trader-mcp/strategies/trend_follower.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 = "Trend Follower"
    STRATEGY_PROFILE = {
        "expects": {
            "trend": "strong",
            "volatility": "moderate",
            "event_risk": "low",
            "liquidity": "normal",
        },
        "avoids": {
            "trend": "range",
            "volatility": "chaotic",
            "event_risk": "high",
            "liquidity": "thin",
        },
        "risk_profile": "growth",
        "capabilities": ["directional_continuation", "momentum_following", "inventory_accumulation"],
        "role": "primary",
        "inventory_behavior": "accumulative_long",
        "requires_rebalance_before_start": False,
        "requires_rebalance_before_stop": False,
        "safe_when_unbalanced": True,
        "can_run_with": ["exposure_protector"],
    }
    TICK_MINUTES = 0.5
    CONFIG_SCHEMA = {
        "trend_timeframe": {"type": "string", "default": "1h"},
        "trend_strength_min": {"type": "float", "default": 0.65, "min": 0.0, "max": 1.0},
        "entry_offset_pct": {"type": "float", "default": 0.003, "min": 0.0, "max": 1.0},
        "exit_offset_pct": {"type": "float", "default": 0.002, "min": 0.0, "max": 1.0},
        "order_size": {"type": "float", "default": 0.0, "min": 0.0},
        "max_order_size": {"type": "float", "default": 0.0, "min": 0.0},
        "fee_rate": {"type": "float", "default": 0.0025, "min": 0.0, "max": 0.05},
        "cooldown_ticks": {"type": "int", "default": 2, "min": 0, "max": 1000},
        "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": []},
        "last_signal": {"type": "string", "default": "neutral"},
        "last_strength": {"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},
        "base_available": {"type": "float", "default": 0.0},
        "counter_available": {"type": "float", "default": 0.0},
    }

    def init(self):
        return {
            "last_price": 0.0,
            "last_action": "idle",
            "last_error": "",
            "debug_log": ["init trend follower"],
            "last_signal": "neutral",
            "last_strength": 0.0,
            "cooldown_remaining": 0,
            "last_order_at": 0.0,
            "last_order_price": 0.0,
            "base_available": 0.0,
            "counter_available": 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("trend", 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 _price(self) -> float:
        payload = self.context.get_price(self._base_symbol())
        return float(payload.get("price") or 0.0)

    def _live_fee_rate(self) -> float:
        try:
            payload = self.context.get_fee_rates(self._market_symbol())
            return float(payload.get("maker") or payload.get("taker") or 0.0)
        except Exception as exc:
            self._log(f"fee lookup failed: {exc}")
            return float(self.config.get("fee_rate", 0.0025) or 0.0)

    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 _inventory_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._inventory_ratio(price if price > 0 else 1.0)
        last_error = str(self.state.get("last_error") or "")
        strength = float(self.state.get("last_strength") or 0.0)
        signal = str(self.state.get("last_signal") or "neutral")
        if ratio >= 0.88:
            pressure = "base_heavy"
        elif ratio <= 0.12:
            pressure = "quote_heavy"
        elif ratio >= 0.68:
            pressure = "base_biased"
        elif ratio <= 0.32:
            pressure = "quote_biased"
        else:
            pressure = "balanced"
        return {
            "health": "degraded" if last_error else "healthy",
            "degraded": bool(last_error),
            "inventory_pressure": pressure,
            "capacity_available": strength >= float(self.config.get("trend_strength_min", 0.65) or 0.65),
            "switch_readiness": "ready_to_yield_to_grid" if pressure == "balanced" and strength < float(self.config.get("trend_strength_min", 0.65) or 0.65) else "prefer_hold",
            "last_reason": last_error or f"signal={signal}, strength={strength:.3f}, base_ratio={ratio:.3f}",
            "desired_companion": "exposure_protector" if pressure != "balanced" else None,
        }

    def _trend_snapshot(self) -> dict:
        tf = str(self.config.get("trend_timeframe", "1h") or "1h")
        try:
            return self.context.get_regime(self._base_symbol(), tf)
        except Exception as exc:
            self._log(f"trend lookup failed: {exc}")
            return {"error": str(exc)}

    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()

        strength_map = {"cautious": 0.8, "normal": 0.65, "assertive": 0.5}
        entry_map = {"cautious": 0.002, "normal": 0.003, "assertive": 0.005}
        exit_map = {"cautious": 0.0015, "normal": 0.002, "assertive": 0.003}
        cooldown_map = {"cautious": 4, "normal": 2, "assertive": 1}
        size_map = {"cautious": 0.5, "normal": 1.0, "assertive": 1.5}

        if priority in {"low", "background"}:
            risk = "cautious"
        elif priority in {"high", "urgent"}:
            risk = "assertive"

        self.config["trend_strength_min"] = float(self.config.get("trend_strength_min") or strength_map.get(risk, 0.65))
        self.config["entry_offset_pct"] = float(self.config.get("entry_offset_pct") or entry_map.get(risk, 0.003))
        self.config["exit_offset_pct"] = float(self.config.get("exit_offset_pct") or exit_map.get(risk, 0.002))
        self.config["cooldown_ticks"] = int(self.config.get("cooldown_ticks") or cooldown_map.get(risk, 2))
        self.config["order_size"] = float(self.config.get("order_size") or size_map.get(risk, 1.0))
        self.state["policy_derived"] = {
            "trend_strength_min": self.config["trend_strength_min"],
            "entry_offset_pct": self.config["entry_offset_pct"],
            "exit_offset_pct": self.config["exit_offset_pct"],
            "cooldown_ticks": self.config["cooldown_ticks"],
            "order_size": self.config["order_size"],
        }
        return policy

