"""PairsWorker — paper trading a 2 GAMBE per la famiglia PR01 (spread reversion). Market-neutral: long asset A / short asset B (o viceversa) sullo z-score del log-ratio. Distinto dallo StrategyWorker single-leg: gestisce due strumenti, due prezzi di ingresso, e conta le fee su ENTRAMBE le gambe (2*fee_rt*lev = 0.20% RT/coppia con fee_rt=0.001). Semantica identica al backtest scripts/analysis/pairs_research.pairs_sim: r[i] = log(closeA[i]/closeB[i]); z[i] = (r[i]-SMA_n(r)[i]) / STD_n(r)[i] (causale) ENTRY a close[i]: z<=-z_in -> LONG ratio (long A / short B); z>=+z_in -> SHORT ratio EXIT: |z| <= z_exit (rientro) oppure time-limit max_bars filtro candele sporche: salta l'ingresso se |dr[i]| > jump_max PnL = (retA - retB) * direction * lev - 2*fee_rt*lev (notional uguale per gamba) Stato persistente (resume al restart) e log come StrategyWorker. """ from __future__ import annotations import json from datetime import datetime, timezone from pathlib import Path import numpy as np import pandas as pd from src.live.telegram_notifier import notify_event class PairsWorker: def __init__( self, asset_a: str, asset_b: str, tf: str, params: dict | None = None, capital: float = 1000.0, position_size: float = 0.15, leverage: float = 3.0, fee_rt: float = 0.001, # per gamba RT; la coppia paga 2x name: str = "PR01_pairs_reversion", data_dir: Path = Path("data/paper_trades"), executor=None, # PairsExecutionClient: esecuzione REALE shadow a 2 gambe exec_instruments: dict | None = None, # {asset: instrument USDC} real_truth: bool = False, ): self.asset_a = asset_a self.asset_b = asset_b self.tf = tf self.name = name p = params or {} self.n = int(p.get("n", 50)) self.z_in = float(p.get("z_in", 2.0)) self.z_exit = float(p.get("z_exit", 0.75)) self.max_bars = int(p.get("max_bars", 72)) self.jump_max = float(p.get("jump_max", 0.08)) # flat-skip (timeframe sub-orari, es. 15m): non entrare/uscire su candele flat # (O=H=L=C, prezzo stale/liquidita' zero -> fill non eseguibile). LIVE-REALIZABLE: # l'uscita arma exit_ready e si esegue alla prima barra PULITA. Parita' col backtest # pairs_research.pairs_sim_flat(flat_skip=True). Default off = comportamento 1h storico. self.flat_skip = bool(p.get("flat_skip", False)) self.initial_capital = capital self.position_size = position_size self.leverage = leverage self.fee_rt = fee_rt self.worker_id = f"{name}__{asset_a}_{asset_b}__{tf}" self.work_dir = data_dir / self.worker_id self.work_dir.mkdir(parents=True, exist_ok=True) self.trades_path = self.work_dir / "trades.jsonl" self.status_path = self.work_dir / "status.json" self.capital = capital self.in_position = False self.direction = 0 # +1 long ratio (long A/short B), -1 short ratio self.entry_a = 0.0 self.entry_b = 0.0 self.entry_z = 0.0 self.entry_time = "" self.bars_held = 0 self.exit_ready = False # flat-skip: condizione di uscita armata, attende barra pulita self.total_trades = 0 self.total_wins = 0 self.last_bar_ts = 0 self.started_at = datetime.now(timezone.utc).isoformat() # --- esecuzione REALE shadow a 2 gambe (sim resta la verita' che guida) --- self.executor = executor self.exec_instruments = exec_instruments or {} self.inst_a = self.exec_instruments.get(asset_a) self.inst_b = self.exec_instruments.get(asset_b) self.execution_enabled = bool(executor and self.inst_a and self.inst_b) # REAL-TRUTH (2026-06-10): come StrategyWorker — `capital` aggiornato dal # PnL dei fill reali (2 gambe, fee reali); sim solo diagnostica nel log. self.real_truth = bool(real_truth and self.execution_enabled) self.real_capital = capital self.real_in_position = False self.real_dir = 0 self.real_side_a = "" # lato della gamba A all'apertura ("buy"/"sell") self.real_side_b = "" self.real_amount_a = 0.0 # amount eseguito per gamba (base-coin) self.real_amount_b = 