""" exit_v2.py -- [2026-09-29] Exits the user asked for on 9/29 ("add the smooth exit and add the breakeven rule stop trail"), ported from trade1/exit_rules.py modes "step_r" and "smooth" (tested there on fixed entries: 21 days smooth break 0.6 +$1,213, 0.8 +$970 vs exit B +$407; step_r + reversal breakeven -$547 vs hold -$1,275 on the first entries). One managed stop + one trend check, evaluated every poll: STOP TRAIL (trail: true) start the entry's stop, at least min_stop_pct below the buy price; R = buy - start steps every time price has risen another R above the buy, the stop rises by R (after the first step it sits at the buy price = BREAKEVEN) trail from breakeven on, the stop also trails atr_mult x the 1-min ATR (Wilder, atr_period bars) under the high since the buy; it never moves down reversal breakeven (reversal_breakeven_atr > 0): at the first 1-min bar after the buy that closes >= 1 ATR under the high since the buy, if that high was < reversal_breakeven_atr x ATR above the buy, the stop moves to the buy price sells on a touch of the stop SMOOTH TREND (smooth: true) smoothness = R^2 of the last smooth_bars finished 1-min closes, signed by the slope; armed once it reaches smooth_arm after the buy; armed -> sell when it drops under smooth_break (the steady climb broke) replace_j: true -> these are the ONLY exits besides the 15:55 sell-all (J's giveback, stall, imbalance, weakening and hard-stop layers are skipped); false -> they run first, then J's layers as before. """ from dataclasses import dataclass, field from datetime import datetime DEFAULTS = { "enabled": False, "replace_j": True, "trail": True, "min_stop_pct": 1.0, "atr_mult": 2.0, "atr_period": 14, "reversal_breakeven_atr": 2.0, "smooth": True, "smooth_bars": 30, "smooth_arm": 0.8, "smooth_break": 0.6, } @dataclass class ExitV2Decision: should_exit: bool = False state: str = "HOLD" reason: str = "" metrics: dict = field(default_factory=dict) def _atr_1m(done, period): atr = None for prev, b in zip(done, done[1:]): tr = max(b["h"] - b["l"], abs(b["h"] - prev["c"]), abs(b["l"] - prev["c"])) atr = tr if atr is None else atr + (tr - atr) / period return atr def _smoothness(closes): n = len(closes) if n < 5: return None xm, ym = (n - 1) / 2, sum(closes) / n sxx = sum((k - xm) ** 2 for k in range(n)) slope = sum((k - xm) * (y - ym) for k, y in enumerate(closes)) / sxx sst = sum((y - ym) ** 2 for y in closes) if sst == 0: return 0.0 ssr = sum((y - (ym + slope * (k - xm))) ** 2 for k, y in enumerate(closes)) return (1 - ssr / sst) * (1 if slope > 0 else -1) def evaluate(bars, position, state, cfg=None) -> ExitV2Decision: """bars: today's 1-min bars incl. the forming one; position: {"entry_price", "stop_price", "entry_time" (iso)}; state: per-position dict kept by the caller.""" c = {**DEFAULTS, **(cfg or {})} price = bars[-1]["c"] entry = position["entry_price"] done = bars[:-1] t_buy = datetime.fromisoformat(position["entry_time"]).replace(second=0, microsecond=0) if "stop" not in state: stop0 = min(position["stop_price"], entry * (1 - c["min_stop_pct"] / 100.0)) state.update(stop0=stop0, stop=stop0, steps=0, high=entry, how="entry stop", armed=False, peak_r2=None, reversal_seen=False, bar_high=entry) state["high"] = max(state["high"], price) R = entry - state["stop0"] atr = _atr_1m(done[-(int(c["atr_period"]) * 3):], int(c["atr_period"])) if len(done) >= 2 else None if c["trail"]: if R > 0: steps = int((state["high"] - entry) // R) if steps > state["steps"]: state["steps"] = steps new = state["stop0"] + steps * R if new > state["stop"]: state["stop"], state["how"] = new, ("breakeven (+1R)" if steps == 1 else f"step +{steps - 1}R") k_rev = c.get("reversal_breakeven_atr") or 0 if k_rev and atr and not state["reversal_seen"] and done and done[-1]["t"] >= t_buy: last = done[-1] state["bar_high"] = max(state["bar_high"], last["h"]) if state["bar_high"] > entry and last["c"] <= state["bar_high"] - atr: state["reversal_seen"] = True run = state["bar_high"] - entry if run < k_rev * atr and entry > state["stop"]: state["stop"], state["how"] = entry, f"first reversal after only {run / atr:.1f} ATR -> buy price" if state["steps"] >= 1 and atr: trail = state["high"] - c["atr_mult"] * atr if trail > state["stop"]: state["stop"], state["how"] = trail, f"trail {c['atr_mult']}x1m-ATR ({atr:.3f})" r2 = None if c["smooth"]: n = int(c["smooth_bars"]) if len(done) >= n: r2 = _smoothness([b["c"] for b in done[-n:]]) if r2 is not None and done and done[-1]["t"] >= t_buy and r2 >= c["smooth_arm"]: state["armed"] = True if r2 is not None: state["peak_r2"] = r2 if state["peak_r2"] is None else max(state["peak_r2"], r2) stop = state["stop"] m = {"stop": round(stop, 4), "stop_from": state["how"], "R": round(R, 4), "steps": state["steps"], "atr_1m": round(atr, 4) if atr else None, "high_since_entry": state["high"], "smoothness": round(r2, 3) if r2 is not None else None, "armed": state["armed"], "peak_smoothness": round(state["peak_r2"], 3) if state["peak_r2"] is not None else None} if price <= stop: return ExitV2Decision(True, "STOP", f"exit_v2 stop: price {price:.2f} <= {stop:.2f} ({state['how']})", m) if c["smooth"] and state["armed"] and r2 is not None and r2 < c["smooth_break"]: return ExitV2Decision(True, "SMOOTH_BREAK", f"exit_v2 smooth break: smoothness {r2:.2f} < {c['smooth_break']} (trend broke)", m) return ExitV2Decision(False, "HOLD", f"exit_v2 hold: stop {stop:.2f} ({state['how']})" + (f", smoothness {r2:.2f}{' armed' if state['armed'] else ''}" if r2 is not None else ""), m)