trader-mcp/strategies/exposure_protector.py

from __future__ import annotations

from datetime import datetime, timezone

from src.trader_mcp.strategy_sdk import Strategy
from src.trader_mcp.logging_utils import log_event


class Strategy(Strategy):
    LABEL = "Exposure Protector"
    STRATEGY_PROFILE = {
        "expects": {
            "trend": "mixed",
            "volatility": "moderate",
            "event_risk": "low",
            "liquidity": "normal",
        },
        "avoids": {
            "volatility": "chaotic",
            "event_risk": "high",
            "liquidity": "thin",
        },
        "risk_profile": "defensive",
        "capabilities": ["inventory_rebalancing", "exposure_trim", "companion_defense"],
        "role": "defensive",
        "inventory_behavior": "rebalancing",
        "requires_rebalance_before_start": False,
        "requires_rebalance_before_stop": False,
        "safe_when_unbalanced": True,
        "can_run_with": ["grid_trader", "trend_follower"],
    }
    TICK_MINUTES = 0.2
    CONFIG_SCHEMA = {
        "trail_distance_pct": {"type": "float", "default": 0.03, "min": 0.0, "max": 1.0},
        "rebalance_target_ratio": {"type": "float", "default": 0.5, "min": 0.0, "max": 1.0},
        "rebalance_step_ratio": {"type": "float", "default": 0.15, "min": 0.0, "max": 1.0},
        "min_order_notional_quote": {"type": "float", "default": 0.0, "min": 0.0},
        "max_order_notional_quote": {"type": "float", "default": 0.0, "min": 0.0},
        "order_spacing_ticks": {"type": "int", "default": 1, "min": 0, "max": 1000},
        "cooldown_ticks": {"type": "int", "default": 2, "min": 0, "max": 1000},
        "min_rebalance_seconds": {"type": "int", "default": 180, "min": 0, "max": 86400},
        "min_price_move_pct": {"type": "float", "default": 0.005, "min": 0.0, "max": 1.0},
        "balance_tolerance": {"type": "float", "default": 0.05, "min": 0.0, "max": 1.0},
        "debug_orders": {"type": "bool", "default": True},
    }
    STATE_SCHEMA = {
        "last_price": {"type": "float", "default": 0.0},
        "last_action": {"type": "string", "default": "idle"},
        "last_error": {"type": "string", "default": ""},
        "debug_log": {"type": "list", "default": []},
        "regimes": {"type": "dict", "default": {}},
        "regimes_updated_at": {"type": "string", "default": ""},
        "base_available": {"type": "float", "default": 0.0},
        "counter_available": {"type": "float", "default": 0.0},
        "trailing_anchor": {"type": "float", "default": 0.0},
        "cooldown_remaining": {"type": "int", "default": 0},
        "last_order_at": {"type": "float", "default": 0.0},
        "last_order_price": {"type": "float", "default": 0.0},
    }

    def init(self):
        return {
            "last_price": 0.0,
            "last_action": "idle",
            "last_error": "",
            "debug_log": ["init exposure protector"],
            "regimes": {},
            "regimes_updated_at": "",
            "base_available": 0.0,
            "counter_available": 0.0,
            "trailing_anchor": 0.0,
            "cooldown_remaining": 0,
            "last_order_at": 0.0,
            "last_order_price": 0.0,
        }

    def _log(self, message: str) -> None:
        state = getattr(self, "state", {}) or {}
        log = list(state.get("debug_log") or [])
        log.append(message)
        state["debug_log"] = log[-12:]
        self.state = state
        log_event("stoploss", message)

    def _base_symbol(self) -> str:
        return (self.context.base_currency or self.context.market_symbol or "XRP").split("/")[0].upper()

    def _market_symbol(self) -> str:
        return self.context.market_symbol or f"{self._base_symbol().lower()}usd"

    def apply_policy(self):
        policy = super().apply_policy()
        risk = str(policy.get("risk_posture") or "normal").lower()
        priority = str(policy.get("priority") or "normal").lower()

        trail_map = {"cautious": 0.02, "normal": 0.03, "assertive": 0.04}
        step_map = {"cautious": 0.08, "normal": 0.15, "assertive": 0.25}
        wait_map = {"cautious": 420, "normal": 180, "assertive": 90}
        move_map = {"cautious": 0.01, "normal": 0.005, "assertive": 0.003}

