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fix(v0.2.8): trajectory override now recovery-based (critical fix)

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Trade #162698852 predicted +$4.54 recovery (80% conf) but override failed.
Bug: checked pred_1m > 0 (absolute) instead of recovery amount.

Fix:
- Recovery-based: recovery_amount = pred_1m - current_profit
- Override if recovery >$3 OR near-breakeven (pred >-$2)
- Relaxed accel threshold: 0.01 → 0.005
- User requirement: "profit kecil dengan interval lama OK" ✅

Impact: Same scenario now triggers override, holds 5-15 min for recovery.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
buckybonez
2026-02-11 23:37:14 +07:00
co-authored by Claude Sonnet 4.5
parent 46000cd122
commit 7044c42b44
3 changed files with 88 additions and 10 deletions
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src/smart_risk_manager.py
+25 -9
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@@ -1309,15 +1309,17 @@ class SmartRiskManager:
pred_1m = predictions.get('pred_1m', 0)
logger.info(f"[TRAJ-OUT] pred_1m=${pred_1m:.2f} | conf={predictions['confidence']:.0%}")
# v0.2.6f: Hybrid trajectory hold logic
# v0.2.7f: Hybrid trajectory hold logic (recovery-based)
# - Ever-profitable: always allow hold (existing behavior)
# - Never-profitable + Golden + strong signal: allow hold (NEW)
# - Never-profitable + Golden + recovery signal: allow hold (NEW)
# - Never-profitable + normal session: skip hold (existing behavior)
pred_1m = predictions.get('pred_1m', 0)
recovery_amount = pred_1m - current_profit
can_hold_never_prof = (
is_golden
and predictions.get('pred_1m', 0) > 0
and (recovery_amount > 3.0 or pred_1m > -2.0) # Recovery or near-breakeven
and predictions.get('confidence', 0) > 0.75
and _accel > 0.01 # positive acceleration
and _accel > 0.005 # Relaxed threshold
)
if should_hold and (guard.ever_profitable or can_hold_never_prof):
@@ -1575,18 +1577,32 @@ class SmartRiskManager:
if (is_golden and not guard.ever_profitable
and current_profit < -5.0 and trade_age_seconds >= 60):
# v0.2.6f: Check if trajectory predicts strong recovery
# v0.2.7f: Check if trajectory predicts RECOVERY (not just profit)
# Key insight: recovery = pred_1m - current_profit
# Example: current=-$5.81, pred=-$1.27 → recovery=+$4.54 (GOOD!)
strong_recovery_signal = False
if self.trajectory_predictor and predictions:
pred_1m = predictions.get('pred_1m', current_profit)
pred_conf = predictions.get('pred_1m_conf', 0)
# Strong recovery: pred > 0, conf > 75%, positive acceleration
if pred_1m > 0 and pred_conf > 0.75 and _accel > 0.01:
# Calculate recovery amount (how much profit will improve)
recovery_amount = pred_1m - current_profit
# Recovery conditions (ANY of these = override):
# 1. Significant recovery: predict >$3 improvement
# 2. Near-breakeven: predict loss <$2 (small loss acceptable)
significant_recovery = recovery_amount > 3.0
near_breakeven = pred_1m > -2.0
strong_confidence = pred_conf > 0.75
positive_momentum = _accel > 0.005 # Relaxed from 0.01
if (significant_recovery or near_breakeven) and strong_confidence and positive_momentum:
strong_recovery_signal = True
recovery_type = "significant recovery" if significant_recovery else "near-breakeven"
logger.info(
f"[GOLDEN EMERGENCY OVERRIDE] Trajectory predicts recovery: "
f"pred_1m=${pred_1m:.2f} conf={pred_conf:.0%} accel={_accel:.4f} — holding"
f"[GOLDEN EMERGENCY OVERRIDE] Trajectory predicts {recovery_type}: "
f"current=${current_profit:.2f} → pred=${pred_1m:.2f} "
f"(recovery=${recovery_amount:+.2f}, conf={pred_conf:.0%}, accel={_accel:.4f}) — holding"
)
if not strong_recovery_signal: