ts is None:
+            console.print(
+                "[red]Nessuno snapshot di catena trovato. Lancia prima "
+                "`cerbero-bite option-chain trigger`.[/red]"
+            )
+            sys.exit(1)
+        quotes_records = repo.list_option_chain_snapshots(
+            conn, asset=asset.upper(), start=latest_ts, end=latest_ts,
+        )
+    finally:
+        conn.close()
+
+    console.print(
+        f"[cyan]Snapshot del {latest_ts.isoformat()} — {len(quotes_records)} "
+        f"quote totali[/cyan]"
+    )
+
+    # Costruzione OptionQuote da OptionChainQuoteRecord per riusare select_strikes.
+    quotes: list[OptionQuote] = []
+    for q in quotes_records:
+        if q.bid is None or q.ask is None or q.mid is None or q.delta is None:
+            continue
+        quotes.append(
+            OptionQuote(
+                instrument=q.instrument_name,
+                strike=q.strike,
+                expiry=q.expiry,
+                option_type=q.option_type,
+                bid=q.bid,
+                ask=q.ask,
+                mid=q.mid,
+                delta=q.delta,
+                gamma=q.gamma or Decimal("0"),
+                theta=q.theta or Decimal("0"),
+                vega=q.vega or Decimal("0"),
+                open_interest=q.open_interest or 0,
+                volume_24h=q.volume_24h or 0,
+                book_depth_top3=q.book_depth_top3 or 0,
+            )
+        )
+
+    if not quotes:
+        console.print("[red]Nessun quote completo per la simulazione.[/red]")
+        sys.exit(1)
+
+    # Lo spot al momento dello snapshot: estraiamo dall'ultimo
+    # `market_snapshot` ETH a quel timestamp (tolleranza ±15 min).
+    spot = _resolve_spot_at(db_path, asset=asset.upper(), at=latest_ts)
+    if spot is None:
+        console.print(
+            "[yellow]Spot non recuperabile dai market_snapshots; "
+            "stimato dal mid ATM.[/yellow]"
+        )
+        spot = _atm_spot_proxy(quotes)
+
+    selection = select_strikes(
+        chain=quotes,
+        bias=bias,  # type: ignore[arg-type]
+        spot=spot,
+        now=latest_ts,
+        cfg=cfg,
+    )
+    if selection is None:
+        console.print(
+            "[red]Il rule engine NON aprirebbe trade con questa catena[/red] "
+            "(no strike compatibile coi gate delta/distance/width/credit-ratio)."
+        )
+        sys.exit(0)
+
+    short, long_ = selection
+    width_usd = (short.strike - long_.strike).copy_abs()
+    credit_eth = short.mid - long_.mid
+    credit_usd = credit_eth * spot
+    ratio = credit_usd / width_usd if width_usd > 0 else Decimal("0")
+    ratio_target = cfg.structure.credit_to_width_ratio_min
+
+    table = Table(title=f"Simulazione picker — bias={bias}, spot={spot:.0f}")
+    table.add_column("Campo", style="cyan")
+    table.add_column("Valore", style="bold")
+    table.add_row("Short strike", f"{short.strike} ({short.delta:+.3f}δ)")
+    table.add_row("Long strike", f"{long_.strike} ({long_.delta:+.3f}δ)")
+    table.add_row("Width", f"{width_usd:.0f} USD")
+    table.add_row("Credit", f"{credit_eth:.4f} ETH ≈ {credit_usd:.2f} USD")
+    table.add_row(
+        "Credit/width ratio",
+        f"{ratio:.2%}  (gate ≥ {float(ratio_target):.0%})",
+    )
+    pass_str = (
+        "[green]PASS — entry possibile[/green]"
+        if ratio >= ratio_target
+        else "[red]FAIL — premio troppo magro[/red]"
+    )
+    table.add_row("Verdetto gate ratio", pass_str)
+    console.print(table)
+
+
+def _resolve_spot_at(db_path: Path, *, asset: str, at: datetime) -> Decimal | None:
+    """Best-effort lookup dello spot al timestamp ``at`` ± 15 min."""
+    conn = connect_state(db_path)
+    try:
+        rows = Repository().list_market_snapshots(
+            conn,
+            asset=asset,
+            start=at - timedelta(minutes=15),
+            end=at + timedelta(minutes=15),
+            limit=1,
+        )
+    finally:
+        conn.close()
+    if not rows:
+        return None
+    return rows[0].spot
+
+
+def _atm_spot_proxy(quotes: list[Any]) -> Decimal:
+    """Stima dello spot prendendo lo strike il cui delta è più vicino a 0.5."""
+    quote = min(quotes, key=lambda q: abs(abs(q.delta) - Decimal("0.5")))
+    return quote.strike
+
+
 def _entrypoint() -> None:
     """Wrapper used by ``cerbero-bite`` console script."""
     try:

src/cerbero_bite/config/schema.py

@@ -75,6 +75,15 @@ class EntryConfig(BaseModel):
     dealer_gamma_filter_enabled: bool = True
     liquidation_filter_enabled: bool = True
 
+    # IV richness filter (§2.9). `iv_minus_rv_min` è la soglia in
+    # punti vol che la IV implicita 30g deve eccedere la RV30g per
+    # ammettere l'entry. Letteratura short-vol systematic: l'edge
+    # sostenibile esiste solo con un margine misurabile fra IV e RV.
+    # Default disabilitato + soglia 0 per non bloccare l'avvio finché
+    # non si è calibrato sui dati raccolti (vedi `📐 Calibrazione`).
+    iv_minus_rv_min: Decimal = Field(default=Decimal("0"))
+    iv_minus_rv_filter_enabled: bool = False
+
 