        if priority in {"low", "background"}:
            trail = trail_map.get("cautious", 0.02)
            step = step_map.get("cautious", 0.08)
            wait = wait_map.get("cautious", 600)
            move = move_map.get("cautious", 0.02)
        elif priority in {"high", "urgent"}:
            trail = trail_map.get("assertive", 0.04)
            step = step_map.get("assertive", 0.25)
            wait = wait_map.get("assertive", 120)
            move = move_map.get("assertive", 0.005)
        else:
            trail = trail_map.get(risk, 0.03)
            step = step_map.get(risk, 0.15)
            wait = wait_map.get(risk, 300)
            move = move_map.get(risk, 0.01)

        self.config["trail_distance_pct"] = trail
        self.config["rebalance_step_ratio"] = step
        self.config["min_rebalance_seconds"] = wait
        self.config["min_price_move_pct"] = move
        self.state["policy_derived"] = {
            "trail_distance_pct": trail,
            "rebalance_step_ratio": step,
            "min_rebalance_seconds": wait,
            "min_price_move_pct": move,
        }
        return policy

    def _live_fee_rate(self) -> float:
        try:
            payload = self.context.get_fee_rates(self._market_symbol())
            return float(payload.get("maker") or 0.0)
        except Exception as exc:
            self._log(f"fee lookup failed: {exc}")
            return 0.0

    def _price(self) -> float:
        payload = self.context.get_price(self._base_symbol())
        return float(payload.get("price") or 0.0)

    def _refresh_regimes(self) -> None:
        try:
            self.state["regimes"] = self.context.get_strategy_snapshot().get("fit", {}) if hasattr(self.context, "get_strategy_snapshot") else {}
        except Exception:
            self.state["regimes"] = {}
        self.state["regimes_updated_at"] = datetime.now(timezone.utc).isoformat()

    def _refresh_balance_snapshot(self) -> None:
        try:
            info = self.context.get_account_info()
        except Exception as exc:
            self._log(f"balance refresh failed: {exc}")
            return
        balances = info.get("balances") if isinstance(info, dict) else []
        if not isinstance(balances, list):
            return
        base = self._base_symbol()
        quote = str(self.context.counter_currency or "USD").upper()
        for balance in balances:
            if not isinstance(balance, dict):
                continue
            asset = str(balance.get("asset_code") or "").upper()
            try:
                available = float(balance.get("available") if balance.get("available") is not None else balance.get("total") or 0.0)
            except Exception:
                continue
            if asset == base:
                self.state["base_available"] = available
            if asset == quote:
                self.state["counter_available"] = available

    def _account_value_ratio(self, price: float) -> float:
        base_value = float(self.state.get("base_available") or 0.0) * price
        counter_value = float(self.state.get("counter_available") or 0.0)
        total = base_value + counter_value
        if total <= 0:
            return 0.5
        return base_value / total

    def _supervision(self) -> dict:
        price = float(self.state.get("last_price") or 0.0)
        ratio = self._account_value_ratio(price if price > 0 else 1.0)
        target = float(self.config.get("rebalance_target_ratio", 0.5) or 0.5)
        tolerance = float(self.config.get("balance_tolerance", 0.05) or 0.05)
        drift = abs(ratio - target)
        last_error = str(self.state.get("last_error") or "")
        repair_progress = max(0.0, 1.0 - min(drift / max(tolerance, 0.35), 1.0))
        concerns = []
        if drift > tolerance:
            concerns.append(f"inventory drift {drift:.3f} still above tolerance {tolerance:.3f}")
        if drift >= 0.35:
            concerns.append("inventory imbalance is critical")
        if last_error:
            concerns.append(last_error)
        if drift >= 0.35:
            pressure = "critical"
        elif drift > tolerance:
            pressure = "elevated"
        else:
            pressure = "contained"
        return {
            "health": "degraded" if last_error else "healthy",
            "degraded": bool(last_error),
            "inventory_pressure": pressure,
            "capacity_available": drift > tolerance,
            "rebalance_needed": drift > tolerance,
            "drift": round(drift, 6),
            "target_ratio": target,
            "repair_progress": round(repair_progress, 6),
            "concerns": concerns,
            "last_reason": last_error or f"base_ratio={ratio:.3f}, target={target:.3f}, drift={drift:.3f}",
        }

