950 lines
35 KiB
Python
950 lines
35 KiB
Python
import os
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import time
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import uuid
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import datetime
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from dataclasses import dataclass
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from tqdm import tqdm
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from loguru import logger
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from bitmart.api_contract import APIContract
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from bitmart.lib.cloud_exceptions import APIException
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from 交易.tools import send_dingtalk_message
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@dataclass
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class StrategyConfig:
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# =============================
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# 1m | ETH 永续 | 控止损≤5/日
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# =============================
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# ===== 合约 =====
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contract_symbol: str = "ETHUSDT"
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open_type: str = "cross"
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leverage: str = "30"
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# ===== K线与指标 =====
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step_min: int = 1
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lookback_min: int = 240
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ema_len: int = 36
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atr_len: int = 14
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# ===== ADX 趋势过滤（新增）=====
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# 目的：单边趋势（ADX高）时，抑制/禁止逆势均值回归单，避免反复反向开仓止损
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enable_adx_filter: bool = True
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adx_len: int = 14
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adx_threshold: float = 25.0 # 常用：20~30区间，你可按回测调整
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# 过滤模式：
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# - "block_countertrend": 只禁止逆着 DI 的方向开仓（推荐，既防反手又不完全停机）
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# - "block_all": ADX 高时直接不允许任何新开仓（更保守）
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adx_mode: str = "block_countertrend"
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# 趋势保护冷却：当 ADX 高且刚止损，延长冷却，减少“止损->立刻反手”的连环
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cooldown_sec_after_sl_extra: int = 40
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# =========================================================
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# ✅ 自动阈值：ATR/Price 分位数基准（更稳，不被短时噪声带跑）
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# =========================================================
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vol_baseline_window: int = 60
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vol_baseline_quantile: float = 0.65
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vol_scale_min: float = 0.80
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vol_scale_max: float = 1.60
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# ✅ baseline 每 60 秒刷新一次（体感更明显、也省CPU）
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base_ratio_refresh_sec: int = 180
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# =========================================================
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# ✅ 动态 floor（方案一）
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# floor = clamp(min, base_k * base_ratio, max)
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# 目的：跟着典型波动变，过滤小噪声；tp/sl 也随环境自适应
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# =========================================================
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# entry_dev_floor 动态
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entry_dev_floor_min: float = 0.0012 # 0.12%
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entry_dev_floor_max: float = 0.0030 # 0.30%
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entry_dev_floor_base_k: float = 1.10 # entry_floor = 1.10 * base_ratio
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# tp_floor 动态
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tp_floor_min: float = 0.0006 # 0.06%
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tp_floor_max: float = 0.0020 # 0.20%
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tp_floor_base_k: float = 0.55 # tp_floor = 0.55 * base_ratio
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# sl_floor 动态
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sl_floor_min: float = 0.0018 # 0.18%
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sl_floor_max: float = 0.0060 # 0.60%
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sl_floor_base_k: float = 1.35 # sl_floor = 1.35 * base_ratio
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# =========================================================
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# ✅ 动态阈值倍率
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# =========================================================
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entry_k: float = 1.45
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tp_k: float = 0.65
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sl_k: float = 1.05
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# ===== 时间/冷却 =====
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max_hold_sec: int = 75
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cooldown_sec_after_exit: int = 20
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# ===== 下单/仓位 =====
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risk_percent: float = 0.004
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min_size: int = 1
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max_size: int = 5000
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# ===== 日内风控 =====
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daily_loss_limit: float = 0.02