 # ---------------------------------------------------------------------------
 # Structure

src/cerbero_bite/core/backtest.py

@@ -0,0 +1,652 @@
+"""Stylized backtest engine over ``market_snapshots`` (§13).
+
+Two layers, both pure functions:
+
+1. **Entry-filter simulation** — for each Monday 14:00 UTC tick in the
+   recorded snapshots, evaluate which §2 gates would have passed,
+   reconstructing :class:`EntryContext` from the snapshot.  This part
+   is **rigorous**: it uses the same :func:`validate_entry` the live
+   engine uses, so the output is exactly "what the bot would have
+   decided".
+
+2. **P/L estimation per accepted entry** — since ``market_snapshots``
+   does NOT record the option chain (we only collect spot, DVOL,
+   funding, etc.), credit and exit P/L are estimated via a stylized
+   Black-Scholes model: given ``spot``, ``DVOL`` (as IV), and the
+   strategy's delta target, we solve for the short strike, the long
+   strike at ``width_pct`` distance, and the combo mid-price.  Future
+   ticks are then re-priced under the same model to detect the first
+   exit trigger from §7.
+
+The stylized layer is **intentionally approximate**: it captures the
+geometry of the strategy (DVOL band sets credit, ETH path drives
+exit triggers) but not the second-order effects (chain liquidity,
+borrow rates, exchange fees beyond the 0.03% notional cap, dealer
+hedging skew).  Numbers are good for ranking and tuning, not for
+operational P/L promises.
+
+The engine is deterministic and side-effect-free: it does **not**
+write to SQLite, does not call MCP, does not place orders.  It
+operates entirely on a list of :class:`MarketSnapshotRecord` rows
+the caller has already loaded.
+"""
+
+from __future__ import annotations
+
+import math
+from dataclasses import dataclass
+from datetime import UTC, datetime, timedelta
+from decimal import Decimal
+from typing import Literal
+
+from pydantic import BaseModel, ConfigDict
+
+from cerbero_bite.config.schema import StrategyConfig
+from cerbero_bite.core.entry_validator import EntryContext, validate_entry
+from cerbero_bite.state.models import MarketSnapshotRecord
+
+__all__ = [
+    "BacktestEntry",
+    "BacktestExit",
+    "BacktestReport",
+    "MondayPick",
+    "bs_put_delta",
+    "bs_put_price",
+    "estimate_credit_eth",
+    "find_strike_for_delta",
+    "monday_picks",
+    "normal_cdf",
+    "run_backtest",
+    "simulate_entry_filters",
+    "simulate_position_outcome",
+]
+
+
+_ANNUAL_DAYS = Decimal("365")
+_DEFAULT_RISK_FREE = Decimal("0")
+_NUM_SLIPPAGE_PCT_OF_CREDIT = Decimal("0.03")
+_NUM_FEE_PCT_OF_NOTIONAL = Decimal("0.0003")
+
+
+# ---------------------------------------------------------------------------
+# Black-Scholes helpers (stdlib-only)
+# ---------------------------------------------------------------------------
+
+
+def normal_cdf(x: float) -> float:
+    """Standard normal CDF, no scipy dependency."""
+    return 0.5 * (1.0 + math.erf(x / math.sqrt(2.0)))
+
+
+def bs_put_price(*, spot: float, strike: float, t_years: float, sigma: float) -> float:
+    """European put price under r=0, q=0 Black-Scholes.
+
+    Returns price in spot units (so for an ETH option, dividing by spot
+    gives the price in ETH).
+    """
+    if t_years <= 0 or sigma <= 0 or spot <= 0 or strike <= 0:
+        return max(0.0, strike - spot)
+    sqrt_t = math.sqrt(t_years)
+    d1 = (math.log(spot / strike) + 0.5 * sigma * sigma * t_years) / (sigma * sqrt_t)
+    d2 = d1 - sigma * sqrt_t
+    return strike * normal_cdf(-d2) - spot * normal_cdf(-d1)
+
+
+def bs_put_delta(*, spot: float, strike: float, t_years: float, sigma: float) -> float:
+    """Put delta under r=0, q=0 Black-Scholes (negative number for put).
+
+    Returns 0 for expired options.
+    """
+    if t_years <= 0 or sigma <= 0 or spot <= 0 or strike <= 0:
+        return 0.0
+    sqrt_t = math.sqrt(t_years)
+    d1 = (math.log(spot / strike) + 0.5 * sigma * sigma * t_years) / (sigma * sqrt_t)
+    return normal_cdf(d1) - 1.0  # = -N(-d1)
+
+
+def find_strike_for_delta(
+    *,
+    spot: float,
+    dvol_pct: float,
+    dte_days: int,
+    target_delta_abs: float,
+) -> float:
+    """Solve for the put strike whose |delta| matches ``target_delta_abs``.
+
+    Bisection on a monotone-decreasing |delta(strike)| relationship.
+    Returns the strike in absolute USD terms.
+    """
+    sigma = max(0.01, dvol_pct / 100.0)
+    t_years = max(1e-6, dte_days / 365.0)
+    # Bracket: from 50% of spot (deep OTM, small |delta|) up to spot
+    # (ATM, |delta| ≈ 0.5).
+    low = max(1.0, spot * 0.30)
+    high = spot
+    for _ in range(64):
+        mid = 0.5 * (low + high)
+        delta_abs = abs(bs_put_delta(spot=spot, strike=mid, t_years=t_years, sigma=sigma))
+        if delta_abs > target_delta_abs:
+            high = mid
+        else:
+            low = mid
+        if abs(high - low) < 1e-3:
+            break
+    return 0.5 * (low + high)
+
+
+def estimate_credit_eth(
+    *,
+    spot: float,
+    dvol_pct: float,
+    dte_days: int,
+    width_pct: float,
+    delta_target_abs: float,
+    skew_premium: float = 1.5,
+) -> tuple[float, float, float]:
+    """Estimate credit (ETH), short_strike, long_strike for a bull-put-style
+    credit spread under Black-Scholes.
+
+    ``skew_premium`` è il moltiplicatore applicato al credito BS per
+    approssimare la **vol smile** dell'ETH options market (le put OTM
+    trattano a IV più alta della IV ATM, quindi un BS pulito sottostima
+    sistematicamente il premio del venditore di vol).  Il default 1.5
+    è una stima conservativa dei dati Deribit storici (smile slope
+    tipica 5-10 vol points per 100δ); valori sensati: 1.3 (smile
+    blanda) … 1.8 (regime "stress IV"). Va calibrato sui dati reali
+    quando avremo abbastanza chain history da farlo.
+
+    Returns ``(credit_eth, short_strike, long_strike)``.  Credit è
+    già moltiplicato per ``skew_premium``.
+    """
+    short_strike = find_strike_for_delta(
+        spot=spot, dvol_pct=dvol_pct, dte_days=dte_days,
+        target_delta_abs=delta_target_abs,
+    )
+    width_usd = width_pct * spot
+    long_strike = max(1.0, short_strike - width_usd)
+    sigma = max(0.01, dvol_pct / 100.0)
+    t_years = max(1e-6, dte_days / 365.0)
+    short_mid_usd = bs_put_price(
+        spot=spot, strike=short_strike, t_years=t_years, sigma=sigma,
+    )
+    long_mid_usd = bs_put_price(
+        spot=spot, strike=long_strike, t_years=t_years, sigma=sigma,
+    )
+    short_mid_eth = short_mid_usd / spot
+    long_mid_eth = long_mid_usd / spot
+    credit_eth = (short_mid_eth - long_mid_eth) * skew_premium
+    return credit_eth, short_strike, long_strike
+
+
+# ---------------------------------------------------------------------------
+# Entry filter simulation — rigorous (uses validate_entry exactly)
+# ---------------------------------------------------------------------------
+
+
+@dataclass(frozen=True)
+class MondayPick:
+    """Indice di un tick "Monday 14:00 UTC" nella time-series."""
+
+    timestamp: datetime
+    snapshot: MarketSnapshotRecord
+
+
+def monday_picks(
+    snapshots: list[MarketSnapshotRecord],
+    *,
+    weekday: int = 0,  # Monday
+    hour_utc: int = 14,
+    asset: str = "ETH",
+) -> list[MondayPick]:
+    """Estrae i tick più vicini a "Monday h:00 UTC" per ogni settimana.
+
+    ``snapshots`` deve essere ordinato per timestamp ascending.  Per ogni
+    occorrenza di ``weekday + hour_utc`` (es. lun 14:00) presa l'unica
+    riga ETH che la copre.  Settimane senza tick a quell'ora vengono
+    saltate.
+    """
+    picks: list[MondayPick] = []
+    seen_dates: set[tuple[int, int]] = set()  # (iso_year, iso_week)
+    for snap in snapshots:
+        if snap.asset.upper() != asset.upper():
+            continue
+        ts = snap.timestamp.astimezone(UTC)
+        if ts.weekday() != weekday or ts.hour != hour_utc:
+            continue
+        iso_y, iso_w, _ = ts.isocalendar()
+        key = (iso_y, iso_w)
+        if key in seen_dates:
+            continue
+        seen_dates.add(key)
+        picks.append(MondayPick(timestamp=ts, snapshot=snap))
+    return picks
+
+
+def _entry_context_from_snapshot(
+    snap: MarketSnapshotRecord,
+    *,
+    capital_usd: Decimal,
+    eth_holdings_pct: Decimal = Decimal("0"),
+) -> EntryContext | None:
+    """Costruisce :class:`EntryContext` dal tick storico.
+
+    ``None`` quando la riga non ha i campi minimi (spot, dvol, funding).
+    Nel filtro questo si traduce in "skip della settimana" — è la
+    stessa logica del live: un tick incompleto è meglio di un'entry
+    al buio.
+    """
+    if snap.dvol is None or snap.funding_perp_annualized is None:
+        return None
+    return EntryContext(
+        capital_usd=capital_usd,
+        dvol_now=snap.dvol,
+        funding_perp_annualized=snap.funding_perp_annualized,
+        eth_holdings_pct_of_portfolio=eth_holdings_pct,
+        next_macro_event_in_days=snap.macro_days_to_event,
+        has_open_position=False,
+        dealer_net_gamma=snap.dealer_net_gamma,
+        liquidation_squeeze_risk_high=(
+            snap.liquidation_long_risk == "high"
+            or snap.liquidation_short_risk == "high"
+        ),
+    )
+
+
+@dataclass(frozen=True)
+class EntryFilterResult:
+    """Esito del check filtri per una singola Monday pick."""
+
+    pick: MondayPick
+    accepted: bool
+    reasons: list[str]
+    skipped_for_data: bool  # True se il tick non aveva i campi minimi
+
+
+def simulate_entry_filters(
+    picks: list[MondayPick],
+    cfg: StrategyConfig,
+    *,
+    capital_usd: Decimal,
+) -> list[EntryFilterResult]:
+    """Per ogni Monday pick, valuta validate_entry come farebbe il live.
+
+    Rigoroso: usa esattamente :func:`validate_entry` e :class:`EntryContext`.
+    Restituisce la lista degli esiti, una entry per pick.
+    """
+    results: list[EntryFilterResult] = []
+    for pick in picks:
+        ctx = _entry_context_from_snapshot(pick.snapshot, capital_usd=capital_usd)
+        if ctx is None:
+            results.append(
+                EntryFilterResult(
+                    pick=pick,
+                    accepted=False,
+                    reasons=["incomplete_snapshot"],
+                    skipped_for_data=True,
+                )
+            )
+            continue
+        decision = validate_entry(ctx, cfg)
+        results.append(
+            EntryFilterResult(
+                pick=pick,
+                accepted=decision.accepted,
+                reasons=list(decision.reasons),
+                skipped_for_data=False,
+            )
+        )
+    return results
+
+
+# ---------------------------------------------------------------------------
+# Position outcome simulation — stylized (Black-Scholes re-pricing)
+# ---------------------------------------------------------------------------
+
+
+class BacktestEntry(BaseModel):
+    """Trade aperto nel backtest (snapshot al momento dell'entry)."""
+
+    model_config = ConfigDict(frozen=True)
+
+    timestamp: datetime
+    spread_type: Literal["bull_put"]  # MVP: solo bull_put nel backtest
+    spot_at_entry: Decimal
+    dvol_at_entry: Decimal
+    short_strike: Decimal
+    long_strike: Decimal
+    expiry: datetime
+    credit_received_eth: Decimal
+    credit_received_usd: Decimal
+    n_contracts: int
+
+
+class BacktestExit(BaseModel):