0.0 self.real_entry_a = 0.0 # prezzo di fill per gamba self.real_entry_b = 0.0 self.real_notional_a = 0.0 # USD effettivi per gamba self.real_notional_b = 0.0 self.real_entry_fee = 0.0 self.real_trades = 0 self.real_first_notified = False self.orphan_legs: list[dict] = [] # gambe respinte dal netting (persistite) self._load_state() self._save_state() # ---------------- persistenza ---------------- def _load_state(self): if not self.status_path.exists(): self._log("INIT", {"capital": self.capital, "pair": f"{self.asset_a}/{self.asset_b}", "tf": self.tf, "params": {"n": self.n, "z_in": self.z_in, "z_exit": self.z_exit, "max_bars": self.max_bars}}) return with open(self.status_path) as f: s = json.load(f) self.capital = s.get("capital", self.initial_capital) self.in_position = s.get("in_position", False) self.direction = s.get("direction", 0) self.entry_a = s.get("entry_a", 0.0) self.entry_b = s.get("entry_b", 0.0) self.entry_z = s.get("entry_z", 0.0) self.entry_time = s.get("entry_time", "") self.bars_held = s.get("bars_held", 0) self.exit_ready = s.get("exit_ready", False) self.total_trades = s.get("total_trades", 0) self.total_wins = s.get("total_wins", 0) self.last_bar_ts = s.get("last_bar_ts", 0) self.started_at = s.get("started_at", self.started_at) self.real_capital = s.get("real_capital", self.initial_capital) self.real_in_position = s.get("real_in_position", False) self.real_dir = s.get("real_dir", 0) self.real_side_a = s.get("real_side_a", "") self.real_side_b = s.get("real_side_b", "") self.real_amount_a = s.get("real_amount_a", 0.0) self.real_amount_b = s.get("real_amount_b", 0.0) self.real_entry_a = s.get("real_entry_a", 0.0) self.real_entry_b = s.get("real_entry_b", 0.0) self.real_notional_a = s.get("real_notional_a", 0.0) self.real_notional_b = s.get("real_notional_b", 0.0) self.real_entry_fee = s.get("real_entry_fee", 0.0) self.real_trades = s.get("real_trades", 0) self.real_first_notified = s.get("real_first_notified", False) self.orphan_legs = s.get("orphan_legs", []) self._log("RESUME", {"capital": round(self.capital, 2), "total_trades": self.total_trades, "in_position": self.in_position, "real_capital": round(self.real_capital, 2), "real_in_position": self.real_in_position}) def _save_state(self): state = { "capital": round(self.capital, 2), "in_position": self.in_position, "direction": self.direction, "entry_a": self.entry_a, "entry_b": self.entry_b, "entry_z": round(self.entry_z, 4), "entry_time": self.entry_time, "bars_held": self.bars_held, "exit_ready": self.exit_ready, "total_trades": self.total_trades, "total_wins": self.total_wins, "last_bar_ts": self.last_bar_ts, "started_at": self.started_at, "last_update": datetime.now(timezone.utc).isoformat(), "real_capital": round(self.real_capital, 4), "real_in_position": self.real_in_position, "real_dir": self.real_dir, "real_side_a": self.real_side_a, "real_side_b": self.real_side_b, "real_amount_a": self.real_amount_a, "real_amount_b": self.real_amount_b, "real_entry_a": self.real_entry_a, "real_entry_b": self.real_entry_b, "real_notional_a": self.real_notional_a, "real_notional_b": self.real_notional_b, "real_entry_fee": self.real_entry_fee, "real_trades": self.real_trades, "real_first_notified": self.real_first_notified, "orphan_legs": self.orphan_legs, } with open(self.status_path, "w") as f: json.dump(state, f, indent=2) def _log(self, event: str, data: dict | None = None): entry = {"ts": datetime.now(timezone.utc).isoformat(), "worker": self.worker_id, "event": event, **(data or {})} with open(self.trades_path, "a") as f: f.write(json.dumps(entry) + "\n") print(f" [{self.worker_id}] {event}: {json.dumps(data or {}, default=str)}") def _notify(self, event: str, data: dict | None = None): notify_event(event, {"worker": self.worker_id, **(data or {})}) # ---------------- segnale ---------------- def _zscore(self, ca: np.ndarray, cb: np.ndarray) -> tuple[np.ndarray, np.ndarray]: r = np.log(ca / cb) ma = pd.Series(r).rolling(self.n).mean().values sd = pd.Series(r).rolling(self.n).std().values z = (r - ma) / np.where(sd == 0, np.nan, sd) dr = np.abs(np.diff(r, prepend=r[0])) return z, dr # ---------------- trading ---------------- def _open(self, d: int, ca: float, cb: float, z: float): self.in_position = True self.direction = d self.entry_a, self.entry_b, self.entry_z = ca, cb, z self.entry_time = datetime.now(timezone.utc).isoformat() self.bars_held = 0 self.exit_ready = False data = {"direction": "long_ratio" if d == 1 else "short_ratio", "long_leg": self.asset_a if d == 1 else self.asset_b, "short_leg": self.asset_b if d == 1 else self.asset_a, "entry_a": round(ca, 4), "entry_b": round(cb, 4), "z": round(z, 3), "capital": round(self.capital, 2)} self._log("OPEN", data); self._notify("OPENED", data) if self.execution_enabled: self._real_open_pair(d, ca, cb) def _real_open_pair(self, d: int, sim_a: float, sim_b: float): """Apertura REALE shadow a 2 gambe (long A/short B se d=1). Notional uguale per gamba = capital*pos*lev. Logga slippage e fee reali; gestisce il leg-fail.""" notional = self.capital * self.position_size * self.leverage pf = self.executor.open_pair(self.inst_a, self.inst_b, d, notional, label=self.worker_id) data = {"dir": d, "inst_a": self.inst_a, "inst_b": self.inst_b, "notional_leg": round(notional, 2), "fill_a": pf.leg_a.fill_price, "fill_b": pf.leg_b.fill_price, "fee_usd": round(pf.leg_a.fee_usd + pf.leg_b.fee_usd, 5), "verified": pf.verified} if pf.verified: self.real_in_position = True self.real_dir = d self.real_side_a, self.real_side_b = pf.leg_a.side, pf.leg_b.side # amount FILLATO, non richiesto (coerente con strategy_worker, 2026-06-11) self.real_amount_a = pf.leg_a.filled_amount or pf.leg_a.amount self.real_amount_b = pf.leg_b.filled_amount or pf.leg_b.amount self.real_entry_a = pf.leg_a.fill_price or sim_a self.real_entry_b = pf.leg_b.fill_price or sim_b self.real_notional_a = pf.leg_a.amount * self.real_entry_a self.real_notional_b = pf.leg_b.amount * self.real_entry_b self.real_entry_fee = pf.leg_a.fee_usd + pf.leg_b.fee_usd self._log("REAL_OPEN_PAIR", data) if not self.real_first_notified: self._notify("REAL_EXEC_LIVE", data); self.real_first_notified = True else: self._log("REAL_OPEN_FAIL", {**data, "note": pf.notes}) self._notify("REAL_OPEN_FAIL", {**data, "note": pf.notes}) self._save_state() # persisti subito il ledger reale (resume-safe sui crash) def _real_close_pair(self, sim_a: float, sim_b: float, reason: str, sim_pnl: float) -> tuple[float | None, bool]: """Chiusura REALE shadow: richiude entrambe le gambe (netting-aware), riconcilia PnL reale per-gamba e fee, aggiorna il ledger reale parallelo. Ritorna (real_pnl, applied): applied=True SOLO se ENTRAMBE le gambe hanno chiuso per intero con fill verificato — con una gamba orfana il "PnL dello spread" non esiste e real-truth ricade sul sim DICHIARATO.""" if not self.real_in_position: return None, False pf = self.executor.close_pair(self.inst_a, self.inst_b, self.real_side_a, self.real_side_b, self.real_amount_a, self.real_amount_b, label=self.worker_id) # VERITA' PER-GAMBA (audit 2026-06-11): una gamba puo' essere RESPINTA dal # netting di conto (reduce-only nel verso sbagliato quando un altro worker e' # nella direzione opposta sullo stesso strumento). Prima il PnL veniva # calcolato col prezzo SIM per la gamba mai eseguita e sommato al ledger # reale (3 PnL fantasma il 2026-06-11, gamba ETH orfana sul conto). # Ora: si booka SOLO il realizzato delle gambe con fill verificato; la gamba # respinta diventa un ORFANO registrato (persistito) + alert Telegram. from