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daily_profit_cap: float = 0.01
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# ===== 危险模式过滤 =====
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atr_ratio_kill: float = 0.0038
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big_body_kill: float = 0.010
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# ===== 轮询节奏 =====
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klines_refresh_sec: int = 10
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tick_refresh_sec: int = 1
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status_notify_sec: int = 60
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# =========================================================
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# ✅ 止损后同向入场加门槛（你原来的逻辑保留）
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# =========================================================
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reentry_penalty_mult: float = 1.55
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reentry_penalty_max_sec: int = 180
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reset_band_k: float = 0.45
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reset_band_floor: float = 0.0006
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# =========================================================
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# ✅ 止损后同方向 SL 放宽幅度与"止损时 vol_scale"联动
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# =========================================================
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post_sl_sl_max_sec: int = 90
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post_sl_mult_min: float = 1.02
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post_sl_mult_max: float = 1.16
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post_sl_vol_alpha: float = 0.20
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class BitmartFuturesMeanReversionBot:
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def __init__(self, cfg: StrategyConfig):
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self.cfg = cfg
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self.api_key = os.getenv("BITMART_API_KEY", "").strip()
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self.secret_key = os.getenv("BITMART_SECRET_KEY", "").strip()
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self.memo = os.getenv("BITMART_MEMO", "合约交易").strip()
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if not self.api_key or not self.secret_key:
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raise RuntimeError("请先设置环境变量 BITMART_API_KEY / BITMART_SECRET_KEY / BITMART_MEMO(可选)")
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self.contractAPI = APIContract(self.api_key, self.secret_key, self.memo, timeout=(5, 15))
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# 持仓状态: -1 空, 0 无, 1 多
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self.pos = 0
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self.entry_price = None
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self.entry_ts = None
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self.last_exit_ts = 0
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# 日内权益基准
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self.day_start_equity = None
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self.trading_enabled = True
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self.day_tag = datetime.date.today()
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# 缓存
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self._klines_cache = None
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self._klines_cache_ts = 0
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self._last_status_notify_ts = 0
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# ✅ base_ratio 缓存
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self._base_ratio_cached = 0.0015 # 初始化默认值 0.15%
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self._base_ratio_ts = 0.0
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# ✅ 止损后"同向入场加门槛"状态
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self.last_sl_dir = 0 # 1=多止损，-1=空止损，0=无
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self.last_sl_ts = 0.0
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# ✅ 止损后"同方向 SL 联动放宽"状态
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self.post_sl_dir = 0
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self.post_sl_ts = 0.0
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self.post_sl_vol_scale = 1.0 # 记录止损时的 vol_scale
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self.pbar = tqdm(total=60, desc="运行中(秒)", ncols=90)
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logger.info(f"初始化完成，基准波动率默认值: {self._base_ratio_cached * 100:.4f}%")
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# ----------------- 通用工具 -----------------
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def ding(self, msg, error=False):
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prefix = "❌bitmart：" if error else "🔔bitmart："
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if error:
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for _ in range(3):
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send_dingtalk_message(f"{prefix}{msg}")
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else:
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send_dingtalk_message(f"{prefix}{msg}")
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def set_leverage(self) -> bool:
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try:
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resp = self.contractAPI.post_submit_leverage(
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contract_symbol=self.cfg.contract_symbol,
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leverage=self.cfg.leverage,
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open_type=self.cfg.open_type
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)[0]
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if resp.get("code") == 1000:
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logger.success(f"设置杠杆成功：{self.cfg.open_type} + {self.cfg.leverage}x")
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return True
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logger.error(f"设置杠杆失败: {resp}")
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self.ding(f"设置杠杆失败: {resp}", error=True)
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return False
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except Exception as e:
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logger.error(f"设置杠杆异常: {e}")
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self.ding(f"设置杠杆异常: {e}", error=True)
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return False
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# ----------------- 行情/指标 -----------------
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def get_klines_cached(self):
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now = time.time()
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if self._klines_cache is not None and (now - self._klines_cache_ts) < self.cfg.klines_refresh_sec:
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return self._klines_cache
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kl = self.get_klines()
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if kl:
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self._klines_cache = kl
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self._klines_cache_ts = now
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return self._klines_cache
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def get_klines(self):
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try:
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end_time = int(time.time())
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start_time = end_time - 60 * self.cfg.lookback_min
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resp = self.contractAPI.get_kline(
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contract_symbol=self.cfg.contract_symbol,
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step=self.cfg.step_min,
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start_time=start_time,
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end_time=end_time
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)[0]
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if resp.get("code") != 1000:
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logger.error(f"获取K线失败: {resp}")
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return None
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data = resp.get("data", [])
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formatted = []
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for k in data:
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formatted.append({
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"id": int(k["timestamp"]),
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"open": float(k["open_price"]),
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"high": float(k["high_price"]),
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"low": float(k["low_price"]),
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"close": float(k["close_price"]),
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})
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formatted.sort(key=lambda x: x["id"])
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return formatted
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except Exception as e:
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logger.error(f"获取K线异常: {e}")
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self.ding(f"获取K线异常: {e}", error=True)
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return None
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def get_last_price(self, fallback_close: float) -> float:
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try:
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if hasattr(self.contractAPI, "get_contract_details"):
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r = self.contractAPI.get_contract_details(contract_symbol=self.cfg.contract_symbol)[0]
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d = r.get("data") if isinstance(r, dict) else None
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if isinstance(d, dict):
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for key in ("last_price", "mark_price", "index_price"):
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if key in d and d[key] is not None:
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return float(d[key])
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if hasattr(self.contractAPI, "get_ticker"):
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r = self.contractAPI.get_ticker(contract_symbol=self.cfg.contract_symbol)[0]
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d = r.get("data") if isinstance(r, dict) else None
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if isinstance(d, dict):
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for key in ("last_price", "price", "last", "close"):
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if key in d and d[key] is not None:
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return float(d[key])
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except Exception:
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pass
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return float(fallback_close)
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@staticmethod
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def ema(values, n: int) -> float:
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k = 2 / (n + 1)
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e = values[0]
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for v in values[1:]:
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e = v * k + e * (1 - k)
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return e
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@staticmethod
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def atr(klines, n: int) -> float:
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if len(klines) < n + 1:
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return 0.0
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trs = []
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for i in range(-n, 0):
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cur = klines[i]
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prev = klines[i - 1]
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tr = max(
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cur["high"] - cur["low"],
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abs(cur["high"] - prev["close"]),
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abs(cur["low"] - prev["close"]),
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)
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trs.append(tr)
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return sum(trs) / len(trs)
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@staticmethod
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def _wilder_smooth(prev: float, val: float, n: int) -> float:
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# Wilder smoothing: prev - prev/n + val
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return prev - (prev / n) + val
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def adx(self, klines, n: int):
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"""
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返回 (adx, plus_di, minus_di)
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采用经典 Wilder ADX/DI 计算（足够稳，避免趋势期逆势反复开仓）
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"""
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if len(klines) < (2 * n + 2):
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return 0.0, 0.0, 0.0
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highs = [k["high"] for k in klines]
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lows = [k["low"] for k in klines]
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closes = [k["close"] for k in klines]
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# 计算 TR, +DM, -DM 序列（从1开始）
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tr_list = []
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pdm_list = []
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mdm_list = []
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for i in range(1, len(klines)):
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high = highs[i]
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low = lows[i]
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prev_close = closes[i - 1]
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prev_high = highs[i - 1]
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prev_low = lows[i - 1]
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tr = max(high - low, abs(high - prev_close), abs(low - prev_close))
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up_move = high - prev_high
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down_move = prev_low - low
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pdm = up_move if (up_move > down_move and up_move > 0) else 0.0
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mdm = down_move if (down_move > up_move and down_move > 0) else 0.0
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tr_list.append(tr)
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pdm_list.append(pdm)
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mdm_list.append(mdm)
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# 初始平滑值（第一个n段的和）
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tr14 = sum(tr_list[:n])
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pdm14 = sum(pdm_list[:n])
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mdm14 = sum(mdm_list[:n])
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def safe_div(a, b):
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return (a / b) if b != 0 else 0.0
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plus_di = 100.0 * safe_div(pdm14, tr14)
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minus_di = 100.0 * safe_div(mdm14, tr14)
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dx = 100.0 * safe_div(abs(plus_di - minus_di), (plus_di + minus_di))
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dx_list = [dx]
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# 继续平滑并计算后续 DX
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for i in range(n, len(tr_list)):
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tr14 = self._wilder_smooth(tr14, tr_list[i], n)
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pdm14 = self._wilder_smooth(pdm14, pdm_list[i], n)
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mdm14 = self._wilder_smooth(mdm14, mdm_list[i], n)
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plus_di = 100.0 * safe_div(pdm14, tr14)
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minus_di = 100.0 * safe_div(mdm14, tr14)
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dx = 100.0 * safe_div(abs(plus_di - minus_di), (plus_di + minus_di))
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dx_list.append(dx)
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# ADX 是 DX 的 Wilder 平滑，常见做法：先取前 n 个 DX 的均值作为初值
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if len(dx_list) < (n + 1):
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return 0.0, plus_di, minus_di
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adx0 = sum(dx_list[:n]) / n
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adx_val = adx0
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for j in range(n, len(dx_list)):
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adx_val = (adx_val * (n - 1) + dx_list[j]) / n
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return float(adx_val), float(plus_di), float(minus_di)
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def is_danger_market(self, klines, price: float) -> bool:
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last = klines[-1]
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body = abs(last["close"] - last["open"]) / last["open"] if last["open"] else 0.0
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if body >= self.cfg.big_body_kill:
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return True
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a = self.atr(klines, self.cfg.atr_len)
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atr_ratio = (a / price) if price > 0 else 0.0
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if atr_ratio >= self.cfg.atr_ratio_kill:
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return True
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return False
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def atr_ratio_baseline(self, klines) -> float:
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"""简化版ATR基准计算"""
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window = min(self.cfg.vol_baseline_window, len(klines) - self.cfg.atr_len - 1)
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if window <= 10:
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logger.warning(f"数据不足计算基准: {len(klines)}根K线")
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return 0.0
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ratios = []
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step = 3
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for i in range(-window, 0, step):
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if len(klines) + i < self.cfg.atr_len + 1:
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continue
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start_idx = len(klines) + i - self.cfg.atr_len
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end_idx = len(klines) + i
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if start_idx < 0 or end_idx <= start_idx:
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continue
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sub_klines = klines[start_idx:end_idx]
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if len(sub_klines) >= self.cfg.atr_len + 1:
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a = self.atr(sub_klines, self.cfg.atr_len)
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price = klines[end_idx - 1]["close"]
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if a > 0 and price > 0:
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ratio = a / price
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if 0.0001 < ratio < 0.01:
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ratios.append(ratio)
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if len(ratios) < 5:
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a = self.atr(klines[-60:], self.cfg.atr_len)
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price = klines[-1]["close"]
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if a > 0 and price > 0:
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baseline = a / price
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logger.debug(f"使用全量数据计算基准: {baseline * 100:.4f}%")
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return baseline
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return 0.0
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ratios.sort()
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idx = min(len(ratios) - 1, max(0, int(self.cfg.vol_baseline_quantile * (len(ratios) - 1))))
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baseline = ratios[idx]
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logger.debug(
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f"基准计算: 样本数={len(ratios)}, 基准={baseline * 100:.4f}%, "
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f"范围=[{ratios[0] * 100:.4f}%, {ratios[-1] * 100:.4f}%]"
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)
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return baseline
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def get_base_ratio_cached(self, klines) -> float:
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"""获取缓存的基准波动率，定期刷新"""
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now = time.time()
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refresh_sec = self.cfg.base_ratio_refresh_sec
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if (self._base_ratio_cached is None or (now - self._base_ratio_ts) >= refresh_sec):
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baseline = self.atr_ratio_baseline(klines)
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if baseline > 0.0001:
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self._base_ratio_cached = baseline
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self._base_ratio_ts = now
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logger.info(f"基准波动率更新: {baseline * 100:.4f}%")
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else:
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current_price = klines[-1]["close"] if klines else 3000
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if current_price > 4000:
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default_baseline = 0.0010
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elif current_price > 3500:
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default_baseline = 0.0012
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elif current_price > 3000:
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default_baseline = 0.0015
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elif current_price > 2500:
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default_baseline = 0.0018
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else:
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default_baseline = 0.0020
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self._base_ratio_cached = default_baseline
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self._base_ratio_ts = now
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logger.warning(
|
||
f"使用价格动态默认基准: {default_baseline * 100:.4f}% (价格=${current_price:.0f})"
|
||
)
|
||
|
||
return self._base_ratio_cached
|
||
|
||
@staticmethod
|
||
def _clamp(x: float, lo: float, hi: float) -> float:
|
||
return max(lo, min(hi, x))
|
||
|
||
def dynamic_thresholds(self, atr_ratio: float, base_ratio: float):
|
||
"""
|
||
✅ entry/tp/sl 全部动态（修复版）：
|
||
- vol_scale：atr_ratio/base_ratio 限幅
|
||
- floor：方案一 (floor = clamp(min, k*base_ratio, max))
|
||
- 最终阈值：max(floor, k * vol_scale * atr_ratio)
|
||
"""
|
||
if atr_ratio <= 0:
|
||
logger.warning(f"ATR比率异常: {atr_ratio}")
|
||
atr_ratio = 0.001
|
||
|
||
if base_ratio < 0.0005:
|
||
base_ratio = max(0.001, atr_ratio * 1.2)
|
||
logger.debug(f"基准太小，使用调整后的atr_ratio: {base_ratio * 100:.4f}%")
|
||
|
||
if base_ratio > 0:
|
||
raw_scale = atr_ratio / base_ratio
|
||
vol_scale = self._clamp(raw_scale, self.cfg.vol_scale_min, self.cfg.vol_scale_max)
|
||
logger.debug(
|
||
f"vol_scale: {raw_scale:.2f} → {vol_scale:.2f} (atr={atr_ratio * 100:.3f}%, base={base_ratio * 100:.3f}%)"
|
||
)
|
||
else:
|
||
vol_scale = 1.0
|
||
logger.warning("基准无效，使用默认vol_scale=1.0")
|
||
|
||
entry_floor_raw = self.cfg.entry_dev_floor_base_k * base_ratio
|
||
entry_floor = self._clamp(entry_floor_raw, self.cfg.entry_dev_floor_min, self.cfg.entry_dev_floor_max)
|
||
|
||
tp_floor_raw = self.cfg.tp_floor_base_k * base_ratio
|
||
tp_floor = self._clamp(tp_floor_raw, self.cfg.tp_floor_min, self.cfg.tp_floor_max)
|
||
|
||
sl_floor_raw = self.cfg.sl_floor_base_k * base_ratio
|
||
sl_floor = self._clamp(sl_floor_raw, self.cfg.sl_floor_min, self.cfg.sl_floor_max)
|
||
|
||
entry_dev_atr_part = self.cfg.entry_k * vol_scale * atr_ratio
|
||
entry_dev = max(entry_floor, entry_dev_atr_part)
|
||
|
||
tp_atr_part = self.cfg.tp_k * vol_scale * atr_ratio
|
||
tp = max(tp_floor, tp_atr_part)
|
||
|
||
sl_atr_part = self.cfg.sl_k * vol_scale * atr_ratio
|
||
sl = max(sl_floor, sl_atr_part)
|
||
|
||
entry_dev = max(entry_dev, self.cfg.entry_dev_floor_min)
|
||
|
||
logger.info(
|
||
f"动态阈值: atr={atr_ratio * 100:.4f}%, base={base_ratio * 100:.4f}%, "
|
||
f"vol_scale={vol_scale:.2f}, floor={entry_floor * 100:.4f}%, "
|
||
f"atr_part={entry_dev_atr_part * 100:.4f}%, 最终entry_dev={entry_dev * 100:.4f}%"
|
||
)
|
||
|
||
return entry_dev, tp, sl, vol_scale, entry_floor, tp_floor, sl_floor
|
||
|
||
# ----------------- 账户/仓位 -----------------
|
||
def get_assets_available(self) -> float:
|
||
try:
|
||
resp = self.contractAPI.get_assets_detail()[0]
|
||
if resp.get("code") != 1000:
|
||
return 0.0
|
||
data = resp.get("data")
|
||
if isinstance(data, dict):
|
||
return float(data.get("available_balance", 0))
|
||
if isinstance(data, list):
|
||
for asset in data:
|
||
if asset.get("currency") == "USDT":
|
||
return float(asset.get("available_balance", 0))
|
||
return 0.0
|
||
except Exception as e:
|
||
logger.error(f"余额查询异常: {e}")
|
||
return 0.0
|
||
|
||
def get_position_status(self) -> bool:
|
||
try:
|
||
resp = self.contractAPI.get_position(contract_symbol=self.cfg.contract_symbol)[0]
|
||
if resp.get("code") != 1000:
|
||
return False
|
||
|
||
positions = resp.get("data", [])
|
||
if not positions:
|
||
self.pos = 0
|
||
return True
|
||
|
||
p = positions[0]
|
||
self.pos = 1 if p["position_type"] == 1 else -1
|
||
return True
|
||
except Exception as e:
|
||
logger.error(f"持仓查询异常: {e}")
|
||
self.ding(f"持仓查询异常: {e}", error=True)
|
||
return False
|
||
|
||
def get_equity_proxy(self) -> float:
|
||
return self.get_assets_available()
|
||
|
||
def refresh_daily_baseline(self):
|
||
today = datetime.date.today()
|
||
if today != self.day_tag:
|
||
self.day_tag = today
|
||
self.day_start_equity = None
|
||
self.trading_enabled = True
|
||
self.ding(f"新的一天({today})：重置日内风控基准")
|
||
|
||
def risk_kill_switch(self):
|
||
self.refresh_daily_baseline()
|
||
equity = self.get_equity_proxy()
|
||
if equity <= 0:
|
||
return
|
||
|
||
if self.day_start_equity is None:
|
||
self.day_start_equity = equity
|
||
logger.info(f"日内权益基准设定：{equity:.2f} USDT")
|
||
return
|
||
|
||
pnl = (equity - self.day_start_equity) / self.day_start_equity
|
||
if pnl <= -self.cfg.daily_loss_limit:
|
||
self.trading_enabled = False
|
||
self.ding(f"触发日止损：{pnl * 100:.2f}% -> 停机", error=True)
|
||
|
||
if pnl >= self.cfg.daily_profit_cap:
|
||
self.trading_enabled = False
|
||
self.ding(f"达到日盈利封顶：{pnl * 100:.2f}% -> 停机")
|
||
|
||
# ----------------- 下单 -----------------
|
||
def calculate_size(self, price: float) -> int:
|
||
bal = self.get_assets_available()
|
||
if bal < 10:
|
||
return 0
|
||
|
||
margin = bal * self.cfg.risk_percent
|
||
lev = int(self.cfg.leverage)
|
||
|
||
# ⚠️ 沿用你的原假设：1张≈0.001ETH
|
||
size = int((margin * lev) / (price * 0.001))
|
||
size = max(self.cfg.min_size, size)
|
||
size = min(self.cfg.max_size, size)
|
||
return size
|
||
|
||
def place_market_order(self, side: int, size: int) -> bool:
|
||
if size <= 0:
|
||
return False
|
||
|
||
client_order_id = f"mr_{int(time.time())}_{uuid.uuid4().hex[:8]}"
|
||
try:
|
||
resp = self.contractAPI.post_submit_order(
|
||
contract_symbol=self.cfg.contract_symbol,
|
||
client_order_id=client_order_id,
|
||
side=side,
|
||
mode=1,
|
||
type="market",
|
||
leverage=self.cfg.leverage,
|
||
open_type=self.cfg.open_type,
|
||
size=size
|
||
)[0]
|
||
|
||
logger.info(f"order_resp: {resp}")
|
||
|
||
if resp.get("code") == 1000:
|
||
return True
|
||
|
||
self.ding(f"下单失败: {resp}", error=True)
|
||
return False
|
||
|
||
except APIException as e:
|
||
logger.error(f"API下单异常: {e}")
|
||
self.ding(f"API下单异常: {e}", error=True)
|
||
return False
|
||
|
||
except Exception as e:
|
||
logger.error(f"下单未知异常: {e}")
|
||
self.ding(f"下单未知异常: {e}", error=True)
|
||
return False
|
||
|
||
def close_position_all(self):
|
||
if self.pos == 1:
|
||
ok = self.place_market_order(3, 999999)
|
||
if ok:
|
||
self.pos = 0
|
||
elif self.pos == -1:
|
||
ok = self.place_market_order(2, 999999)
|
||
if ok:
|
||
self.pos = 0
|
||
|
||
# ----------------- 止损后机制 -----------------
|
||
def _reentry_penalty_active(self, dev: float, entry_dev: float) -> bool:
|
||
"""检查是否需要应用重新入场惩罚（你原逻辑保留）"""
|
||
if self.last_sl_dir == 0:
|
||
return False
|
||
|
||
if (time.time() - self.last_sl_ts) > self.cfg.reentry_penalty_max_sec:
|
||
self.last_sl_dir = 0
|
||
return False
|
||
|
||
reset_band = max(self.cfg.reset_band_floor, self.cfg.reset_band_k * entry_dev)
|
||
if abs(dev) <= reset_band:
|
||
self.last_sl_dir = 0
|
||
return False
|
||
|
||
return True
|
||
|
||
def _post_sl_dynamic_mult(self) -> float:
|
||
"""计算止损后SL放宽倍数"""
|
||
if self.post_sl_dir == 0:
|
||
return 1.0
|
||
|
||
if (time.time() - self.post_sl_ts) > self.cfg.post_sl_sl_max_sec:
|
||
self.post_sl_dir = 0
|
||
self.post_sl_vol_scale = 1.0
|
||
return 1.0
|
||
|
||
raw = 1.0 + self.cfg.post_sl_vol_alpha * (self.post_sl_vol_scale - 1.0)
|
||
raw = max(1.0, raw) # 不缩小止损，只放宽
|
||
return max(self.cfg.post_sl_mult_min, min(self.cfg.post_sl_mult_max, raw))
|
||
|
||
# ----------------- 交易逻辑 -----------------
|
||
def in_cooldown(self) -> bool:
|
||
"""检查是否在冷却期内（新增：止损后可额外延长冷却，用于抑制反手连环）"""
|
||
cd = self.cfg.cooldown_sec_after_exit
|
||
if self.last_sl_ts and (time.time() - self.last_sl_ts) < self.cfg.reentry_penalty_max_sec:
|
||
cd += max(0, self.cfg.cooldown_sec_after_sl_extra)
|
||
return (time.time() - self.last_exit_ts) < cd
|
||
|
||
def _adx_blocks_entry(self, adx_val: float, plus_di: float, minus_di: float, want_dir: int) -> bool:
|
||
"""
|
||
ADX 趋势过滤：
|
||
- want_dir: 1=想开多, -1=想开空
|
||
"""
|
||
if not self.cfg.enable_adx_filter:
|
||
return False
|
||
if adx_val < self.cfg.adx_threshold:
|
||
return False
|
||
|
||
if self.cfg.adx_mode == "block_all":
|
||
return True
|
||
|
||
# block_countertrend：只禁止逆 DI 方向
|
||
# 上升趋势：+DI > -DI => 禁止开空
|
||
# 下降趋势：-DI > +DI => 禁止开多
|
||
if plus_di > minus_di and want_dir == -1:
|
||
return True
|
||
if minus_di > plus_di and want_dir == 1:
|
||
return True
|
||
return False
|
||
|
||
def maybe_enter(self, price: float, ema_value: float, entry_dev: float,
|
||
adx_val: float, plus_di: float, minus_di: float):
|
||
"""检查并执行入场（新增：ADX趋势过滤，防止趋势期逆势反复开仓）"""
|
||
if self.pos != 0:
|
||
return
|
||
if self.in_cooldown():
|
||
return
|
||
|
||
dev = (price - ema_value) / ema_value if ema_value else 0.0
|
||
size = self.calculate_size(price)
|
||
if size <= 0:
|
||
return
|
||
|
||
penalty_active = self._reentry_penalty_active(dev, entry_dev)
|
||
|
||
long_th = -entry_dev
|
||
short_th = entry_dev
|
||
|
||
if penalty_active:
|
||
if self.last_sl_dir == 1:
|
||
long_th = -entry_dev * self.cfg.reentry_penalty_mult
|
||
logger.info(f"多头止损后惩罚生效: long_th={long_th * 100:.3f}%")
|
||
elif self.last_sl_dir == -1:
|
||
short_th = entry_dev * self.cfg.reentry_penalty_mult
|
||
logger.info(f"空头止损后惩罚生效: short_th={short_th * 100:.3f}%")
|
||
|
||
logger.info(
|
||
f"入场检查: price={price:.2f}, ema={ema_value:.2f}, dev={dev * 100:.3f}% "
|
||
f"(entry_dev={entry_dev * 100:.3f}%, long_th={long_th * 100:.3f}%, short_th={short_th * 100:.3f}%) "
|
||
f"ADX={adx_val:.2f} +DI={plus_di:.2f} -DI={minus_di:.2f} "
|
||
f"size={size}, penalty={penalty_active}, last_sl_dir={self.last_sl_dir}"
|
||
)
|
||
|
||
# 先判断信号，再用 ADX 过滤（这样日志更直观）
|
||
if dev <= long_th:
|
||
if self._adx_blocks_entry(adx_val, plus_di, minus_di, want_dir=1):
|
||
logger.warning(
|
||
f"ADX过滤：趋势期禁止逆势开多（ADX={adx_val:.2f}, +DI={plus_di:.2f}, -DI={minus_di:.2f}）"
|
||
)
|
||
return
|
||
|
||
if self.place_market_order(1, size):
|
||
self.pos = 1
|
||
self.entry_price = price
|
||
self.entry_ts = time.time()
|
||
self.ding(f"✅开多：dev={dev * 100:.3f}% size={size} entry={price:.2f}")
|
||
|
||
elif dev >= short_th:
|
||
if self._adx_blocks_entry(adx_val, plus_di, minus_di, want_dir=-1):
|
||
logger.warning(
|
||
f"ADX过滤：趋势期禁止逆势开空（ADX={adx_val:.2f}, +DI={plus_di:.2f}, -DI={minus_di:.2f}）"
|
||
)
|
||
return
|
||
|
||
if self.place_market_order(4, size):
|
||
self.pos = -1
|
||
self.entry_price = price
|
||
self.entry_ts = time.time()
|
||
self.ding(f"✅开空：dev={dev * 100:.3f}% size={size} entry={price:.2f}")
|
||
|
||
def maybe_exit(self, price: float, tp: float, sl: float, vol_scale: float):
|
||
"""检查并执行出场"""
|
||
if self.pos == 0 or self.entry_price is None or self.entry_ts is None:
|
||
return
|
||
|
||
hold = time.time() - self.entry_ts
|
||
|
||
if self.pos == 1:
|
||
pnl = (price - self.entry_price) / self.entry_price
|
||
else:
|
||
pnl = (self.entry_price - price) / self.entry_price
|
||
|
||
sl_mult = 1.0
|
||
if self.post_sl_dir == self.pos and self.post_sl_dir != 0:
|
||
sl_mult = self._post_sl_dynamic_mult()
|
||
effective_sl = sl * sl_mult
|
||
|
||
if pnl >= tp:
|
||
self.close_position_all()
|
||
self.ding(f"🎯止盈：pnl={pnl * 100:.3f}% price={price:.2f} tp={tp * 100:.3f}%")
|
||
self.entry_price, self.entry_ts = None, None
|
||
self.last_exit_ts = time.time()
|
||
|
||
elif pnl <= -effective_sl:
|
||
sl_dir = self.pos
|
||
self.close_position_all()
|
||
self.ding(
|
||
f"🛑止损：pnl={pnl * 100:.3f}% price={price:.2f} "
|
||
f"sl={sl * 100:.3f}% effective_sl={effective_sl * 100:.3f}%(×{sl_mult:.2f})",
|
||
error=True
|
||
)
|
||
|
||
# 记录止损方向与时间
|
||
self.last_sl_dir = sl_dir
|
||
self.last_sl_ts = time.time()
|
||
|
||
self.post_sl_dir = sl_dir
|
||
self.post_sl_ts = time.time()
|
||
self.post_sl_vol_scale = float(vol_scale)
|
||
|
||
self.entry_price, self.entry_ts = None, None
|
||
self.last_exit_ts = time.time()
|
||
|
||
elif hold >= self.cfg.max_hold_sec:
|
||
self.close_position_all()
|
||
self.ding(f"⏱超时：hold={int(hold)}s pnl={pnl * 100:.3f}% price={price:.2f}")
|
||
self.entry_price, self.entry_ts = None, None
|
||
self.last_exit_ts = time.time()
|
||
|
||
def notify_status_throttled(self, price: float, ema_value: float, dev: float, bal: float,
|
||
atr_ratio: float, base_ratio: float, vol_scale: float,
|
||
entry_dev: float, tp: float, sl: float,
|
||
entry_floor: float, tp_floor: float, sl_floor: float,
|
||
adx_val: float, plus_di: float, minus_di: float):
|
||
"""限频状态通知"""
|
||
now = time.time()
|
||
if (now - self._last_status_notify_ts) < self.cfg.status_notify_sec:
|
||
return
|
||
self._last_status_notify_ts = now
|
||
|
||
direction_str = "多" if self.pos == 1 else ("空" if self.pos == -1 else "无")
|
||
penalty_active = self._reentry_penalty_active(dev, entry_dev)
|
||
|
||
sl_mult = 1.0
|
||
if self.pos != 0 and self.post_sl_dir == self.pos:
|
||
sl_mult = self._post_sl_dynamic_mult()
|
||
|
||
base_age = int(now - self._base_ratio_ts) if self._base_ratio_ts else -1
|
||
|
||
msg = (
|
||
f"【BitMart {self.cfg.contract_symbol}｜1m均值回归(动态阈值+ADX过滤)】\n"
|
||
f"📊 状态：{direction_str}\n"
|
||
f"💰 现价：{price:.2f} | EMA{self.cfg.ema_len}：{ema_value:.2f}\n"
|
||
f"📈 偏离：{dev * 100:.3f}% (入场阈值：±{entry_dev * 100:.3f}%)\n"
|
||
f"🌊 波动率：ATR比={atr_ratio * 100:.3f}% | 基准={base_ratio * 100:.3f}% | 缩放={vol_scale:.2f}\n"
|
||
f"🧭 趋势：ADX={adx_val:.2f} | +DI={plus_di:.2f} | -DI={minus_di:.2f} "
|
||
f"(阈值={self.cfg.adx_threshold:.1f}, 模式={self.cfg.adx_mode})\n"
|
||
f"🎯 动态Floor：入场={entry_floor * 100:.3f}% | 止盈={tp_floor * 100:.3f}% | 止损={sl_floor * 100:.3f}%\n"
|
||
f"💰 止盈/止损：{tp * 100:.3f}% / {sl * 100:.3f}% (盈亏比：{tp / sl:.2f})\n"
|
||
f"🔄 基准刷新：{self.cfg.base_ratio_refresh_sec}s (已过={base_age}s)\n"
|
||
f"⚠️ 止损同向加门槛：{'开启' if penalty_active else '关闭'} (方向={self.last_sl_dir})\n"
|
||
f"💳 可用余额：{bal:.2f} USDT | 杠杆：{self.cfg.leverage}x\n"
|
||
f"⏱️ 持仓限制：{self.cfg.max_hold_sec}s | 冷却：{self.cfg.cooldown_sec_after_exit}s"
|
||
)
|
||
self.ding(msg)
|
||
|
||
def action(self):
|
||
"""主循环"""
|
||
if not self.set_leverage():
|
||
self.ding("杠杆设置失败，停止运行", error=True)
|
||
return
|
||
|
||
while True:
|
||
now_dt = datetime.datetime.now()
|
||
self.pbar.n = now_dt.second
|
||
self.pbar.refresh()
|
||
|
||
# 1. 获取K线数据
|
||
klines = self.get_klines_cached()
|
||
if not klines or len(klines) < (max(self.cfg.ema_len + 5, 2 * self.cfg.adx_len + 5)):
|
||
logger.warning("K线数据不足，等待...")