+    """Esito di un trade nel backtest."""
+
+    model_config = ConfigDict(frozen=True)
+
+    timestamp: datetime
+    action: Literal[
+        "CLOSE_PROFIT", "CLOSE_STOP", "CLOSE_VOL", "CLOSE_TIME",
+        "CLOSE_DELTA", "CLOSE_AVERSE", "EXPIRED",
+    ]
+    reason: str
+    spot_at_exit: Decimal
+    dvol_at_exit: Decimal
+    debit_paid_eth: Decimal
+    pnl_eth: Decimal
+    pnl_usd: Decimal
+
+
+def _combo_mid_eth(
+    *, spot: float, dvol_pct: float, dte_days: int,
+    short_strike: float, long_strike: float,
+    skew_premium: float = 1.5,
+) -> float:
+    """Re-prezza il combo bull-put usando BS sul nuovo spot/dvol/dte."""
+    sigma = max(0.01, dvol_pct / 100.0)
+    t_years = max(1e-6, dte_days / 365.0)
+    short_mid_usd = bs_put_price(
+        spot=spot, strike=short_strike, t_years=t_years, sigma=sigma,
+    )
+    long_mid_usd = bs_put_price(
+        spot=spot, strike=long_strike, t_years=t_years, sigma=sigma,
+    )
+    return (short_mid_usd - long_mid_usd) / spot * skew_premium
+
+
+def simulate_position_outcome(
+    entry: BacktestEntry,
+    future_snapshots: list[MarketSnapshotRecord],
+    cfg: StrategyConfig,
+) -> BacktestExit:
+    """Re-prezza il combo a ogni tick futuro fino al primo exit trigger.
+
+    Triggers in ordine §7:
+      1. profit_take (debit ≤ 0.5×credit)
+      2. stop_loss (debit ≥ 2.5×credit)
+      3. vol_stop (DVOL salita di ≥10 pt rispetto entry)
+      4. time_stop (DTE ≤ 7 e debit > 0.7×credit)
+      5. expiry (uscita per scadenza, P/L = credit − intrinsic)
+    """
+    ec = cfg.exit
+    credit = float(entry.credit_received_eth)
+    short = float(entry.short_strike)
+    long_ = float(entry.long_strike)
+
+    profit_thresh = float(ec.profit_take_pct_of_credit) * credit
+    stop_thresh = float(ec.stop_loss_mark_x_credit) * credit
+    skip_time_thresh = float(ec.time_stop_skip_if_close_to_profit_pct) * credit
+
+    for snap in future_snapshots:
+        if snap.timestamp <= entry.timestamp:
+            continue
+        if snap.timestamp >= entry.expiry:
+            break
+        if snap.dvol is None or snap.spot is None:
+            continue
+        spot_now = float(snap.spot)
+        dvol_now = float(snap.dvol)
+        dte = max(0, (entry.expiry - snap.timestamp).days)
+        debit = _combo_mid_eth(
+            spot=spot_now, dvol_pct=dvol_now, dte_days=dte,
+            short_strike=short, long_strike=long_,
+        )
+        if debit <= profit_thresh:
+            return _exit(
+                snap, entry, debit,
+                action="CLOSE_PROFIT",
+                reason=f"debit {debit:.4f} ≤ {profit_thresh:.4f}",
+            )
+        if debit >= stop_thresh:
+            return _exit(
+                snap, entry, debit,
+                action="CLOSE_STOP",
+                reason=f"debit {debit:.4f} ≥ {stop_thresh:.4f}",
+            )
+        if dvol_now >= float(entry.dvol_at_entry) + float(ec.vol_stop_dvol_increase):
+            return _exit(
+                snap, entry, debit,
+                action="CLOSE_VOL",
+                reason=f"DVOL {dvol_now:.1f} ≥ entry+{ec.vol_stop_dvol_increase}",
+            )
+        if dte <= ec.time_stop_dte_remaining and debit > skip_time_thresh:
+            return _exit(
+                snap, entry, debit,
+                action="CLOSE_TIME",
+                reason=f"DTE {dte} ≤ {ec.time_stop_dte_remaining}",
+            )
+
+    # Tick passati senza trigger: scadenza naturale.
+    last = future_snapshots[-1] if future_snapshots else None
+    intrinsic = max(0.0, short - float(last.spot if last and last.spot else 0))
+    intrinsic_capped = min(intrinsic, short - long_)
+    debit_at_expiry_eth = (
+        intrinsic_capped / float(last.spot)
+        if last is not None and last.spot is not None and float(last.spot) > 0
+        else 0.0
+    )
+    return _exit(
+        last or _synthetic_expiry_snapshot(entry),
+        entry,
+        debit_at_expiry_eth,
+        action="EXPIRED",
+        reason="held to expiry",
+    )
+
+
+def _synthetic_expiry_snapshot(entry: BacktestEntry) -> MarketSnapshotRecord:
+    return MarketSnapshotRecord(
+        timestamp=entry.expiry,
+        asset="ETH",
+        spot=entry.spot_at_entry,
+        dvol=entry.dvol_at_entry,
+        fetch_ok=False,
+    )
+
+
+def _exit(
+    snap: MarketSnapshotRecord,
+    entry: BacktestEntry,
+    debit_eth: float,
+    *,
+    action: str,
+    reason: str,
+) -> BacktestExit:
+    pnl_eth = float(entry.credit_received_eth) - debit_eth
+    spot = float(snap.spot) if snap.spot is not None else float(entry.spot_at_entry)
+    dvol = float(snap.dvol) if snap.dvol is not None else float(entry.dvol_at_entry)
+    return BacktestExit(
+        timestamp=snap.timestamp,
+        action=action,  # type: ignore[arg-type]
+        reason=reason,
+        spot_at_exit=Decimal(str(spot)),
+        dvol_at_exit=Decimal(str(dvol)),
+        debit_paid_eth=Decimal(str(debit_eth)),
+        pnl_eth=Decimal(str(pnl_eth)),
+        pnl_usd=Decimal(str(pnl_eth * spot * entry.n_contracts)),
+    )
+
+
+# ---------------------------------------------------------------------------
+# Full pipeline
+# ---------------------------------------------------------------------------
+
+
+@dataclass(frozen=True)
+class CompletedTrade:
+    entry: BacktestEntry
+    exit: BacktestExit
+
+
+class BacktestReport(BaseModel):
+    """Aggregato del backtest. Tutti i numeri sono **stime**."""
+
+    model_config = ConfigDict(frozen=True)
+
+    n_picks: int
+    n_accepted: int
+    n_skipped_data: int
+    n_completed: int
+    n_winners: int
+    win_rate: Decimal
+    cumulative_pnl_usd: Decimal
+    cumulative_pnl_pct_of_capital: Decimal
+    max_drawdown_usd: Decimal
+    max_drawdown_pct: Decimal
+    sharpe_annualized: Decimal | None
+    skip_reasons: dict[str, int]
+    trades: list[CompletedTrade]
+
+
+def _build_entry_from_pick(
+    pick: MondayPick,
+    cfg: StrategyConfig,
+    *,
+    capital_usd: Decimal,
+    eur_to_usd: Decimal,
+) -> BacktestEntry | None:
+    snap = pick.snapshot
+    if snap.spot is None or snap.dvol is None:
+        return None
+    spot = float(snap.spot)
+    dvol = float(snap.dvol)
+    width_pct = float(cfg.structure.spread_width.target_pct_of_spot)
+    delta_target = float(cfg.structure.short_strike.delta_target)
+    dte = cfg.structure.dte_target
+
+    credit_eth, short_strike, long_strike = estimate_credit_eth(
+        spot=spot, dvol_pct=dvol, dte_days=dte,
+        width_pct=width_pct, delta_target_abs=delta_target,
+    )
+    width_usd = float(cfg.structure.spread_width.target_pct_of_spot) * spot
+    credit_usd = credit_eth * spot
+    if width_usd <= 0 or credit_usd / width_usd < float(
+        cfg.structure.credit_to_width_ratio_min
+    ):
+        return None  # ratio gate fallisce → no entry
+
+    cap_pertrade_usd = float(cfg.sizing.cap_per_trade_eur) * float(eur_to_usd)
+    risk_target = min(float(cfg.sizing.kelly_fraction) * float(capital_usd), cap_pertrade_usd)
+    n_contracts = max(0, min(int(risk_target // width_usd), cfg.sizing.max_contracts_per_trade))
+    if n_contracts == 0:
+        return None
+
+    expiry = pick.timestamp + timedelta(days=dte)
+    return BacktestEntry(
+        timestamp=pick.timestamp,
+        spread_type="bull_put",
+        spot_at_entry=Decimal(str(spot)),
+        dvol_at_entry=Decimal(str(dvol)),
+        short_strike=Decimal(str(round(short_strike, 2))),
+        long_strike=Decimal(str(round(long_strike, 2))),
+        expiry=expiry,
+        credit_received_eth=Decimal(str(credit_eth)),
+        credit_received_usd=Decimal(str(credit_usd * n_contracts)),
+        n_contracts=n_contracts,
+    )
+
+
+def _max_drawdown_usd(equity: list[Decimal]) -> tuple[Decimal, Decimal]:
+    """Return ``(max_dd_usd, max_dd_pct_of_peak)`` over an equity curve."""
+    if not equity:
+        return Decimal("0"), Decimal("0")
+    peak = equity[0]
+    max_dd_usd = Decimal("0")
+    max_dd_pct = Decimal("0")
+    for v in equity:
+        if v > peak:
+            peak = v
+        dd = peak - v
+        if dd > max_dd_usd:
+            max_dd_usd = dd
+        if peak > 0 and (dd / peak) > max_dd_pct:
+            max_dd_pct = dd / peak
+    return max_dd_usd, max_dd_pct
+
+
+def _sharpe_annualized(pnls_usd: list[Decimal], capital_usd: Decimal) -> Decimal | None:
+    """Annualized Sharpe approximation: 52 trade/anno (settimanali).
+
+    Restituisce ``None`` se ci sono <5 trade o stdev = 0.
+    """
+    if len(pnls_usd) < 5 or capital_usd <= 0:
+        return None
+    rets = [float(p / capital_usd) for p in pnls_usd]
+    mean = sum(rets) / len(rets)
+    var = sum((r - mean) ** 2 for r in rets) / max(1, (len(rets) - 1))
+    std = math.sqrt(var)
+    if std == 0:
+        return None
+    sharpe = mean / std * math.sqrt(52)
+    return Decimal(str(round(sharpe, 3)))
+
+
+def run_backtest(
+    snapshots: list[MarketSnapshotRecord],
+    cfg: StrategyConfig,
+    *,
+    capital_usd: Decimal,
+    eur_to_usd: Decimal = Decimal("1.075"),
+    asset: str = "ETH",
+) -> BacktestReport:
+    """Esegue il backtest end-to-end sui ``snapshots`` ETH ordinati per ts."""
+    snapshots = sorted(snapshots, key=lambda s: s.timestamp)
+    eth_snapshots = [s for s in snapshots if s.asset.upper() == asset.upper()]
+    picks = monday_picks(eth_snapshots, asset=asset)
+    filter_results = simulate_entry_filters(picks, cfg, capital_usd=capital_usd)
+
+    # Tally skip reasons
+    skip_reasons: dict[str, int] = {}
+    for r in filter_results:
+        if r.accepted:
+            continue
+        for reason in r.reasons:
+            skip_reasons[reason] = skip_reasons.get(reason, 0) + 1
+
+    trades: list[CompletedTrade] = []
+    for r in filter_results:
+        if not r.accepted:
+            continue
+        entry = _build_entry_from_pick(
+            r.pick, cfg, capital_usd=capital_usd, eur_to_usd=eur_to_usd,
+        )
+        if entry is None:
+            skip_reasons["sizing_or_ratio"] = skip_reasons.get("sizing_or_ratio", 0) + 1
+            continue
+        future = [s for s in eth_snapshots if s.timestamp > r.pick.timestamp]
+        exit_ = simulate_position_outcome(entry, future, cfg)
+        trades.append(CompletedTrade(entry=entry, exit=exit_))
+
+    pnls = [t.exit.pnl_usd for t in trades]
+    cumulative = sum(pnls, start=Decimal("0"))
+    n_winners = sum(1 for p in pnls if p > 0)
+    win_rate = (
+        Decimal(n_winners) / Decimal(len(pnls))
+        if pnls
+        else Decimal("0")
+    )
+
+    # Equity curve in USD assoluti
+    equity = [capital_usd]
+    for p in pnls:
+        equity.append(equity[-1] + p)
+    max_dd_usd, max_dd_pct = _max_drawdown_usd(equity)
+
+    return BacktestReport(
+        n_picks=len(picks),
+        n_accepted=sum(1 for r in filter_results if r.accepted),
+        n_skipped_data=sum(1 for r in filter_results if r.skipped_for_data),
+        n_completed=len(trades),
+        n_winners=n_winners,
+        win_rate=win_rate,
+        cumulative_pnl_usd=cumulative,
+        cumulative_pnl_pct_of_capital=(
+            cumulative / capital_usd if capital_usd > 0 else Decimal("0")
+        ),
+        max_drawdown_usd=max_dd_usd,
+        max_drawdown_pct=max_dd_pct,
+        sharpe_annualized=_sharpe_annualized(pnls, capital_usd),
+        skip_reasons=skip_reasons,
+        trades=trades,
+    )

src/cerbero_bite/core/entry_validator.py

@@ -44,6 +44,12 @@ class EntryContext(BaseModel):
     dealer_net_gamma: Decimal | None = None
     liquidation_squeeze_risk_high: bool | None = None
 
+    # IV richness gate (§2.9). Differenza IV30g − RV30g in punti vol.
+    # Optional, stessa logica best-effort dei filtri quant: ``None``
+    # significa "dato non disponibile" e fa saltare il gate (non
+    # invalida l'entry).
+    iv_minus_rv: Decimal | None = None
+
 
 class EntryDecision(BaseModel):
     """Result of :func:`validate_entry`. ``reasons`` holds *all* blocking reasons."""
@@ -131,6 +137,20 @@ def validate_entry(ctx: EntryContext, cfg: StrategyConfig) -> EntryDecision:
     ):
         reasons.append("imminent liquidation squeeze risk")
 
+    # §2.9: IV richness gate. Vendere vol senza un margine misurabile
+    # fra IV e RV è statisticamente neutro: l'edge della strategia
+    # esiste solo quando il premio è "ricco" rispetto a quanto il
+    # mercato si è effettivamente mosso.
+    if (
+        entry_cfg.iv_minus_rv_filter_enabled
+        and ctx.iv_minus_rv is not None
+        and ctx.iv_minus_rv < entry_cfg.iv_minus_rv_min
+    ):
+        reasons.append(
+            f"IV richness below floor "
+            f"(IV-RV={ctx.iv_minus_rv} < {entry_cfg.iv_minus_rv_min} vol pts)"
+        )
+
     return EntryDecision(accepted=not reasons, reasons=reasons)
 
 

src/cerbero_bite/gui/pages/6_📐_Calibrazione.py

@@ -167,9 +167,21 @@ def _percentiles_strip(s: pd.Series) -> None:
         st.caption("(nessun dato)")
         return
     quantiles = [0.05, 0.10, 0.25, 0.50, 0.75, 0.90, 0.95]
-    cols = st.columns(len(quantiles))
-    for col, q in zip(cols, quantiles, strict=False):
-        col.metric(f"P{int(q * 100)}", f"{s.quantile(q):.4g}")
+    # Inline markdown compatto: i valori a 4 cifre significative
+    # cadono regolarmente fuori dalla colonna se renderizzati con
+    # ``st.metric`` (font fisso, label sopra, no shrink). Render
+    # orizzontale con font ridotto evita il troncamento.
+    parts = [
+        f"<b>P{int(q * 100)}</b> {s.quantile(q):.4g}"
+        for q in quantiles
+    ]
+    html = (
+        "<div style='font-size:0.85rem;line-height:1.5;"
+        "white-space:nowrap;overflow-x:auto;'>"
+        + " &nbsp;·&nbsp; ".join(parts)
+        + "</div>"
+    )
+    st.markdown(html, unsafe_allow_html=True)
 
 
 def _render_metric(spec: MetricSpec, records: list[MarketSnapshotRecord]) -> None:

src/cerbero_bite/gui/pages/7_📚_Strategia.py

@@ -11,6 +11,7 @@ La pagina è di sola lettura: non chiama MCP, non scrive sul DB.
 
 from __future__ import annotations
 
+import math
 import os
 from dataclasses import dataclass
 from pathlib import Path
@@ -280,13 +281,18 @@ def _build_gates(
         )
     )
 
-    # --- IV − RV (richness) — solo informativo --------------------
+    # --- IV − RV (richness) — gate §2.9 ---------------------------
     rv = (
         float(snap.realized_vol_30d) if snap.realized_vol_30d is not None else None
     )
     iv_minus_rv = (
         float(snap.iv_minus_rv) if snap.iv_minus_rv is not None else None
     )
+    iv_min = float(getattr(entry, "iv_minus_rv_min", 0.0)) if entry else 0.0
+    iv_enabled = (
+        bool(getattr(entry, "iv_minus_rv_filter_enabled", False)) if entry else False
+    )
+    if not iv_enabled:
         rows.append(
             _GateRow(
                 "IV − RV (richness)",
@@ -295,9 +301,34 @@ def _build_gates(
                     if iv_minus_rv is not None
                     else "—"
                 ),
-            "info, > 0 = premio ricco",
-            "pass" if (iv_minus_rv is not None and iv_minus_rv > 0) else "n/a",
-            f"RV30={rv:.2f}" if rv is not None else "",
+                "filtro DISABILITATO (info-only)",
+                "n/a",
+                f"RV30={rv:.2f} · attiva con `iv_minus_rv_filter_enabled: true`"
+                if rv is not None
+                else "Attiva con `iv_minus_rv_filter_enabled: true`",
+            )
+        )
+    elif iv_minus_rv is None:
+        rows.append(
+            _GateRow(
+                "IV − RV ≥ soglia",
+                "—",
+                f"≥ {iv_min:.1f} pt vol",
+                "n/a",
+                "Dato non disponibile in questo tick (best-effort skip).",
+            )
+        )
+    else:
+        ok = iv_minus_rv >= iv_min
+        rows.append(
+            _GateRow(
+                "IV − RV ≥ soglia",
+                f"{iv_minus_rv:+.2f} pt vol",
+                f"≥ {iv_min:.1f} pt vol",
+                "pass" if ok else "fail",
+                "Premio ricco rispetto a quanto il mercato si è davvero "
+                "mosso → edge sostenibile per il venditore di vol."
+                + (f" RV30={rv:.2f}" if rv is not None else ""),
             )
         )
 
@@ -470,6 +501,37 @@ def _compute_pl(
     annual_pl = trades_eff * n_per_trade * concurrency * e_trade_net
     apr = (annual_pl / capital) if capital > 0 else 0.0
 
+    # --- Max drawdown -------------------------------------------------
+    # Due metriche distinte:
+    #
+    # 1. **Streak atteso (P99)**: lunghezza della peggior sequenza di
+    #    stop consecutivi che ci si aspetta di vedere in un anno con
+    #    probabilità ≤ 1%. Usa l'approssimazione union-bound:
+    #        P(streak ≥ N in N_trade tentativi) ≈ N_trade × p_loss^N
+    #    Imponendo questa quantità ≤ 0.01 e risolvendo per N:
+    #        N = ceil( log(0.01 / N_trade) / log(p_loss) )
+    #    Drawdown corrispondente = N × stop_loss × contracts × concurrency.
+    #
+    # 2. **Tail/gap risk**: scenario "gap notturno" in cui il mark
+    #    salta oltre la copertura long PRIMA che lo stop sia
+    #    eseguibile. La perdita massima reale è la larghezza intera
+    #    dello spread meno il credito iniziale, su tutte le posizioni
+    #    aperte simultaneamente.
+    if prob_loss > 0 and prob_loss < 1 and trades_per_year > 0:
+        streak_99 = max(
+            1,
+            int(math.ceil(
+                math.log(0.01 / trades_per_year) / math.log(prob_loss)
+            )) if prob_loss < 1 else 1,
+        )
+    else:
+        streak_99 = 0
+    expected_dd_usd = streak_99 * sl_loss * n_per_trade * concurrency
+    expected_dd_pct = expected_dd_usd / capital if capital > 0 else 0.0
+
+    tail_dd_usd = (width - credit) * n_per_trade * concurrency
+    tail_dd_pct = tail_dd_usd / capital if capital > 0 else 0.0
+
     return {
         "width": width,
         "credit": credit,
@@ -483,10 +545,15 @@ def _compute_pl(
         "apr": apr,
         "fees": fees,
         "slippage": slippage,
-        "win_rate_eff": win_rate_eff,
-        "trades_eff": trades_eff,
         "prob_loss": prob_loss,
         "prob_harvest": prob_harvest,
+        "streak_99": float(streak_99),
+        "expected_dd_usd": expected_dd_usd,
+        "expected_dd_pct": expected_dd_pct,
+        "tail_dd_usd": tail_dd_usd,
+        "tail_dd_pct": tail_dd_pct,
+        "win_rate_eff": win_rate_eff,
+        "trades_eff": trades_eff,
     }
 
 
@@ -560,6 +627,34 @@ def _render_profile_card(
         ),
     )
 
+    cols = st.columns(2)
+    cols[0].metric(
+        "Max DD attesa (P99)",
+        f"−{metrics['expected_dd_usd']:.0f} USD",
+        delta=f"{-metrics['expected_dd_pct']:+.1%} cap",
+        delta_color="inverse",
+        help=(
+            f"Streak di {int(metrics['streak_99'])} stop consecutivi "
+            f"(probabilità ≤ 1% nell'anno) × perdita stop "
+            f"({metrics['sl_loss']:.0f} USD) × contratti × posizioni "
+            f"concorrenti. È la peggior sequenza che ti aspetti di "
+            "vedere; il drawdown reale può essere maggiore se i filtri "
+            "non rilevano un regime change."
+        ),
+    )
+    cols[1].metric(
+        "Max DD coda (gap)",
+        f"−{metrics['tail_dd_usd']:.0f} USD",
+        delta=f"{-metrics['tail_dd_pct']:+.1%} cap",
+        delta_color="inverse",
+        help=(
+            "Scenario gap notturno: il mark salta oltre la copertura "
+            "long PRIMA che lo stop sia eseguibile. Perdita = larghezza "
+            "intera meno credito, su tutte le posizioni aperte. "
+            "I filtri quant + macro lo riducono ma NON lo annullano."
+        ),
+    )
+
     if metrics["n_per_trade"] == 0:
         st.warning(
             "Sizing 0 contratti: capitale insufficiente per i cap di "
@@ -749,10 +844,10 @@ def _render_pl_panel(
         sens_rows.append(
             {
                 "Win rate": f"{wr:.0%}",
-                "Conservativa P/L": f"{m_c['annual_pl']:+.0f} USD",
-                "Conservativa APR": f"{m_c['apr']:+.1%}",
-                "Aggressiva P/L": f"{m_a['annual_pl']:+.0f} USD",
-                "Aggressiva APR": f"{m_a['apr']:+.1%}",
+                "Cons. APR": f"{m_c['apr']:+.1%}",
+                "Cons. Max DD": f"−{m_c['expected_dd_pct']:.1%}",
+                "Aggr. APR": f"{m_a['apr']:+.1%}",
+                "Aggr. Max DD": f"−{m_a['expected_dd_pct']:.1%}",
             }
         )
     st.table(sens_rows)

src/cerbero_bite/runtime/entry_cycle.py

@@ -96,6 +96,7 @@ class _MarketSnapshot:
     portfolio_eur: Decimal
     dealer_net_gamma: Decimal | None
     liquidation_squeeze_risk_high: bool | None
+    iv_minus_rv: Decimal | None
 
 
 async def _gather_snapshot(
@@ -161,6 +162,9 @@ async def _gather_snapshot(
     liquidation_t: asyncio.Task[bool | None] = asyncio.create_task(
         _safe_liquidation_squeeze(sentiment)
     )
+    iv_rv_t: asyncio.Task[Decimal | None] = asyncio.create_task(
+        _safe_iv_minus_rv(deribit)
+    )
 
     await asyncio.gather(
         spot_t,
@@ -174,6 +178,7 @@ async def _gather_snapshot(
         portfolio_t,
         dealer_t,
         liquidation_t,
+        iv_rv_t,
     )
     return _MarketSnapshot(
         spot_eth_usd=spot_t.result(),
@@ -187,6 +192,7 @@ async def _gather_snapshot(
         portfolio_eur=portfolio_t.result(),
         dealer_net_gamma=dealer_t.result(),
         liquidation_squeeze_risk_high=liquidation_t.result(),
+        iv_minus_rv=iv_rv_t.result(),
     )
 
 
@@ -198,6 +204,20 @@ async def _safe_dealer_gamma(deribit: DeribitClient) -> Decimal | None:
     return snap.total_net_dealer_gamma
 
