866 lines
32 KiB
Python
866 lines
32 KiB
Python
import os
|
||
import time
|
||
import uuid
|
||
import datetime
|
||
from dataclasses import dataclass
|
||
|
||
from tqdm import tqdm
|
||
from loguru import logger
|
||
|
||
from bitmart.api_contract import APIContract
|
||
from bitmart.lib.cloud_exceptions import APIException
|
||
|
||
from 交易.tools import send_dingtalk_message
|
||
|
||
|
||
@dataclass
|
||
class StrategyConfig:
|
||
# =============================
|
||
# 1m | ETH 永续 | 控止损≤5/日
|
||
# =============================
|
||
|
||
# ===== 合约 =====
|
||
contract_symbol: str = "ETHUSDT"
|
||
open_type: str = "cross"
|
||
leverage: str = "30"
|
||
|
||
# ===== K线与指标 =====
|
||
step_min: int = 1
|
||
lookback_min: int = 240
|
||
ema_len: int = 36
|
||
atr_len: int = 14
|
||
|
||
# =========================================================
|
||
# ✅ 自动阈值：ATR/Price 分位数基准（更稳，不被短时噪声带跑）
|
||
# =========================================================
|
||
vol_baseline_window: int = 60
|
||
vol_baseline_quantile: float = 0.65
|
||
vol_scale_min: float = 0.80
|
||
vol_scale_max: float = 1.60
|
||
|
||
# ✅ baseline 每 60 秒刷新一次（体感更明显、也省CPU）
|
||
base_ratio_refresh_sec: int = 60
|
||
|
||
# =========================================================
|
||
# ✅ 动态 floor（方案一）
|
||
# floor = clamp(min, base_k * base_ratio, max)
|
||
# 目的：跟着典型波动变，过滤小噪声；tp/sl 也随环境自适应
|
||
# =========================================================
|
||
# entry_dev_floor 动态
|
||
entry_dev_floor_min: float = 0.0012 # 0.12%
|
||
entry_dev_floor_max: float = 0.0030 # 0.30%（可按你偏好调）
|
||
entry_dev_floor_base_k: float = 1.10 # entry_floor = 1.10 * base_ratio
|
||
|
||
# tp_floor 动态
|
||
tp_floor_min: float = 0.0006 # 0.06%
|
||
tp_floor_max: float = 0.0020 # 0.20%
|
||
tp_floor_base_k: float = 0.55 # tp_floor = 0.55 * base_ratio（止盈别太大，1m回归更实际）
|
||
|
||
# sl_floor 动态
|
||
sl_floor_min: float = 0.0018 # 0.18%
|
||
sl_floor_max: float = 0.0060 # 0.60%
|
||
sl_floor_base_k: float = 1.35 # sl_floor = 1.35 * base_ratio（ETH 1m 插针多，止损下限可更稳）
|
||
|
||
# =========================================================
|
||
# ✅ 动态阈值倍率（仍然保留你原来思路）
|
||
# =========================================================
|
||
entry_k: float = 1.45
|
||
tp_k: float = 0.65
|
||
sl_k: float = 1.05
|
||
|
||
# ===== 时间/冷却 =====
|
||
max_hold_sec: int = 75
|
||
cooldown_sec_after_exit: int = 20
|
||
|
||
# ===== 下单/仓位 =====
|
||
risk_percent: float = 0.004
|
||
min_size: int = 1
|
||
max_size: int = 5000
|
||
|
||
# ===== 日内风控 =====
|
||
daily_loss_limit: float = 0.02
|
||
daily_profit_cap: float = 0.01
|
||
|
||
# ===== 危险模式过滤 =====
|
||
atr_ratio_kill: float = 0.0038
|
||
big_body_kill: float = 0.010
|
||
|
||
# ===== 轮询节奏 =====
|
||
klines_refresh_sec: int = 10
|
||
tick_refresh_sec: int = 1
|
||
status_notify_sec: int = 60
|
||
|
||
# =========================================================
|
||
# ✅ 止损后同向入场加门槛（但不禁止同向重入）
|
||
# =========================================================
|
||
reentry_penalty_mult: float = 1.55
|
||
reentry_penalty_max_sec: int = 180
|
||
reset_band_k: float = 0.45
|
||
reset_band_floor: float = 0.0006
|
||
|
||
# =========================================================
|
||
# ✅ 止损后同方向 SL 放宽幅度与"止损时 vol_scale"联动
|
||
# =========================================================
|
||
post_sl_sl_max_sec: int = 90
|
||
post_sl_mult_min: float = 1.02
|
||
post_sl_mult_max: float = 1.16
|
||
post_sl_vol_alpha: float = 0.20
|
||
|
||
|
||
class BitmartFuturesMeanReversionBot:
|
||
def __init__(self, cfg: StrategyConfig):
|
||
self.cfg = cfg
|
||
|
||
self.api_key = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8"
|
||
self.secret_key = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5"
|
||
self.memo = "合约交易"
|
||
|
||
if not self.api_key or not self.secret_key:
|
||
raise RuntimeError("请先设置环境变量 BITMART_API_KEY / BITMART_SECRET_KEY / BITMART_MEMO(可选)")
|
||
|
||
self.contractAPI = APIContract(self.api_key, self.secret_key, self.memo, timeout=(5, 15))
|
||
|
||
# 持仓状态: -1 空, 0 无, 1 多
|
||
self.pos = 0
|
||
self.entry_price = None
|
||
self.entry_ts = None
|
||
self.last_exit_ts = 0
|
||
|
||
# 日内权益基准
|
||
self.day_start_equity = None
|
||
self.trading_enabled = True
|
||
self.day_tag = datetime.date.today()
|
||
|
||
# 缓存
|
||
self._klines_cache = None
|
||
self._klines_cache_ts = 0
|
||
self._last_status_notify_ts = 0
|
||
|
||
# ✅ base_ratio 缓存
|
||
self._base_ratio_cached = 0.0015 # 初始化默认值 0.15%
|
||
self._base_ratio_ts = 0.0
|
||
|
||
# ✅ 止损后"同向入场加门槛"状态
|
||
self.last_sl_dir = 0 # 1=多止损，-1=空止损，0=无
|
||
self.last_sl_ts = 0.0
|
||
|
||
# ✅ 止损后"同方向 SL 联动放宽"状态
|
||
self.post_sl_dir = 0
|
||
self.post_sl_ts = 0.0
|
||
self.post_sl_vol_scale = 1.0 # 记录止损时的 vol_scale
|
||
|
||
self.pbar = tqdm(total=60, desc="运行中(秒)", ncols=90)
|
||
|
||
logger.info(f"初始化完成，基准波动率默认值: {self._base_ratio_cached * 100:.4f}%")
|
||
|
||
# ----------------- 通用工具 -----------------
|
||
def ding(self, msg, error=False):
|
||
prefix = "❌bitmart：" if error else "🔔bitmart："
|
||
if error:
|
||
for _ in range(3):
|
||
send_dingtalk_message(f"{prefix}{msg}")
|
||
else:
|
||
send_dingtalk_message(f"{prefix}{msg}")
|
||
|
||
def set_leverage(self) -> bool:
|
||
try:
|
||
resp = self.contractAPI.post_submit_leverage(
|
||
contract_symbol=self.cfg.contract_symbol,
|
||
leverage=self.cfg.leverage,
|
||
open_type=self.cfg.open_type
|
||
)[0]
|
||
if resp.get("code") == 1000:
|
||
logger.success(f"设置杠杆成功：{self.cfg.open_type} + {self.cfg.leverage}x")
|
||
return True
|
||
logger.error(f"设置杠杆失败: {resp}")
|
||
self.ding(f"设置杠杆失败: {resp}", error=True)
|
||
return False
|
||
except Exception as e:
|
||
logger.error(f"设置杠杆异常: {e}")
|
||
self.ding(f"设置杠杆异常: {e}", error=True)
|
||
return False
|
||
|
||
# ----------------- 行情/指标 -----------------
|
||
def get_klines_cached(self):
|
||
now = time.time()
|
||
if self._klines_cache is not None and (now - self._klines_cache_ts) < self.cfg.klines_refresh_sec:
|
||
return self._klines_cache
|
||
|
||
kl = self.get_klines()
|
||
if kl:
|
||
self._klines_cache = kl
|
||
self._klines_cache_ts = now
|
||
return self._klines_cache
|
||
|
||
def get_klines(self):
|
||
try:
|
||
end_time = int(time.time())
|
||
start_time = end_time - 60 * self.cfg.lookback_min
|
||
|
||
resp = self.contractAPI.get_kline(
|
||
contract_symbol=self.cfg.contract_symbol,
|
||
step=self.cfg.step_min,
|
||
start_time=start_time,
|
||
end_time=end_time
|
||
)[0]
|
||
|
||
if resp.get("code") != 1000:
|
||
logger.error(f"获取K线失败: {resp}")
|
||
return None
|
||
|
||
data = resp.get("data", [])
|
||
formatted = []
|
||
for k in data:
|
||
formatted.append({
|
||
"id": int(k["timestamp"]),
|
||
"open": float(k["open_price"]),
|
||
"high": float(k["high_price"]),
|
||
"low": float(k["low_price"]),
|
||
"close": float(k["close_price"]),
|
||
})
|
||
formatted.sort(key=lambda x: x["id"])
|
||
return formatted
|
||
except Exception as e:
|
||
logger.error(f"获取K线异常: {e}")
|
||
self.ding(f"获取K线异常: {e}", error=True)
|
||
return None
|
||
|
||
def get_last_price(self, fallback_close: float) -> float:
|
||
try:
|
||
if hasattr(self.contractAPI, "get_contract_details"):
|
||
r = self.contractAPI.get_contract_details(contract_symbol=self.cfg.contract_symbol)[0]
|
||
d = r.get("data") if isinstance(r, dict) else None
|
||
if isinstance(d, dict):
|
||
for key in ("last_price", "mark_price", "index_price"):
|
||
if key in d and d[key] is not None:
|
||
return float(d[key])
|
||
|
||
if hasattr(self.contractAPI, "get_ticker"):
|
||
r = self.contractAPI.get_ticker(contract_symbol=self.cfg.contract_symbol)[0]
|
||
d = r.get("data") if isinstance(r, dict) else None
|
||
if isinstance(d, dict):
|
||
for key in ("last_price", "price", "last", "close"):
|
||
if key in d and d[key] is not None:
|
||
return float(d[key])
|
||
except Exception:
|
||
pass
|
||
|
||
return float(fallback_close)
|
||
|
||
@staticmethod
|
||
def ema(values, n: int) -> float:
|
||
k = 2 / (n + 1)
|
||
e = values[0]
|
||
for v in values[1:]:
|
||
e = v * k + e * (1 - k)
|
||
return e
|
||
|
||
@staticmethod
|
||
def atr(klines, n: int) -> float:
|
||
if len(klines) < n + 1:
|
||
return 0.0
|
||
trs = []
|
||
for i in range(-n, 0):
|
||
cur = klines[i]
|
||
prev = klines[i - 1]
|
||
tr = max(
|
||
cur["high"] - cur["low"],
|
||
abs(cur["high"] - prev["close"]),
|
||
abs(cur["low"] - prev["close"]),
|
||
)
|
||
trs.append(tr)
|
||
return sum(trs) / len(trs)
|
||
|
||
def is_danger_market(self, klines, price: float) -> bool:
|
||
last = klines[-1]
|
||
body = abs(last["close"] - last["open"]) / last["open"] if last["open"] else 0.0
|
||
if body >= self.cfg.big_body_kill:
|
||
return True
|
||
|
||
a = self.atr(klines, self.cfg.atr_len)
|
||
atr_ratio = (a / price) if price > 0 else 0.0
|
||
if atr_ratio >= self.cfg.atr_ratio_kill:
|
||
return True
|
||
|
||
return False
|
||
|
||
def atr_ratio_baseline(self, klines) -> float:
|
||
"""简化版ATR基准计算"""
|
||
window = min(self.cfg.vol_baseline_window, len(klines) - self.cfg.atr_len - 1)
|
||
if window <= 10: # 数据太少
|
||
logger.warning(f"数据不足计算基准: {len(klines)}根K线")
|
||
return 0.0
|
||
|
||
ratios = []
|
||
|
||
# 简化计算：每隔3根K线计算一个ATR比率（减少计算量）
|
||
step = 3
|
||
for i in range(-window, 0, step):
|
||
if len(klines) + i < self.cfg.atr_len + 1:
|
||
continue
|
||
|
||
# 计算当前位置的ATR
|
||
start_idx = len(klines) + i - self.cfg.atr_len
|
||
end_idx = len(klines) + i
|
||
|
||
if start_idx < 0 or end_idx <= start_idx:
|
||
continue
|
||
|
||
sub_klines = klines[start_idx:end_idx]
|
||
|
||
# 确保有足够数据计算ATR
|
||
if len(sub_klines) >= self.cfg.atr_len + 1:
|
||
a = self.atr(sub_klines, self.cfg.atr_len)
|
||
price = klines[end_idx - 1]["close"]
|
||
|
||
if a > 0 and price > 0:
|
||
ratio = a / price
|
||
if 0.0001 < ratio < 0.01: # 过滤异常值
|
||
ratios.append(ratio)
|
||
|
||
if len(ratios) < 5: # 样本太少
|
||
# 尝试直接使用整个数据计算一个ATR比率
|
||
a = self.atr(klines[-60:], self.cfg.atr_len) # 使用最近60根K线
|
||
price = klines[-1]["close"]
|
||
if a > 0 and price > 0:
|
||
baseline = a / price
|
||
logger.debug(f"使用全量数据计算基准: {baseline * 100:.4f}%")
|
||
return baseline
|
||
else:
|
||
return 0.0
|
||
|
||
# 计算分位数
|
||
ratios.sort()
|
||
idx = min(len(ratios) - 1,
|
||
max(0, int(self.cfg.vol_baseline_quantile * (len(ratios) - 1))))
|
||
baseline = ratios[idx]
|
||
|
||
logger.debug(f"基准计算: 样本数={len(ratios)}, 基准={baseline * 100:.4f}%, "
|
||
f"范围=[{ratios[0] * 100:.4f}%, {ratios[-1] * 100:.4f}%]")