    def _trend_strength(self) -> tuple[str, float]:
        regime = self._trend_snapshot()
        trend = regime.get("trend") or {}
        momentum = regime.get("momentum") or {}
        direction = str(trend.get("state") or trend.get("direction") or "unknown")
        strength = self._coerce_strength(trend.get("strength"))
        if strength is None:
            strength = self._derive_strength_from_regime(direction=direction, trend=trend, momentum=momentum, regime=regime)
        return direction, strength

    def _coerce_strength(self, value) -> float | None:
        try:
            if value is None:
                return None
            return max(0.0, min(1.0, float(value)))
        except Exception:
            return None

    def _derive_strength_from_regime(self, *, direction: str, trend: dict, momentum: dict, regime: dict) -> float:
        direction = str(direction or "unknown").lower()
        score = 0.0

        if direction in {"bull", "up", "long"}:
            score += 0.45
        elif direction in {"bear", "down", "short"}:
            score += 0.45
        else:
            return 0.0

        momentum_state = str(momentum.get("state") or "").lower()
        if direction in {"bull", "up", "long"} and momentum_state == "bull":
            score += 0.2
        elif direction in {"bear", "down", "short"} and momentum_state == "bear":
            score += 0.2

        try:
            rsi = float(momentum.get("rsi") or 0.0)
        except Exception:
            rsi = 0.0
        if direction in {"bull", "up", "long"}:
            if rsi >= 60:
                score += 0.2
            elif rsi >= 52:
                score += 0.1
        else:
            if 0 < rsi <= 40:
                score += 0.2
            elif 0 < rsi <= 48:
                score += 0.1

        try:
            macd_hist = float(momentum.get("macd_histogram") or 0.0)
        except Exception:
            macd_hist = 0.0
        if direction in {"bull", "up", "long"} and macd_hist > 0:
            score += 0.1
        elif direction in {"bear", "down", "short"} and macd_hist < 0:
            score += 0.1

        try:
            ema_fast = float(trend.get("ema_fast") or 0.0)
            ema_slow = float(trend.get("ema_slow") or 0.0)
        except Exception:
            ema_fast = 0.0
            ema_slow = 0.0
        if direction in {"bull", "up", "long"} and ema_fast > ema_slow > 0:
            score += 0.05
        elif direction in {"bear", "down", "short"} and 0 < ema_fast < ema_slow:
            score += 0.05

        return max(0.0, min(1.0, round(score, 4)))

    def _suggest_amount(self, price: float) -> float:
        min_notional = float(self.context.minimum_order_value or 0.0)
        max_order = float(self.config.get("max_order_size", 0.0) or 0.0)
        if hasattr(self.context, "suggest_order_amount"):
            fee_rate = self._live_fee_rate()
            return float(self.context.suggest_order_amount(
                side="buy" if str(self.state.get("last_signal") or "").lower() in {"bull", "up", "long"} else "sell",
                price=price,
                levels=1,
                min_notional=min_notional,
                fee_rate=fee_rate,
                max_notional_per_order=(max_order * price) if max_order > 0 else 0.0,
                order_size=float(self.config.get("order_size", 0.0) or 0.0),
            ) or 0.0)
        amount = float(self.config.get("order_size", 0.0) or 0.0)
        if max_order > 0:
            amount = min(amount, max_order)
        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()
        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}

        direction, strength = self._trend_strength()
        self.state["last_signal"] = direction
        self.state["last_strength"] = strength

        if strength < float(self.config.get("trend_strength_min", 0.65) or 0.65):
            self.state["last_action"] = "hold"
            return {"action": "hold", "price": price, "reason": "trend too weak", "strength": strength}

        amount = self._suggest_amount(price)
        if amount <= 0:
            self.state["last_action"] = "hold"
            return {"action": "hold", "price": price, "reason": "no usable size"}

        side = "buy" if direction in {"bull", "up", "long"} else "sell"
        offset = float(self.config.get("entry_offset_pct", 0.003) or 0.0)
        if side == "buy":
            order_price = round(price * (1 + offset), 8)
        else:
            order_price = round(price * (1 - offset), 8)

        try:
            if self.config.get("debug_orders", True):
                self._log(f"{side} trend amount={amount:.6g} price={order_price} strength={strength:.3f}")
            result = self.context.place_order(
                side=side,
                order_type="limit",
                amount=amount,
                price=order_price,
                market=self._market_symbol(),
            )
            self.state["cooldown_remaining"] = int(self.config.get("cooldown_ticks", 2) or 2)
            self.state["last_order_at"] = datetime.now(timezone.utc).timestamp()
            self.state["last_order_price"] = order_price
            self.state["last_action"] = f"{side}_trend"
            return {"action": side, "price": order_price, "amount": amount, "result": result, "strength": strength}
        except Exception as exc:
            self.state["last_error"] = str(exc)
            self._log(f"trend order 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": snapshot.get("position", {}),
            "state": {
                "last_price": self.state.get("last_price", 0.0),
                "last_action": self.state.get("last_action", "idle"),
                "last_signal": self.state.get("last_signal", "neutral"),
                "last_strength": self.state.get("last_strength", 0.0),
                "cooldown_remaining": self.state.get("cooldown_remaining", 0),
                "base_available": self.state.get("base_available", 0.0),
                "counter_available": self.state.get("counter_available", 0.0),
            },
            "assessment": {
                "confidence": None,
                "uncertainty": None,
                "reason": "trend capture",
                "warnings": [],
                "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": "signal", "value": self.state.get("last_signal", "neutral")},
                {"type": "metric", "label": "strength", "value": round(float(self.state.get("last_strength") or 0.0), 4)},
                {"type": "metric", "label": "state", "value": self.state.get("last_action", "idle")},
                {"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 []},
            ]
        }