 
+async def _safe_iv_minus_rv(deribit: DeribitClient) -> Decimal | None:
+    """Best-effort fetch of the IV30g − RV30g spread (vol points)."""
+    try:
+        rv = await deribit.realized_vol("ETH")
+    except Exception:
+        return None
+    if not isinstance(rv, dict):
+        return None
+    value = rv.get("iv_minus_rv_30d")
+    if value is None:
+        return None
+    return value if isinstance(value, Decimal) else Decimal(str(value))
+
+
 async def _safe_liquidation_squeeze(sentiment: SentimentClient) -> bool | None:
     try:
         heatmap = await sentiment.liquidation_heatmap("ETH")
@@ -415,6 +435,7 @@ async def run_entry_cycle(
         next_macro_event_in_days=snap.macro_days_to_event,
         has_open_position=False,
         dealer_net_gamma=snap.dealer_net_gamma,
+        iv_minus_rv=snap.iv_minus_rv,
         liquidation_squeeze_risk_high=snap.liquidation_squeeze_risk_high,
     )
     decision = validate_entry(entry_ctx, cfg)
@@ -432,6 +453,9 @@ async def run_entry_cycle(
             "eth_holdings_pct": str(snap.eth_holdings_pct),
             "portfolio_eur": str(snap.portfolio_eur),
             "capital_usd": str(capital_usd),
+            "iv_minus_rv": (
+                str(snap.iv_minus_rv) if snap.iv_minus_rv is not None else None
+            ),
         }
     }
     if not decision.accepted:

src/cerbero_bite/runtime/option_chain_snapshot_cycle.py

@@ -0,0 +1,185 @@
+"""Periodic option-chain snapshot collector (§13).
+
+Fetches the Deribit option chain for every strike entro la finestra
+DTE configurata, prima del trigger entry settimanale (cron
+``55 13 * * MON`` di default). Persiste un quote per ogni strumento
+in ``option_chain_snapshots`` con un timestamp condiviso, che diventa
+il dato di base per:
+
+* il backtest non-stilizzato (vedi ``core/backtest.py``),
+* la calibrazione empirica dello skew premium e del credit/width
+  ratio sui regimi reali,
+* l'analisi ex-post degli strike picker.
+
+Il collector è **best-effort**: se ``get_tickers`` fallisce per un
+batch, gli altri batch passano comunque; se manca completamente la
+chain, il job ritorna 0 senza alzare eccezioni e logga il problema.
+Non chiama l'order book per ogni strike (sarebbe troppo costoso) —
+``book_depth_top3`` resta NULL nel quote, il liquidity gate del live
+lo legge al volo solo per gli strike che gli interessano.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+from datetime import UTC, datetime, timedelta
+from decimal import Decimal
+from typing import TYPE_CHECKING, Any
+
+from cerbero_bite.state import connect, transaction
+from cerbero_bite.state.models import OptionChainQuoteRecord
+
+if TYPE_CHECKING:
+    from cerbero_bite.runtime.dependencies import RuntimeContext
+
+__all__ = ["DEFAULT_BATCH_SIZE", "collect_option_chain_snapshot"]
+
+
+_log = logging.getLogger("cerbero_bite.runtime.option_chain_snapshot")
+
+
+DEFAULT_BATCH_SIZE = 20  # Deribit get_ticker_batch limit
+
+
+def _to_decimal_or_none(value: Any) -> Decimal | None:
+    if value is None:
+        return None
+    try:
+        return Decimal(str(value))
+    except Exception:
+        return None
+
+
+async def _fetch_tickers_in_batches(
+    ctx: RuntimeContext, names: list[str], *, batch_size: int = DEFAULT_BATCH_SIZE
+) -> dict[str, dict[str, Any]]:
+    """Best-effort fetch dei ticker per tutti i nomi richiesti."""
+    out: dict[str, dict[str, Any]] = {}
+    for i in range(0, len(names), batch_size):
+        batch = names[i : i + batch_size]
+        try:
+            tickers = await ctx.deribit.get_tickers(batch)
+        except Exception as exc:
+            _log.warning(
+                "get_tickers failed for batch starting %s: %s",
+                batch[0] if batch else "<empty>", exc,
+            )
+            continue
+        for t in tickers:
+            name = t.get("instrument_name") or t.get("instrument")
+            if isinstance(name, str):
+                out[name] = t
+    return out
+
+
+async def collect_option_chain_snapshot(
+    ctx: RuntimeContext,
+    *,
+    asset: str = "ETH",
+    now: datetime | None = None,
+    batch_size: int = DEFAULT_BATCH_SIZE,
+) -> int:
+    """Collect + persist a single chain snapshot for ``asset``. Returns
+    the number of quotes persisted (0 on best-effort failure).
+
+    Filtra le scadenze nella finestra ``[dte_min, dte_max]`` di
+    ``cfg.structure`` per non sprecare richieste su scadenze che il
+    rule engine non userebbe mai.
+    """
+    when = (now or datetime.now(UTC)).astimezone(UTC)
+    cfg = ctx.cfg
+
+    expiry_from = when + timedelta(days=cfg.structure.dte_min)
+    expiry_to = when + timedelta(days=cfg.structure.dte_max)
+
+    try:
+        chain = await ctx.deribit.options_chain(
+            currency=asset.upper(),
+            expiry_from=expiry_from,
+            expiry_to=expiry_to,
+            min_open_interest=int(cfg.liquidity.open_interest_min),
+        )
+    except Exception:
+        _log.exception("option chain fetch failed")
+        return 0
+
+    if not chain:
+        _log.info("option chain empty for %s in window", asset)
+        return 0
+
+    names = [meta.name for meta in chain]
+    tickers = await _fetch_tickers_in_batches(ctx, names, batch_size=batch_size)
+
+    quotes: list[OptionChainQuoteRecord] = []
+    for meta in chain:
+        ticker = tickers.get(meta.name)
+        if ticker is None:
+            # Lasciamo comunque la riga senza quote: utile sapere
+            # che lo strumento esisteva.
+            quotes.append(
+                OptionChainQuoteRecord(
+                    timestamp=when,
+                    asset=asset.upper(),
+                    instrument_name=meta.name,
+                    strike=meta.strike,
+                    expiry=meta.expiry,
+                    option_type=meta.option_type,
+                    open_interest=int(meta.open_interest)
+                    if meta.open_interest is not None
+                    else None,
+                )
+            )
+            continue
+        greeks = ticker.get("greeks") or {}
+        quotes.append(
+            OptionChainQuoteRecord(
+                timestamp=when,
+                asset=asset.upper(),
+                instrument_name=meta.name,
+                strike=meta.strike,
+                expiry=meta.expiry,
+                option_type=meta.option_type,
+                bid=_to_decimal_or_none(ticker.get("bid")),
+                ask=_to_decimal_or_none(ticker.get("ask")),
+                mid=_to_decimal_or_none(ticker.get("mark_price")),
+                iv=_to_decimal_or_none(ticker.get("mark_iv")),
+                delta=_to_decimal_or_none(greeks.get("delta")),
+                gamma=_to_decimal_or_none(greeks.get("gamma")),
+                theta=_to_decimal_or_none(greeks.get("theta")),
+                vega=_to_decimal_or_none(greeks.get("vega")),
+                open_interest=int(meta.open_interest)
+                if meta.open_interest is not None
+                else None,
+                volume_24h=(
+                    int(ticker["volume_24h"])
+                    if ticker.get("volume_24h") is not None
+                    else None
+                ),
+                # book_depth_top3: NULL — non lo prendiamo per ogni
+                # strike per non saturare l'API. Il liquidity gate
+                # del live lo chiede on-the-fly per gli strike
+                # candidati al picker.
+            )
+        )
+
+    persisted = 0
+    try:
+        conn = connect(ctx.db_path)
+        try:
+            with transaction(conn):
+                persisted = ctx.repository.record_option_chain_snapshot(
+                    conn, quotes
+                )
+        finally:
+            conn.close()
+    except Exception:
+        _log.exception("persist option chain snapshot failed")
+        return 0
+
+    _log.info("option_chain_snapshot persisted %d quote(s)", persisted)
+    return persisted
+
+
+# Avoid unused import warning for asyncio in lint when only used as type
+_ = asyncio

src/cerbero_bite/runtime/orchestrator.py

@@ -34,6 +34,9 @@ from cerbero_bite.runtime.market_snapshot_cycle import (
     DEFAULT_ASSETS,
     collect_market_snapshot,
 )
+from cerbero_bite.runtime.option_chain_snapshot_cycle import (
+    collect_option_chain_snapshot,
+)
 from cerbero_bite.runtime.monitor_cycle import MonitorCycleResult, run_monitor_cycle
 from cerbero_bite.runtime.recovery import recover_state
 from cerbero_bite.runtime.scheduler import JobSpec, build_scheduler
@@ -53,6 +56,7 @@ _CRON_HEALTH = "*/5 * * * *"
 _CRON_BACKUP = "0 * * * *"
 _CRON_MANUAL_ACTIONS = "*/1 * * * *"
 _CRON_MARKET_SNAPSHOT = "*/15 * * * *"
+_CRON_OPTION_CHAIN_SNAPSHOT = "55 13 * * MON"  # 5 min prima del trigger entry
 _BACKUP_RETENTION_DAYS = 30
 
 
@@ -217,6 +221,8 @@ class Orchestrator:
         manual_actions_cron: str = _CRON_MANUAL_ACTIONS,
         market_snapshot_cron: str = _CRON_MARKET_SNAPSHOT,
         market_snapshot_assets: tuple[str, ...] = DEFAULT_ASSETS,
+        option_chain_cron: str = _CRON_OPTION_CHAIN_SNAPSHOT,
+        option_chain_asset: str = "ETH",
         backup_dir: Path | None = None,
         backup_retention_days: int = _BACKUP_RETENTION_DAYS,
     ) -> AsyncIOScheduler:
@@ -282,6 +288,14 @@ class Orchestrator:
 
             await _safe("market_snapshot", _do)
 
+        async def _option_chain_snapshot() -> None:
+            async def _do() -> None:
+                await collect_option_chain_snapshot(
+                    self._ctx, asset=option_chain_asset
+                )
+
+            await _safe("option_chain_snapshot", _do)
+
         jobs: list[JobSpec] = [
             JobSpec(name="health", cron=health_cron, coro_factory=_health),
             JobSpec(name="backup", cron=backup_cron, coro_factory=_backup),
@@ -309,6 +323,13 @@ class Orchestrator:
                     coro_factory=_market_snapshot,
                 )
             )
+            jobs.append(
+                JobSpec(
+                    name="option_chain_snapshot",
+                    cron=option_chain_cron,
+                    coro_factory=_option_chain_snapshot,
+                )
+            )
         else:
             _log.warning(
                 "data analysis disabled (CERBERO_BITE_ENABLE_DATA_ANALYSIS="

src/cerbero_bite/state/migrations/0005_option_chain_snapshots.sql

@@ -0,0 +1,42 @@
+-- 0004_option_chain_snapshots.sql — catena opzioni storica
+--
+-- Snapshot della option chain Deribit, prelevata settimanalmente (cron
+-- 55 13 * * MON, appena prima del trigger entry alle 14:00 UTC) per
+-- ogni strike entro ±30% dallo spot e per ogni scadenza in finestra
+-- 14-28 DTE. Dato di base per il backtest non-stilizzato e per
+-- calibrare empiricamente lo skew premium del modello BS.
+--
+-- Granularità: una riga per (snapshot_ts, instrument). Lo
+-- snapshot_ts è il timestamp del cron tick — TUTTI i quote raccolti
+-- in quello stesso tick condividono il timestamp, così filtrare per
+-- "lo snapshot del 2026-05-04 alle 13:55" è una semplice
+-- WHERE timestamp = X.
+
+CREATE TABLE option_chain_snapshots (
+    timestamp        TEXT    NOT NULL,
+    asset            TEXT    NOT NULL,
+    instrument_name  TEXT    NOT NULL,
+    strike           TEXT    NOT NULL,
+    expiry           TEXT    NOT NULL,
+    option_type      TEXT    NOT NULL CHECK (option_type IN ('C','P')),
+    bid              TEXT,
+    ask              TEXT,
+    mid              TEXT,
+    iv               TEXT,
+    delta            TEXT,
+    gamma            TEXT,
+    theta            TEXT,
+    vega             TEXT,
+    open_interest    INTEGER,
+    volume_24h       INTEGER,
+    book_depth_top3  INTEGER,
+    PRIMARY KEY (timestamp, instrument_name)
+) WITHOUT ROWID;
+
+CREATE INDEX idx_option_chain_asset_ts
+    ON option_chain_snapshots(asset, timestamp DESC);
+
+CREATE INDEX idx_option_chain_expiry
+    ON option_chain_snapshots(asset, expiry);
+
+PRAGMA user_version = 5;

src/cerbero_bite/state/models.py

@@ -22,6 +22,7 @@ __all__ = [
     "InstructionRecord",
     "ManualAction",
     "MarketSnapshotRecord",
+    "OptionChainQuoteRecord",
     "PositionRecord",
     "PositionStatus",
     "SystemStateRecord",
@@ -148,6 +149,36 @@ class MarketSnapshotRecord(BaseModel):
     fetch_errors_json: str | None = None
 
 
+class OptionChainQuoteRecord(BaseModel):
+    """Row of the ``option_chain_snapshots`` table.
+
+    One row per (snapshot_ts, instrument) — the same ``timestamp`` is
+    shared by every quote prelevato nello stesso tick del cron.  Tutti
+    i campi numerici sono opzionali perché il collector è
+    best-effort: un ticker mancante non invalida il resto della chain.
+    """
+
+    model_config = ConfigDict(extra="forbid")
+
+    timestamp: datetime
+    asset: str
+    instrument_name: str
+    strike: Decimal
+    expiry: datetime
+    option_type: Literal["C", "P"]
+    bid: Decimal | None = None
+    ask: Decimal | None = None
+    mid: Decimal | None = None
+    iv: Decimal | None = None
+    delta: Decimal | None = None
+    gamma: Decimal | None = None
+    theta: Decimal | None = None
+    vega: Decimal | None = None
+    open_interest: int | None = None
+    volume_24h: int | None = None
+    book_depth_top3: int | None = None
+
+
 class ManualAction(BaseModel):
     """Row of the ``manual_actions`` table."""
 

src/cerbero_bite/state/repository.py

@@ -24,6 +24,7 @@ from cerbero_bite.state.models import (
     InstructionRecord,
     ManualAction,
     MarketSnapshotRecord,
+    OptionChainQuoteRecord,
     PositionRecord,
     PositionStatus,
     SystemStateRecord,
@@ -407,6 +408,103 @@ class Repository:
         ).fetchall()
         return [_row_to_market_snapshot(r) for r in rows]
 
+    # ------------------------------------------------------------------
+    # option_chain_snapshots
+    # ------------------------------------------------------------------
+
+    def record_option_chain_snapshot(
+        self,
+        conn: sqlite3.Connection,
+        quotes: list[OptionChainQuoteRecord],
+    ) -> int:
+        """Bulk-insert dei quote di un singolo tick. Tutti i quote
+        condividono lo stesso ``timestamp``. Idempotente per
+        (timestamp, instrument_name)."""
+        if not quotes:
+            return 0
+        rows = [
+            (
+                _enc_dt(q.timestamp),
+                q.asset,
+                q.instrument_name,
+                _enc_dec(q.strike),
+                _enc_dt(q.expiry),
+                q.option_type,
+                _enc_dec(q.bid),
+                _enc_dec(q.ask),
+                _enc_dec(q.mid),
+                _enc_dec(q.iv),
+                _enc_dec(q.delta),
+                _enc_dec(q.gamma),
+                _enc_dec(q.theta),
+                _enc_dec(q.vega),
+                q.open_interest,
+                q.volume_24h,
+                q.book_depth_top3,
+            )
+            for q in quotes
+        ]
+        conn.executemany(
+            "INSERT OR REPLACE INTO option_chain_snapshots("
+            "timestamp, asset, instrument_name, strike, expiry, option_type, "
+            "bid, ask, mid, iv, delta, gamma, theta, vega, "
+            "open_interest, volume_24h, book_depth_top3) "
+            "VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)",
+            rows,
+        )
+        return len(rows)
+
+    def list_option_chain_snapshots(
+        self,
+        conn: sqlite3.Connection,
+        *,
+        asset: str,
+        start: datetime | None = None,
+        end: datetime | None = None,
+        expiry_from: datetime | None = None,
+        expiry_to: datetime | None = None,
+        limit: int = 50000,
+    ) -> list[OptionChainQuoteRecord]:
+        clauses: list[str] = ["asset = ?"]
+        params: list[Any] = [asset]
+        if start is not None:
+            clauses.append("timestamp >= ?")
+            params.append(_enc_dt(start))
+        if end is not None:
+            clauses.append("timestamp <= ?")
+            params.append(_enc_dt(end))
+        if expiry_from is not None:
+            clauses.append("expiry >= ?")
+            params.append(_enc_dt(expiry_from))
+        if expiry_to is not None:
+            clauses.append("expiry <= ?")
+            params.append(_enc_dt(expiry_to))
+        params.append(int(limit))
+        rows = conn.execute(
+            f"SELECT * FROM option_chain_snapshots "
+            f"WHERE {' AND '.join(clauses)} "
+            f"ORDER BY timestamp DESC, instrument_name ASC LIMIT ?",
+            params,
+        ).fetchall()
+        return [_row_to_option_chain_quote(r) for r in rows]
+
+    def latest_option_chain_timestamp(
+        self,
+        conn: sqlite3.Connection,
+        *,
+        asset: str,
+    ) -> datetime | None:
+        """Timestamp dell'ultimo snapshot raccolto per ``asset``,
+        utile per stimare la freschezza del dato dalla GUI."""
+        row = conn.execute(
+            "SELECT timestamp FROM option_chain_snapshots "
+            "WHERE asset = ? ORDER BY timestamp DESC LIMIT 1",
+            (asset,),
+        ).fetchone()
+        if row is None:
+            return None
+        return _dec_dt(row["timestamp"])
+
     # ------------------------------------------------------------------
     # manual_actions
     # ------------------------------------------------------------------
@@ -692,6 +790,38 @@ def _row_to_market_snapshot(row: sqlite3.Row) -> MarketSnapshotRecord:
     )
 
 
+def _row_to_option_chain_quote(row: sqlite3.Row) -> OptionChainQuoteRecord:
+    return OptionChainQuoteRecord(
+        timestamp=_dec_dt_required(row["timestamp"]),
+        asset=row["asset"],
+        instrument_name=row["instrument_name"],
+        strike=_dec_dec_required(row["strike"]),
+        expiry=_dec_dt_required(row["expiry"]),
+        option_type=row["option_type"],
+        bid=_dec_dec(row["bid"]),
+        ask=_dec_dec(row["ask"]),
+        mid=_dec_dec(row["mid"]),
+        iv=_dec_dec(row["iv"]),
+        delta=_dec_dec(row["delta"]),
+        gamma=_dec_dec(row["gamma"]),
+        theta=_dec_dec(row["theta"]),
+        vega=_dec_dec(row["vega"]),
+        open_interest=(
+            int(row["open_interest"])
+            if row["open_interest"] is not None
+            else None
+        ),
+        volume_24h=(
+            int(row["volume_24h"]) if row["volume_24h"] is not None else None
+        ),
+        book_depth_top3=(
+            int(row["book_depth_top3"])
+            if row["book_depth_top3"] is not None
+            else None
+        ),
+    )
+
+
 def _dec_dec_required(value: Any) -> Decimal:
     out = _dec_dec(value)
     if out is None:

strategy.aggressiva.yaml

@@ -28,8 +28,8 @@
 # 2× via "ETH + BTC" indicato in `📚 Strategia` è una **stima ex-ante**
 # di cosa otterresti DOPO quel lavoro di codice.
 
-config_version: "1.2.0-aggressiva"
-config_hash: "e3a583cabfaa4781cd0ebcc8b62fc8f200648153738f93ab8726b062e46cacef"
+config_version: "1.3.0-aggressiva"
+config_hash: "e983e156bf0c270941765e7b9639a35fdc6de7b091076bf5a9b360e294e81e4c"
 last_review: "2026-04-26"
 last_reviewer: "Adriano"
 
@@ -65,6 +65,10 @@ entry:
   dealer_gamma_min: "0"
   dealer_gamma_filter_enabled: true
   liquidation_filter_enabled: true
+  # IV richness gate (§2.9) — abilitato a 3 pt vol per profilo aggressivo.
+  iv_minus_rv_min: "3"
+  iv_minus_rv_filter_enabled: true
+
 
 structure:
   dte_target: 18

strategy.conservativa.yaml

@@ -15,8 +15,8 @@
 #   cerbero-bite config hash --file strategy.conservativa.yaml
 # e bumpare config_version.
 
-config_version: "1.2.0-conservativa"
-config_hash: "fa09dad9cfa40a8ab006ec85157635603e0c4b6381ecd5d721504e00c4119a1b"
+config_version: "1.3.0-conservativa"
+config_hash: "900646beb1dd0a7bfaf553f76adb4b55004eff1f094585f779302131625919e8"
 last_review: "2026-04-26"
 last_reviewer: "Adriano"
 
@@ -49,6 +49,10 @@ entry:
   dealer_gamma_min: "0"
   dealer_gamma_filter_enabled: true
   liquidation_filter_enabled: true
+  # IV richness gate (§2.9). Disabilitato di default.
+  iv_minus_rv_min: "0"
+  iv_minus_rv_filter_enabled: false
+
 
 structure:
   dte_target: 18

strategy.yaml

@@ -6,8 +6,8 @@
 # config hash), and lands as a separate commit with the motivation in
 # the commit message.
 
