feat(live): worker con exit TP/SL/max_bars per MR01 + doc aggiornata

StrategyWorker ora supporta exit guidati dalla strategia via Signal.metadata
(take-profit alla media / stop-loss ad ATR / time-limit), con fallback al
vecchio hold_bars/stop -2% per strategie senza metadata. Usa fee_rt della
strategia (MR01 = 0.10% RT reale Deribit, non piu' 0.20% hardcoded).
Persistenza di tp/sl/max_bars in status.json per resume.

Re-validato col worker reale (replay finestre mobili 1h, fee 0.10%):
  BTC 1h MR01: +196% OOS, ETH 1h: +251% OOS (nov 2023->mag 2026) — coerente col backtest.

README + CLAUDE.md riscritti: squeeze = artefatto di look-ahead -> waste,
MR01 mean-reversion unica attiva, metodologia anti-look-ahead e fee reali 0.10% RT.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Adriano Dal Pastro
2026-05-28 20:46:35 +00:00
parent 9879b46688
commit 48435f6858
4 changed files with 218 additions and 94 deletions
+41 -2
View File
@@ -55,6 +55,13 @@ class StrategyWorker:
self.started_at = datetime.now(timezone.utc).isoformat()
self.last_bar_ts: int = 0
# Exit guidati dalla strategia via Signal.metadata (0 = usa hold_bars/stop legacy)
self.tp: float = 0.0
self.sl: float = 0.0
self.max_bars: int = 0
# Fee dalla strategia (MR01 = 0.001 realistico Deribit), fallback al default modulo
self.fee_rt: float = float(getattr(strategy, "fee_rt", FEE_RT))
self._load_state()
self._save_state()
@@ -78,6 +85,9 @@ class StrategyWorker:
self.total_wins = state.get("total_wins", 0)
self.started_at = state.get("started_at", self.started_at)
self.last_bar_ts = state.get("last_bar_ts", 0)
self.tp = state.get("tp", 0.0)
self.sl = state.get("sl", 0.0)
self.max_bars = state.get("max_bars", 0)
self._log("RESUME", {"capital": round(self.capital, 2),
"total_trades": self.total_trades,
@@ -95,6 +105,9 @@ class StrategyWorker:
"total_wins": self.total_wins,
"started_at": self.started_at,
"last_bar_ts": self.last_bar_ts,
"tp": self.tp,
"sl": self.sl,
"max_bars": self.max_bars,
"last_update": datetime.now(timezone.utc).isoformat(),
}
with open(self.status_path, "w") as f:
@@ -125,12 +138,19 @@ class StrategyWorker:
self.entry_time = datetime.now(timezone.utc).isoformat()
self.bars_held = 0
meta = signal.metadata or {}
self.tp = float(meta.get("tp", 0.0) or 0.0)
self.sl = float(meta.get("sl", 0.0) or 0.0)
self.max_bars = int(meta.get("max_bars", 0) or 0)
trade_data = {
"direction": "long" if signal.direction == 1 else "short",
"price": round(current_price, 2),
"size": round(size, 6),
"notional": round(notional, 2),
"capital": round(self.capital, 2),
"tp": round(self.tp, 2) if self.tp else None,
"sl": round(self.sl, 2) if self.sl else None,
}
self._log("OPEN", trade_data)
self._notify("OPENED", trade_data)
@@ -141,7 +161,7 @@ class StrategyWorker:
price_change = (current_price - self.entry_price) / self.entry_price
trade_return = price_change * self.direction
net = trade_return * self.leverage - FEE_RT * self.leverage
net = trade_return * self.leverage - self.fee_rt * self.leverage
pnl = self.capital * self.position_size * net
is_win = trade_return > 0
@@ -174,6 +194,9 @@ class StrategyWorker:
self.entry_price = 0
self.entry_time = ""
self.bars_held = 0
self.tp = 0.0
self.sl = 0.0
self.max_bars = 0
def tick(self, df: pd.DataFrame, df_1h: pd.DataFrame | None = None):
"""Chiamato ad ogni poll con DataFrame OHLCV aggiornato.
@@ -195,7 +218,23 @@ class StrategyWorker:
self.bars_held += 1
self.last_bar_ts = current_ts
if self.bars_held >= self.hold_bars:
if self.tp and self.sl:
# Exit guidati dalla strategia: SL (conservativo, prima), poi TP, poi time-limit
if self.direction == 1:
if current_price <= self.sl:
self._close_position(current_price, "stop_loss")
elif current_price >= self.tp:
self._close_position(current_price, "take_profit")
elif self.max_bars and self.bars_held >= self.max_bars:
self._close_position(current_price, "time_limit")
else:
if current_price >= self.sl:
self._close_position(current_price, "stop_loss")
elif current_price <= self.tp:
self._close_position(current_price, "take_profit")
elif self.max_bars and self.bars_held >= self.max_bars:
self._close_position(current_price, "time_limit")
elif self.bars_held >= self.hold_bars:
self._close_position(current_price, "hold_limit")
else:
pnl_pct = (current_price - self.entry_price) / self.entry_price * self.direction