Make risk guard symbol aware

2026-06-24 05:30:12 +03:00
parent 4112a17bc5
commit a6c94b1555
4 changed files with 168 additions and 12 deletions
@@ -114,30 +114,39 @@ def risk_guard_snapshot(
            "position_size_multiplier": 1.0,
            "reasons": [],
        }
+    active_trades = _active_universe_trades(settings, closed_trades)
    reasons: list[str] = []
-    consecutive_losses = _consecutive_losses(closed_trades)
+    degraded_reasons: list[str] = []
+    consecutive_losses = _consecutive_losses(active_trades)
    if consecutive_losses >= settings.risk_max_consecutive_losses:
-        reasons.append("consecutive_losses")
-    today_pnl = _today_pnl(closed_trades)
+        degraded_reasons.append("consecutive_losses")
+    today_pnl = _today_pnl(active_trades)
    if today_pnl <= -abs(settings.max_daily_drawdown_usdt):
        reasons.append("daily_loss_limit")
    window = max(4, settings.risk_recent_trade_window)
-    recent_stats = _trade_stats(closed_trades[:window])
+    recent_stats = _trade_stats(active_trades[:window])
    if recent_stats["trades"] >= max(4, min(window, 8)):
        if recent_stats["profit_factor"] < settings.risk_min_recent_profit_factor:
-            reasons.append("recent_profit_factor_below_min")
+            degraded_reasons.append("recent_profit_factor_below_min")
        if recent_stats["avg_net_percent"] <= 0:
-            reasons.append("recent_expectancy_non_positive")
+            degraded_reasons.append("recent_expectancy_non_positive")
    latest_drawdown = float((latest_equity or {}).get("drawdown", 0.0) or 0.0)
    if latest_drawdown >= abs(settings.max_daily_drawdown_usdt):
        reasons.append("equity_drawdown_limit")
-    block = bool({"consecutive_losses", "daily_loss_limit", "equity_drawdown_limit"} & set(reasons))
-    multiplier = 0.0 if block else (settings.risk_reduce_multiplier if reasons else 1.0)
+    symbol_stats = _symbol_guard_stats(settings, active_trades)
+    blocked_symbols = sorted(row["symbol"] for row in symbol_stats if row["block_new_entries"])
+    block = bool(reasons)
+    all_reasons = reasons + degraded_reasons
+    multiplier = 0.0 if block else (settings.risk_reduce_multiplier if degraded_reasons else 1.0)
    return {
        "enabled": True,
        "block_new_entries": block,
        "position_size_multiplier": round(max(0.0, min(1.0, multiplier)), 4),
-        "reasons": reasons,
+        "reasons": all_reasons,
+        "global_reasons": reasons,
+        "degraded_reasons": degraded_reasons,
+        "blocked_symbols": blocked_symbols,
+        "symbols": symbol_stats,
        "consecutive_losses": consecutive_losses,
        "today_pnl": round(today_pnl, 6),
        "recent": recent_stats,
@@ -183,6 +192,41 @@ def _group_stats(trades: list[dict[str, Any]], key_fn) -> list[dict[str, Any]]:
    return sorted(rows, key=lambda row: (row["net_pnl"], row["trades"]), reverse=True)


+def _active_universe_trades(settings: Settings, trades: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    symbols = {symbol.upper() for symbol in settings.symbols}
+    if not symbols:
+        return trades
+    return [trade for trade in trades if str(trade.get("symbol", "")).upper() in symbols]
+
+
+def _symbol_guard_stats(settings: Settings, trades: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    expectancy_min_samples = max(6, min(settings.risk_recent_trade_window, 10))
+    loss_streak_min_samples = max(3, settings.risk_max_consecutive_losses)
+    rows: list[dict[str, Any]] = []
+    for symbol in settings.symbols:
+        symbol_trades = [trade for trade in trades if str(trade.get("symbol", "")).upper() == symbol.upper()]
+        recent = symbol_trades[: settings.risk_recent_trade_window]
+        stats = _trade_stats(recent)
+        losses = _consecutive_losses(recent)
+        reasons: list[str] = []
+        if stats["trades"] >= expectancy_min_samples:
+            if stats["profit_factor"] < settings.risk_min_recent_profit_factor and stats["avg_net_percent"] <= 0:
+                reasons.append("symbol_expectancy_negative")
+        if stats["trades"] >= loss_streak_min_samples:
+            if losses >= settings.risk_max_consecutive_losses:
+                reasons.append("symbol_consecutive_losses")
+        rows.append(
+            {
+                "symbol": symbol.upper(),
+                "block_new_entries": bool(reasons),
+                "reasons": reasons,
+                "consecutive_losses": losses,
+                **stats,
+            }
+        )
+    return rows
+
+
 def _trade_summary(trade: dict[str, Any]) -> dict[str, Any]:
    diagnostics = trade.get("entry_diagnostics") if isinstance(trade.get("entry_diagnostics"), dict) else {}
    forecast = diagnostics.get("forecast") if isinstance(diagnostics.get("forecast"), dict) else {}