-config_version: "1.2.0"
-config_hash: "33263a313b26b24b41269f93f93783784451ac9b4b6460005b95c2fb3624fcdc"
+config_version: "1.3.0"
+config_hash: "178a87467707d54d1ffef2d585a3a01be54de5ccc7e23493356eac47fd1c24d8"
 last_review: "2026-04-26"
 last_reviewer: "Adriano"
 
@@ -45,6 +45,10 @@ entry:
   dealer_gamma_min: "0"
   dealer_gamma_filter_enabled: true
   liquidation_filter_enabled: true
+  # IV richness gate (§2.9). Disabilitato di default.
+  iv_minus_rv_min: "0"
+  iv_minus_rv_filter_enabled: false
+
 
 structure:
   dte_target: 18

tests/integration/test_entry_cycle.py

@@ -118,6 +118,16 @@ def _wire_market_snapshot(
         },
         is_reusable=True,
     )
+    httpx_mock.add_response(
+        url="http://mcp-deribit:9011/tools/get_realized_vol",
+        json={
+            "currency": "ETH",
+            "realized_vol_pct": {"14d": 30.0, "30d": 30.0},
+            "iv_current_pct": 38.0,
+            "iv_minus_rv_pct": {"14d": 8.0, "30d": 8.0},
+        },
+        is_reusable=True,
+    )
     httpx_mock.add_response(
         url="http://mcp-sentiment:9014/tools/get_liquidation_heatmap",
         json={

tests/integration/test_orchestrator.py

@@ -129,6 +129,7 @@ def test_install_scheduler_registers_canonical_jobs(tmp_path: Path) -> None:
         "backup",
         "manual_actions",
         "market_snapshot",
+        "option_chain_snapshot",
     }
 
 

tests/unit/test_backtest.py

@@ -0,0 +1,259 @@
+"""TDD per :mod:`cerbero_bite.core.backtest`."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime, timedelta
+from decimal import Decimal
+
+import pytest
+
+from cerbero_bite.config import StrategyConfig, golden_config
+from cerbero_bite.core.backtest import (
+    bs_put_delta,
+    bs_put_price,
+    estimate_credit_eth,
+    find_strike_for_delta,
+    monday_picks,
+    normal_cdf,
+    run_backtest,
+    simulate_entry_filters,
+)
+from cerbero_bite.state.models import MarketSnapshotRecord
+
+
+# ---------------------------------------------------------------------------
+# Black-Scholes helpers
+# ---------------------------------------------------------------------------
+
+
+def test_normal_cdf_known_values() -> None:
+    assert normal_cdf(0.0) == pytest.approx(0.5, abs=1e-6)
+    assert normal_cdf(1.0) == pytest.approx(0.8413, abs=1e-3)
+    assert normal_cdf(-1.0) == pytest.approx(0.1587, abs=1e-3)
+    assert normal_cdf(2.0) == pytest.approx(0.9772, abs=1e-3)
+
+
+def test_bs_put_price_atm_positive_and_less_than_strike() -> None:
+    p = bs_put_price(spot=3000, strike=3000, t_years=18 / 365, sigma=0.50)
+    assert p > 0
+    assert p < 3000  # cap
+
+
+def test_bs_put_price_far_otm_close_to_zero() -> None:
+    p = bs_put_price(spot=3000, strike=1500, t_years=18 / 365, sigma=0.50)
+    assert 0 <= p < 5  # essentially zero
+
+
+def test_bs_put_delta_atm_around_minus_half() -> None:
+    d = bs_put_delta(spot=3000, strike=3000, t_years=18 / 365, sigma=0.50)
+    assert d == pytest.approx(-0.475, abs=0.05)
+
+
+def test_bs_put_delta_far_otm_close_to_zero() -> None:
+    d = bs_put_delta(spot=3000, strike=1500, t_years=18 / 365, sigma=0.50)
+    assert -0.05 < d <= 0
+
+
+def test_find_strike_for_delta_monotone() -> None:
+    spot = 3000.0
+    dvol = 50.0
+    dte = 18
+    s_010 = find_strike_for_delta(
+        spot=spot, dvol_pct=dvol, dte_days=dte, target_delta_abs=0.10,
+    )
+    s_020 = find_strike_for_delta(
+        spot=spot, dvol_pct=dvol, dte_days=dte, target_delta_abs=0.20,
+    )
+    # |Δ|=0.20 (più ITM) ⇒ strike più alto di |Δ|=0.10 (più OTM).
+    assert s_020 > s_010
+    # Verifica che il delta corrisponda a target ± tolleranza.
+    achieved = abs(
+        bs_put_delta(
+            spot=spot, strike=s_020, t_years=dte / 365, sigma=dvol / 100,
+        )
+    )
+    assert achieved == pytest.approx(0.20, abs=0.02)
+
+
+def test_estimate_credit_returns_positive_credit_in_normal_regime() -> None:
+    credit_eth, short_k, long_k = estimate_credit_eth(
+        spot=3000, dvol_pct=50, dte_days=18, width_pct=0.04, delta_target_abs=0.12,
+    )
+    # Sanity: credit > 0, short_k < spot, long_k = short_k - 4%×spot
+    assert credit_eth > 0
+    assert short_k < 3000
+    assert long_k < short_k
+    assert short_k - long_k == pytest.approx(0.04 * 3000, abs=1.0)
+
+
+# ---------------------------------------------------------------------------
+# Monday picks + entry filter simulation
+# ---------------------------------------------------------------------------
+
+
+def _snap(
+    *, ts: datetime,
+    spot: float = 3000,
+    dvol: float = 50,
+    funding: float = 0.0,
+    macro_d: int | None = None,
+    asset: str = "ETH",
+) -> MarketSnapshotRecord:
+    return MarketSnapshotRecord(
+        timestamp=ts,
+        asset=asset,
+        spot=Decimal(str(spot)),
+        dvol=Decimal(str(dvol)),
+        funding_perp_annualized=Decimal(str(funding)),
+        funding_cross_annualized=Decimal("0"),
+        dealer_net_gamma=Decimal("100"),
+        liquidation_long_risk="low",
+        liquidation_short_risk="low",
+        macro_days_to_event=macro_d,
+        fetch_ok=True,
+    )
+
+
+def test_monday_picks_extracts_one_per_iso_week() -> None:
+    monday_2026_05_04 = datetime(2026, 5, 4, 14, 0, tzinfo=UTC)
+    monday_2026_05_11 = datetime(2026, 5, 11, 14, 0, tzinfo=UTC)
+    snapshots = [
+        _snap(ts=monday_2026_05_04),
+        _snap(ts=monday_2026_05_04 + timedelta(minutes=15)),  # not picked
+        _snap(ts=monday_2026_05_11),
+    ]
+    picks = monday_picks(snapshots)
+    assert len(picks) == 2
+    assert picks[0].timestamp == monday_2026_05_04
+    assert picks[1].timestamp == monday_2026_05_11
+
+
+def test_monday_picks_skips_other_days_and_hours() -> None:
+    snapshots = [
+        _snap(ts=datetime(2026, 5, 4, 13, 0, tzinfo=UTC)),  # Monday 13:00
+        _snap(ts=datetime(2026, 5, 5, 14, 0, tzinfo=UTC)),  # Tuesday 14:00
+    ]
+    assert monday_picks(snapshots) == []
+
+
+def test_monday_picks_filters_by_asset() -> None:
+    monday = datetime(2026, 5, 4, 14, 0, tzinfo=UTC)
+    snapshots = [
+        _snap(ts=monday, asset="BTC"),
+        _snap(ts=monday, asset="ETH"),
+    ]
+    picks = monday_picks(snapshots, asset="ETH")
+    assert len(picks) == 1
+    assert picks[0].snapshot.asset == "ETH"
+
+
+def test_simulate_entry_filters_accepts_clean_snapshot(
+) -> None:
+    cfg: StrategyConfig = golden_config()
+    monday = datetime(2026, 5, 4, 14, 0, tzinfo=UTC)
+    snap = _snap(ts=monday, dvol=50, funding=0.10)
+    picks = [
+        type("MP", (), {"timestamp": monday, "snapshot": snap})()  # type: ignore[arg-type]
+    ]
+    # Hack: build via real dataclass
+    from cerbero_bite.core.backtest import MondayPick
+    picks = [MondayPick(timestamp=monday, snapshot=snap)]
+    results = simulate_entry_filters(picks, cfg, capital_usd=Decimal("1500"))
+    assert len(results) == 1
+    assert results[0].accepted is True
+
+
+def test_simulate_entry_filters_rejects_dvol_out_of_band() -> None:
+    cfg = golden_config()
+    monday = datetime(2026, 5, 4, 14, 0, tzinfo=UTC)
+    snap = _snap(ts=monday, dvol=20, funding=0.10)  # below 35
+    from cerbero_bite.core.backtest import MondayPick
+    picks = [MondayPick(timestamp=monday, snapshot=snap)]
+    results = simulate_entry_filters(picks, cfg, capital_usd=Decimal("1500"))
+    assert results[0].accepted is False
+    assert any("dvol" in r.lower() for r in results[0].reasons)
+
+
+def test_simulate_entry_filters_skips_incomplete_snapshot() -> None:
+    cfg = golden_config()
+    monday = datetime(2026, 5, 4, 14, 0, tzinfo=UTC)
+    incomplete = MarketSnapshotRecord(
+        timestamp=monday, asset="ETH", spot=Decimal("3000"),
+        # dvol=None ⇒ skipped
+        fetch_ok=False,
+    )
+    from cerbero_bite.core.backtest import MondayPick
+    picks = [MondayPick(timestamp=monday, snapshot=incomplete)]
+    results = simulate_entry_filters(picks, cfg, capital_usd=Decimal("1500"))
+    assert results[0].accepted is False
+    assert results[0].skipped_for_data is True
+
+
+# ---------------------------------------------------------------------------
+# Full pipeline (sintetico)
+# ---------------------------------------------------------------------------
+
+
+def _synthetic_year_of_snapshots(
+    *,
+    n_weeks: int = 8,
+    spot: float = 3000,
+    dvol: float = 60,  # con skew_premium 1.5 ⇒ credit/width ≈ 35% (sopra soglia 30%)
+    funding: float = 0.10,
+) -> list[MarketSnapshotRecord]:
+    """Genera N settimane di snapshot sintetici ETH a 4 tick/settimana."""
+    rows: list[MarketSnapshotRecord] = []
+    monday = datetime(2026, 5, 4, 14, 0, tzinfo=UTC)
+    for week in range(n_weeks):
+        base = monday + timedelta(weeks=week)
+        # Lunedì 14:00 è il pick
+        rows.append(_snap(ts=base, spot=spot, dvol=dvol, funding=funding))
+        # Tick intermedi che NON cadono di lunedì alle 14:00:
+        # offset +1h così vengono ignorati da `monday_picks`.
+        for d in (2, 8, 14, 19):
+            rows.append(
+                _snap(
+                    ts=base + timedelta(days=d, hours=1),
+                    spot=spot * (1 + 0.005 * d),  # +0.5% al giorno
+                    dvol=dvol - 1.5 * d,  # vol che scende lentamente
+                    funding=funding,
+                )
+            )
+    return rows
+
+
+def test_run_backtest_produces_report_with_trades() -> None:
+    # Per il test scaliamo il credit/width gate al 15%: il modello BS
+    # senza skew completo sottostima i premi OTM rispetto al reale.
+    # Vedi `estimate_credit_eth.skew_premium` docstring per dettagli.
+    from cerbero_bite.config.schema import StructureConfig
+    cfg = golden_config()
+    cfg = cfg.model_copy(
+        update={
+            "structure": StructureConfig(
+                **{
+                    **cfg.structure.model_dump(),
+                    "credit_to_width_ratio_min": Decimal("0.15"),
+                }
+            )
+        }
+    )
+    snapshots = _synthetic_year_of_snapshots(n_weeks=4)
+    report = run_backtest(snapshots, cfg, capital_usd=Decimal("1500"))
+    # Sanity: 4 picks, almeno 1 trade chiuso
+    assert report.n_picks == 4
+    assert report.n_completed >= 1
+    assert report.cumulative_pnl_usd != Decimal("0")
+    # Bull-put + ETH al rialzo + DVOL che scende ⇒ atteso win
+    assert report.n_winners >= 1
+
+
+def test_run_backtest_handles_no_picks_gracefully() -> None:
+    cfg = golden_config()
+    # Solo tick infrasettimanali, niente Monday 14:00.
+    monday = datetime(2026, 5, 4, 14, 0, tzinfo=UTC)
+    snapshots = [_snap(ts=monday + timedelta(hours=1))]
+    report = run_backtest(snapshots, cfg, capital_usd=Decimal("1500"))
+    assert report.n_picks == 0
+    assert report.n_completed == 0
+    assert report.cumulative_pnl_usd == Decimal("0")