|
||
time.sleep(1)
|
||
continue
|
||
|
||
# 2. 计算技术指标
|
||
last_k = klines[-1]
|
||
closes = [k["close"] for k in klines[-(self.cfg.ema_len + 1):]]
|
||
ema_value = self.ema(closes, self.cfg.ema_len)
|
||
|
||
price = self.get_last_price(fallback_close=float(last_k["close"]))
|
||
dev = (price - ema_value) / ema_value if ema_value else 0.0
|
||
|
||
# 3. 计算波动率相关指标
|
||
a = self.atr(klines, self.cfg.atr_len)
|
||
atr_ratio = (a / price) if price > 0 else 0.0
|
||
base_ratio = self.get_base_ratio_cached(klines)
|
||
|
||
# 4. 计算动态阈值
|
||
entry_dev, tp, sl, vol_scale, entry_floor, tp_floor, sl_floor = self.dynamic_thresholds(
|
||
atr_ratio, base_ratio
|
||
)
|
||
|
||
# 5. 计算 ADX（新增）
|
||
adx_val, plus_di, minus_di = self.adx(klines, self.cfg.adx_len)
|
||
logger.info(f"ADX: {adx_val:.2f} (+DI={plus_di:.2f}, -DI={minus_di:.2f})")
|
||
|
||
# 6. 风控检查
|
||
self.risk_kill_switch()
|
||
|
||
# 7. 获取持仓状态
|
||
if not self.get_position_status():
|
||
time.sleep(1)
|
||
continue
|
||
|
||
# 8. 检查交易是否启用
|
||
if not self.trading_enabled:
|
||
if self.pos != 0:
|
||
self.close_position_all()
|
||
logger.warning("交易被禁用（风控触发），等待...")
|
||
time.sleep(5)
|
||
continue
|
||
|
||
# 9. 检查危险市场
|
||
if self.is_danger_market(klines, price):
|
||
logger.warning("危险模式：高波动/大实体K，暂停开仓")
|
||
self.maybe_exit(price, tp, sl, vol_scale)
|
||
time.sleep(self.cfg.tick_refresh_sec)
|
||
continue
|
||
|
||
# 10. 执行交易逻辑
|
||
self.maybe_exit(price, tp, sl, vol_scale)
|
||
self.maybe_enter(price, ema_value, entry_dev, adx_val, plus_di, minus_di)
|
||
|
||
# 11. 状态通知
|
||
bal = self.get_assets_available()
|
||
self.notify_status_throttled(
|
||
price, ema_value, dev, bal,
|
||
atr_ratio, base_ratio, vol_scale,
|
||
entry_dev, tp, sl,
|
||
entry_floor, tp_floor, sl_floor,
|
||
adx_val, plus_di, minus_di
|
||
)
|
||
|
||
time.sleep(self.cfg.tick_refresh_sec)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
"""
|
||
Windows PowerShell:
|
||
setx BITMART_API_KEY "你的key"
|
||
setx BITMART_SECRET_KEY "你的secret"
|
||
setx BITMART_MEMO "合约交易"
|
||
重新打开终端再运行。
|
||
|
||
Linux/macOS:
|
||
export BITMART_API_KEY="你的key"
|
||
export BITMART_SECRET_KEY="你的secret"
|
||
export BITMART_MEMO "合约交易"
|
||
"""
|
||
cfg = StrategyConfig()
|
||
bot = BitmartFuturesMeanReversionBot(cfg)
|
||
|
||
logger.remove()
|
||
logger.add(lambda msg: tqdm.write(msg, end=""), level="INFO")
|
||
|
||
try:
|
||
bot.action()
|
||
except KeyboardInterrupt:
|
||
logger.info("程序被用户中断")
|
||
bot.ding("🤖 策略已手动停止")
|
||
except Exception as e:
|
||
logger.error(f"程序异常退出: {e}")
|
||
bot.ding(f"❌ 策略异常退出: {e}", error=True)
|
||
raise
|