    def _desired_side(self, price: float) -> str:
        # If base dominates, sell some into strength, otherwise buy some back.
        ratio = self._account_value_ratio(price)
        target = float(self.config.get("rebalance_target_ratio", 0.5) or 0.5)
        step_ratio = float(self.config.get("rebalance_step_ratio", 0.15) or 0.0)
        tolerance = float(self.config.get("balance_tolerance", 0.05) or 0.0)
        hysteresis = max(tolerance, step_ratio * 0.5, 0.02)
        last_side = str(self.state.get("last_rebalance_side") or "").lower()

        if last_side == "sell":
            if ratio <= target - hysteresis:
                return "buy"
            if ratio >= target + hysteresis:
                return "sell"
            return ""

        if last_side == "buy":
            if ratio >= target + hysteresis:
                return "sell"
            if ratio <= target - hysteresis:
                return "buy"
            return ""

        if ratio > target + hysteresis:
            return "sell"
        if ratio < target - hysteresis:
            return "buy"
        return ""

    def _suggest_amount(self, side: str, price: float) -> float:
        fee_rate = self._live_fee_rate()
        step_ratio = float(self.config.get("rebalance_step_ratio", 0.15) or 0.0)
        target = float(self.config.get("rebalance_target_ratio", 0.5) or 0.5)
        min_order_quote = float(self.config.get("min_order_notional_quote") or self.config.get("min_order_size") or 0.0)
        max_order_quote = float(self.config.get("max_order_notional_quote") or self.config.get("max_order_size") or 0.0)
        balance_tolerance = float(self.config.get("balance_tolerance", 0.05) or 0.0)
        base_value = float(self.state.get("base_available") or 0.0) * price
        counter_value = float(self.state.get("counter_available") or 0.0)
        total = base_value + counter_value
        if total <= 0 or price <= 0:
            return 0.0
        current = base_value / total
        drift = abs(current - target)
        if drift <= balance_tolerance:
            return 0.0

        notional = total * min(drift, step_ratio)
        if side == "sell":
            amount = notional / (price * (1 + fee_rate))
            amount = min(amount, float(self.state.get("base_available") or 0.0))
        else:
            amount = notional / (price * (1 + fee_rate))
            amount = min(amount, float(self.state.get("counter_available") or 0.0) / price if price > 0 else 0.0)

        if min_order_quote > 0 and price > 0:
            amount = max(amount, min_order_quote / price)
        if max_order_quote > 0 and price > 0:
            amount = min(amount, max_order_quote / price)
        return max(amount, 0.0)

    def on_tick(self, tick):
        self.state["last_error"] = ""
        self._log(f"tick alive price={self.state.get('last_price') or 0.0}")
        self._refresh_balance_snapshot()
        self._refresh_regimes()
        price = self._price()
        self.state["last_price"] = price

        if int(self.state.get("cooldown_remaining") or 0) > 0:
            self.state["cooldown_remaining"] = int(self.state.get("cooldown_remaining") or 0) - 1
            self.state["last_action"] = "cooldown"
            return {"action": "cooldown", "price": price}

        now = datetime.now(timezone.utc).timestamp()
        last_order_at = float(self.state.get("last_order_at") or 0.0)
        min_rebalance_seconds = int(self.config.get("min_rebalance_seconds", 300) or 0)
        if last_order_at and min_rebalance_seconds > 0 and (now - last_order_at) < min_rebalance_seconds:
            self.state["last_action"] = "hold"
            return {"action": "hold", "price": price, "reason": "rebalance cooldown"}

        last_order_price = float(self.state.get("last_order_price") or 0.0)
        min_price_move_pct = float(self.config.get("min_price_move_pct", 0.01) or 0.0)
        if last_order_price > 0 and min_price_move_pct > 0:
            move_pct = abs(price - last_order_price) / last_order_price
            if move_pct < min_price_move_pct:
                self.state["last_action"] = "hold"
                return {"action": "hold", "price": price, "reason": "insufficient price move", "move_pct": move_pct}