tests/unit/test_config_loader.py

@@ -68,7 +68,7 @@ def test_compute_hash_is_independent_of_recorded_hash_value(tmp_path: Path) -> N
 def test_load_repo_strategy_yaml(tmp_path: Path) -> None:
     """The committed strategy.yaml validates with the recorded hash."""
     result = load_strategy(REPO_ROOT / "strategy.yaml")
-    assert result.config.config_version == "1.2.0"
+    assert result.config.config_version == "1.3.0"
     assert result.config.sizing.kelly_fraction == Decimal("0.13")
     assert result.computed_hash == result.config.config_hash
 

tests/unit/test_entry_validator.py

@@ -194,6 +194,62 @@ def test_dealer_gamma_filter_disabled_in_config(cfg: StrategyConfig) -> None:
     assert decision.accepted is True
 
 
+# ---------------------------------------------------------------------------
+# IV richness gate (§2.9)
+# ---------------------------------------------------------------------------
+
+
+def _strict_iv_rv_cfg(
+    cfg: StrategyConfig, *, threshold: Decimal = Decimal("5")
+) -> StrategyConfig:
+    return golden_config(
+        entry=EntryConfig(
+            **{
+                **cfg.entry.model_dump(),
+                "iv_minus_rv_filter_enabled": True,
+                "iv_minus_rv_min": threshold,
+            }
+        )
+    )
+
+
+def test_iv_richness_gate_disabled_by_default_lets_thin_premium_pass(
+    cfg: StrategyConfig,
+) -> None:
+    # Default config: filter disabled. Anche con IV-RV negativa (RV>IV)
+    # l'entry deve passare per non rompere setup pre-calibrazione.
+    decision = validate_entry(_good_ctx(iv_minus_rv=Decimal("-2")), cfg)
+    assert decision.accepted is True
+
+
+def test_iv_richness_gate_blocks_when_below_floor(cfg: StrategyConfig) -> None:
+    strict = _strict_iv_rv_cfg(cfg, threshold=Decimal("5"))
+    decision = validate_entry(_good_ctx(iv_minus_rv=Decimal("3")), strict)
+    assert decision.accepted is False
+    assert any("IV richness" in r for r in decision.reasons)
+
+
+def test_iv_richness_gate_passes_when_above_floor(cfg: StrategyConfig) -> None:
+    strict = _strict_iv_rv_cfg(cfg, threshold=Decimal("5"))
+    decision = validate_entry(_good_ctx(iv_minus_rv=Decimal("6")), strict)
+    assert decision.accepted is True
+
+
+def test_iv_richness_gate_passes_at_exact_threshold(cfg: StrategyConfig) -> None:
+    # Soglia inclusiva: IV-RV == soglia → accettato (gate è "<", non "<=").
+    strict = _strict_iv_rv_cfg(cfg, threshold=Decimal("5"))
+    decision = validate_entry(_good_ctx(iv_minus_rv=Decimal("5")), strict)
+    assert decision.accepted is True
+
+
+def test_iv_richness_gate_skipped_when_data_missing(cfg: StrategyConfig) -> None:
+    # MCP irraggiungibile: best-effort skip, non bloccare l'entry per
+    # un problema di infrastruttura.
+    strict = _strict_iv_rv_cfg(cfg, threshold=Decimal("5"))
+    decision = validate_entry(_good_ctx(iv_minus_rv=None), strict)
+    assert decision.accepted is True
+
+
 def test_validate_entry_accumulates_all_reasons(cfg: StrategyConfig) -> None:
     decision = validate_entry(
         _good_ctx(

tests/unit/test_option_chain_snapshot_cycle.py

@@ -0,0 +1,134 @@
+"""TDD per :mod:`cerbero_bite.runtime.option_chain_snapshot_cycle`."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime
+from decimal import Decimal
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from cerbero_bite.clients.deribit import InstrumentMeta
+from cerbero_bite.runtime.option_chain_snapshot_cycle import (
+    collect_option_chain_snapshot,
+)
+from cerbero_bite.state.models import OptionChainQuoteRecord
+
+
+_NOW = datetime(2026, 5, 4, 13, 55, tzinfo=UTC)
+
+
+def _meta(name: str, strike: int, expiry_dte: int = 18) -> InstrumentMeta:
+    expiry = _NOW.replace(hour=8, minute=0, second=0)
+    expiry = expiry.replace(day=expiry.day) + (
+        # add days
+        __import__("datetime").timedelta(days=expiry_dte)
+    )
+    return InstrumentMeta(
+        name=name,
+        strike=Decimal(str(strike)),
+        expiry=expiry,
+        option_type="P",
+        open_interest=Decimal("100"),
+        tick_size=Decimal("0.0005"),
+        min_trade_amount=Decimal("1"),
+    )
+
+
+def _ticker(name: str, *, mark: float = 0.020, bid: float = 0.018,
+            ask: float = 0.022, delta: float = -0.12) -> dict:
+    return {
+        "instrument_name": name,
+        "bid": bid,
+        "ask": ask,
+        "mark_price": mark,
+        "mark_iv": 60.0,
+        "volume_24h": 50,
+        "greeks": {
+            "delta": delta,
+            "gamma": 0.001,
+            "theta": -0.0005,
+            "vega": 0.10,
+        },
+    }
+
+
+@pytest.fixture
+def cfg() -> object:
+    from cerbero_bite.config import golden_config
+    return golden_config()
+
+
+@pytest.fixture
+def fake_ctx(cfg: object) -> MagicMock:
+    """Mock minimal RuntimeContext."""
+    ctx = MagicMock()
+    ctx.cfg = cfg
+    ctx.db_path = ":memory:"
+    return ctx
+
+
+@pytest.mark.asyncio
+async def test_collector_persists_one_quote_per_instrument(
+    fake_ctx: MagicMock,
+) -> None:
+    metas = [_meta("ETH-21MAY26-2475-P", 2475), _meta("ETH-21MAY26-2400-P", 2400)]
+    fake_ctx.deribit.options_chain = AsyncMock(return_value=metas)
+    fake_ctx.deribit.get_tickers = AsyncMock(
+        return_value=[_ticker(m.name) for m in metas]
+    )
+    persisted: list[list[OptionChainQuoteRecord]] = []
+
+    def _record(_conn: object, qs: list[OptionChainQuoteRecord]) -> int:
+        persisted.append(qs)
+        return len(qs)
+
+    fake_ctx.repository.record_option_chain_snapshot = _record
+
+    n = await collect_option_chain_snapshot(fake_ctx, asset="ETH", now=_NOW)
+    assert n == 2
+    assert len(persisted) == 1
+    assert {q.instrument_name for q in persisted[0]} == {
+        "ETH-21MAY26-2475-P", "ETH-21MAY26-2400-P",
+    }
+    # Tutti i quote condividono il timestamp del cron tick.
+    assert all(q.timestamp == _NOW for q in persisted[0])
+
+
+@pytest.mark.asyncio
+async def test_collector_handles_missing_tickers_with_null_fields(
+    fake_ctx: MagicMock,
+) -> None:
+    metas = [_meta("ETH-21MAY26-2475-P", 2475)]
+    fake_ctx.deribit.options_chain = AsyncMock(return_value=metas)
+    fake_ctx.deribit.get_tickers = AsyncMock(return_value=[])  # vuoto
+    persisted: list[list[OptionChainQuoteRecord]] = []
+
+    def _record(_conn: object, qs: list[OptionChainQuoteRecord]) -> int:
+        persisted.append(qs)
+        return len(qs)
+
+    fake_ctx.repository.record_option_chain_snapshot = _record
+
+    n = await collect_option_chain_snapshot(fake_ctx, now=_NOW)
+    assert n == 1
+    assert persisted[0][0].mid is None  # ticker mancante ⇒ campi NULL
+    assert persisted[0][0].instrument_name == "ETH-21MAY26-2475-P"
+
+
+@pytest.mark.asyncio
+async def test_collector_returns_zero_when_chain_empty(
+    fake_ctx: MagicMock,
+) -> None:
+    fake_ctx.deribit.options_chain = AsyncMock(return_value=[])
+    n = await collect_option_chain_snapshot(fake_ctx, now=_NOW)
+    assert n == 0
+
+
+@pytest.mark.asyncio
+async def test_collector_swallows_chain_fetch_failure(
+    fake_ctx: MagicMock,
+) -> None:
+    fake_ctx.deribit.options_chain = AsyncMock(side_effect=RuntimeError("boom"))
+    n = await collect_option_chain_snapshot(fake_ctx, now=_NOW)
+    assert n == 0  # best-effort: non rilancia