src.live.execution import contract_spec for leg in (pf.leg_a, pf.leg_b): if "netting" in (getattr(leg, "notes", "") or ""): # reduce-only cappato/respinto, residuo in market puro (v1.1.25) self._log("NET_CLOSE", {"instrument": leg.instrument, "note": leg.notes}) self._notify("NET_CLOSE", {"instrument": leg.instrument, "note": leg.notes}) # verita' per-FRAZIONE di gamba (code-review 2026-06-11): una gamba puo' # chiudere PARZIALMENTE (reduce-only cappato + netting negato/fallito) — # si booka il gross della sola frazione FILLATA e l'orfano registra il # solo RESIDUO (prima: gross binario tutto-o-niente e orfano a amount # pieno, che falsava reconciler e real_capital della parte gia' chiusa). filled_a = min(getattr(pf.leg_a, "filled_amount", 0.0), self.real_amount_a) filled_b = min(getattr(pf.leg_b, "filled_amount", 0.0), self.real_amount_b) step_a = contract_spec(self.inst_a).get("step", 0.001) step_b = contract_spec(self.inst_b).get("step", 0.001) ok_a = filled_a >= self.real_amount_a - step_a / 2 ok_b = filled_b >= self.real_amount_b - step_b / 2 frac_a = filled_a / self.real_amount_a if self.real_amount_a else 0.0 frac_b = filled_b / self.real_amount_b if self.real_amount_b else 0.0 exit_a = pf.leg_a.fill_price or sim_a exit_b = pf.leg_b.fill_price or sim_b # PnL per gamba: dir A = +d (long ratio compra A), dir B = -d da, db = self.real_dir, -self.real_dir gross_a = da * (exit_a - self.real_entry_a) / self.real_entry_a * self.real_notional_a gross_b = db * (exit_b - self.real_entry_b) / self.real_entry_b * self.real_notional_b exit_fee = pf.leg_a.fee_usd + pf.leg_b.fee_usd real_pnl = (gross_a * frac_a + gross_b * frac_b - self.real_entry_fee - exit_fee) self.real_capital += real_pnl self.real_trades += 1 self._log("REAL_CLOSE_PAIR", { "reason": reason, "exit_a": exit_a, "exit_b": exit_b, "leg_a_ok": ok_a, "leg_b_ok": ok_b, "filled_a": filled_a, "filled_b": filled_b, "real_pnl_usd": round(real_pnl, 4), "sim_pnl_usd": round(sim_pnl, 4), "entry_fee": round(self.real_entry_fee, 5), "exit_fee": round(exit_fee, 5), "real_capital": round(self.real_capital, 4), "verified": pf.verified}) for ok, inst, side, amt, filled, step in ( (ok_a, self.inst_a, self.real_side_a, self.real_amount_a, filled_a, step_a), (ok_b, self.inst_b, self.real_side_b, self.real_amount_b, filled_b, step_b)): residue = amt - filled if not ok and residue >= step / 2: orphan = {"instrument": inst, "entry_side": side, "amount": round(residue, 8), "ts": datetime.now(timezone.utc).isoformat(), "reason": reason} self.orphan_legs.append(orphan) self._notify("PAIR_LEG_ORPHAN", { "worker": self.worker_id, **orphan, "note": ("gamba NON chiusa per il residuo indicato (netting " "negato/fallito): posizione orfana sul conto — " "risolvere e RIMUOVERE l'orfano dallo status")}) self.real_in_position = False self.real_dir = 0 self.real_side_a = self.real_side_b = "" self.real_amount_a = self.real_amount_b = 0.0 self.real_entry_a = self.real_entry_b = 0.0 self.real_notional_a = self.real_notional_b = 0.0 self.real_entry_fee = 0.0 self._save_state() # applied (real-truth) SOLO se entrambe le gambe hanno chiuso verificate: # con una gamba orfana il "PnL reale dello spread" non esiste -> meglio il # fallback sim DICHIARATO che un numero mezzo-reale return real_pnl, ok_a and ok_b def _close(self, ca: float, cb: float, z: float, reason: str): if not self.in_position: return ret_a = (ca - self.entry_a) / self.entry_a ret_b = (cb - self.entry_b) / self.entry_b gross = (ret_a - ret_b) * self.direction * self.leverage fee = 2 * self.fee_rt * self.leverage # 2 gambe net = gross - fee sim_pnl = self.capital * self.position_size * net # REAL-TRUTH: chiusura reale PRIMA dell'update ledger (come StrategyWorker) real_pnl, real_applied = (None, False) if self.execution_enabled: real_pnl, real_applied = self._real_close_pair(ca, cb, reason, sim_pnl) use_real = self.real_truth and real_applied pnl = real_pnl if use_real else sim_pnl self.capital = max(self.capital + pnl, 0.0) is_win = pnl > 0 self.total_trades += 1 self.total_wins += is_win acc = self.total_wins / self.total_trades * 100 if self.total_trades else 0 data = {"reason": reason, "exit_a": round(ca, 4), "exit_b": round(cb, 4), "z": round(z, 3), "gross_ret": round(gross * 100, 3), "fee": round(fee * 100, 3), "net_return": round(net * 100, 3), "pnl": round(pnl, 2), "capital": round(self.capital, 2), "bars_held": self.bars_held, "win": bool(is_win), "total_trades": self.total_trades, "accuracy": round(acc, 1)} if self.real_truth: data["pnl_source"] = "real" if use_real else "sim_fallback" data["sim_pnl"] = round(sim_pnl, 2) if real_pnl is not None: data["real_pnl"] = round(real_pnl, 4) self._log("CLOSE", data); self._notify("CLOSED", data) self.in_position = False self.direction = 0 self.entry_a = self.entry_b = self.entry_z = 0.0 self.bars_held = 0 def tick(self, df_a: pd.DataFrame, df_b: pd.DataFrame): """Chiamato ad ogni poll con gli OHLCV aggiornati delle due gambe.""" if df_a is None or df_b is None or df_a.empty or df_b.empty: return # merge OHLC quando disponibile (serve a rilevare le candele flat per il flat-skip); # se le colonne OHLC mancano, flat resta False -> comportamento close-only invariato. ohlc = ["open", "high", "low", "close"] keep_a = ["timestamp"] + [c for c in ohlc if c in df_a.columns] keep_b = ["timestamp"] + [c for c in ohlc if c in df_b.columns] m = df_a[keep_a].merge(df_b[keep_b], on="timestamp", how="inner", suffixes=("_a", "_b")).sort_values("timestamp").reset_index(drop=True) # Scarta la barra IN FORMAZIONE: entry ED exit valutati SOLO sul close di # barra COMPLETA, come il backtest (pairs_research: close settled) — # lezione EXIT-16. Detection condivisa: src.live.bars. from src.live.bars import last_bar_is_forming if last_bar_is_forming(m["timestamp"].values): m = m.iloc[:-1] if len(m) < self.n + 2: return ca, cb = m["close_a"].values, m["close_b"].values z, dr = self._zscore(ca, cb) i = len(m) - 1 cur_ts = int(m["timestamp"].iloc[i]) zi = z[i] if np.isnan(zi): self._save_state(); return # flat della barra corrente (entrambe le gambe): O=H=L=C in una delle due flat_i = False if self.flat_skip and {"open_a", "high_a", "low_a"}.issubset(m.columns) \ and {"open_b", "high_b", "low_b"}.issubset(m.columns): fa = (m["open_a"].iloc[i] == m["high_a"].iloc[i] == m["low_a"].iloc[i] == ca[i]) fb = (m["open_b"].iloc[i] == m["high_b"].iloc[i] == m["low_b"].iloc[i] == cb[i]) flat_i = bool(fa or fb) if self.in_position: if cur_ts > self.last_bar_ts: self.bars_held += 1 self.last_bar_ts = cur_ts # arma l'uscita: |z|<=z_exit (rientro) o time-limit; poi esegui alla 1a barra pulita if not self.exit_ready and (abs(zi) <= self.z_exit or self.bars_held >= self.max_bars): self.exit_ready = True if self.exit_ready and not flat_i: reason = "mean_revert" if abs(zi) <= self.z_exit else "time_limit" self._close(float(ca[i]), float(cb[i]), float(zi), reason) self._save_state() return # cerca ingresso (no look-ahead: z[i] usa solo dati <= i); mai su barra stale if dr[i] <= self.jump_max and not flat_i: if zi <= -self.z_in: self._open(1, float(ca[i]), float(cb[i]), float(zi)); self.last_bar_ts = cur_ts elif zi >= self.z_in: self._open(-1, float(ca[i]), float(cb[i]), float(zi)); self.last_bar_ts = cur_ts self._save_state() @property def status_summary(self) -> str: acc = self.total_wins / self.total_trades * 100 if self.total_trades else 0 pos = ("LONG " + self.asset_a if self.direction == 1 else "SHORT " + self.asset_a if self.direction == -1 else "FLAT") return (f"{self.worker_id}: €{self.capital:.0f} | {self.total_trades}t {acc:.0f}% | {pos}")