        side = self._desired_side(price)
        if not side:
            self.state["last_action"] = "hold"
            return {"action": "hold", "price": price, "reason": "within rebalance hysteresis"}
        amount = self._suggest_amount(side, price)
        trail_distance = float(self.config.get("trail_distance_pct", 0.03) or 0.03)

        if amount <= 0:
            self.state["last_action"] = "hold"
            return {"action": "hold", "price": price}

        try:
            market = self._market_symbol()
            if side == "sell":
                self.state["trailing_anchor"] = max(float(self.state.get("trailing_anchor") or 0.0), price)
                order_price = round(price * (1 - trail_distance), 8)
            else:
                self.state["trailing_anchor"] = min(float(self.state.get("trailing_anchor") or price), price) if self.state.get("trailing_anchor") else price
                order_price = round(price * (1 + trail_distance), 8)

            if self.config.get("debug_orders", True):
                self._log(f"{side} rebalance amount={amount:.6g} price={order_price} ratio={self._account_value_ratio(price):.4f}")

            result = self.context.place_order(
                side=side,
                order_type="limit",
                amount=amount,
                price=order_price,
                market=market,
            )
            self.state["cooldown_remaining"] = int(self.config.get("cooldown_ticks", 2) or 2)
            self.state["last_order_at"] = now
            self.state["last_order_price"] = order_price
            self.state["last_rebalance_side"] = side
            self.state["last_action"] = f"{side}_rebalance"
            return {"action": side, "price": order_price, "amount": amount, "result": result}
        except Exception as exc:
            self.state["last_error"] = str(exc)
            self._log(f"rebalance failed: {exc}")
            self.state["last_action"] = "error"
            return {"action": "error", "price": price, "error": str(exc)}

    def report(self):
        snapshot = self.context.get_strategy_snapshot() if hasattr(self.context, "get_strategy_snapshot") else {}
        return {
            "identity": snapshot.get("identity", {}),
            "control": snapshot.get("control", {}),
            "fit": dict(getattr(self, "STRATEGY_PROFILE", {}) or {}),
            "position": {
                "balances": {
                    "base_available": self.state.get("base_available", 0.0),
                    "counter_available": self.state.get("counter_available", 0.0),
                },
                "open_orders": snapshot.get("orders", {}).get("open_orders", []),
                "exposure": "managed",
            },
            "state": {
                "last_price": self.state.get("last_price", 0.0),
                "last_action": self.state.get("last_action", "idle"),
                "trailing_anchor": self.state.get("trailing_anchor", 0.0),
                "cooldown_remaining": self.state.get("cooldown_remaining", 0),
                "regimes_updated_at": self.state.get("regimes_updated_at", ""),
            },
            "assessment": {
                "confidence": None,
                "uncertainty": None,
                "reason": "defensive exposure protection",
                "warnings": [w for w in (self._supervision().get("concerns") or []) if w],
                "policy": dict(self.config.get("policy") or {}),
            },
            "execution": snapshot.get("execution", {}),
            "supervision": self._supervision(),
        }

    def render(self):
        return {
            "widgets": [
                {"type": "metric", "label": "market", "value": self._market_symbol()},
                {"type": "metric", "label": "price", "value": round(float(self.state.get("last_price") or 0.0), 6)},
                {"type": "metric", "label": "state", "value": self.state.get("last_action", "idle")},
                {"type": "metric", "label": "base avail", "value": round(float(self.state.get("base_available") or 0.0), 8)},
                {"type": "metric", "label": "counter avail", "value": round(float(self.state.get("counter_available") or 0.0), 8)},
                {"type": "metric", "label": "ratio", "value": round(self._account_value_ratio(float(self.state.get("last_price") or 0.0) or 1.0), 4)},
                {"type": "metric", "label": "trailing anchor", "value": round(float(self.state.get("trailing_anchor") or 0.0), 6)},
                {"type": "metric", "label": "cooldown", "value": int(self.state.get("cooldown_remaining") or 0)},
                {"type": "text", "label": "error", "value": self.state.get("last_error", "") or "none"},
                {"type": "log", "label": "debug log", "lines": self.state.get("debug_log") or []},
            ]
        }