|
||
|
||
return baseline
|
||
|
||
def get_base_ratio_cached(self, klines) -> float:
|
||
"""获取缓存的基准波动率，定期刷新"""
|
||
now = time.time()
|
||
refresh_sec = self.cfg.base_ratio_refresh_sec
|
||
|
||
if (self._base_ratio_cached is None or
|
||
(now - self._base_ratio_ts) >= refresh_sec):
|
||
|
||
# 使用简单版本的基准计算
|
||
baseline = self.atr_ratio_baseline(klines)
|
||
|
||
if baseline > 0.0001: # 大于0.01%才认为是有效值
|
||
self._base_ratio_cached = baseline
|
||
self._base_ratio_ts = now
|
||
logger.info(f"基准波动率更新: {baseline * 100:.4f}%")
|
||
else:
|
||
# 使用基于价格的动态默认值
|
||
current_price = klines[-1]["close"] if klines else 3000
|
||
# ETH价格越高，基准波动率越小（百分比）
|
||
if current_price > 4000:
|
||
default_baseline = 0.0010 # 0.10%
|
||
elif current_price > 3500:
|
||
default_baseline = 0.0012 # 0.12%
|
||
elif current_price > 3000:
|
||
default_baseline = 0.0015 # 0.15%
|
||
elif current_price > 2500:
|
||
default_baseline = 0.0018 # 0.18%
|
||
else:
|
||
default_baseline = 0.0020 # 0.20%
|
||
|
||
self._base_ratio_cached = default_baseline
|
||
self._base_ratio_ts = now
|
||
logger.warning(f"使用价格动态默认基准: {default_baseline * 100:.4f}% "
|
||
f"(价格=${current_price:.0f})")
|
||
|
||
return self._base_ratio_cached
|
||
|
||
@staticmethod
|
||
def _clamp(x: float, lo: float, hi: float) -> float:
|
||
"""限制数值在指定范围内"""
|
||
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)
|
||
"""
|
||
# 1) 检查输入有效性
|
||
if atr_ratio <= 0:
|
||
logger.warning(f"ATR比率异常: {atr_ratio}")
|
||
atr_ratio = 0.001 # 默认值 0.1%
|
||
|
||
# 2) 如果base_ratio太小或无效，使用调整后的atr_ratio
|
||
if base_ratio < 0.0005: # 小于0.05%视为无效
|
||
base_ratio = max(0.001, atr_ratio * 1.2) # 比当前ATR比率稍大
|
||
logger.debug(f"基准太小，使用调整后的atr_ratio: {base_ratio * 100:.4f}%")
|
||
|
||
# 3) vol_scale计算
|
||
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(f"基准无效，使用默认vol_scale=1.0")
|
||
|
||
# 4) 动态floor计算
|
||
# Entry floor
|
||
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
|
||
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
|
||
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,
|
||
)
|
||
|
||
# 5) 最终阈值计算
|
||
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)
|
||
|
||
# 6) 确保entry_dev不会太小
|
||
entry_dev = max(entry_dev, self.cfg.entry_dev_floor_min)
|
||
|
||
# 7) 输出详细信息
|
||
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"""
|
||
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"""
|
||
return (time.time() - self.last_exit_ts) < self.cfg.cooldown_sec_after_exit
|
||
|
||
def maybe_enter(self, price: float, ema_value: float, entry_dev: float):
|
||
"""检查并执行入场"""
|
||
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: 入场阈值从 {long_th * 100:.3f}% 调整为 {(-entry_dev * self.cfg.reentry_penalty_mult) * 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: 入场阈值从 {short_th * 100:.3f}% 调整为 {(entry_dev * self.cfg.reentry_penalty_mult) * 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"size={size}, penalty={penalty_active}, last_sl_dir={self.last_sl_dir}"
|
||
)
|
||
|
||
if dev <= long_th:
|
||
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.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
|
||
)
|
||
|
||
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):
|
||
"""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)】\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"🎯 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) < (self.cfg.ema_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
|
||
)
|
||
|
||
# 记录调试信息
|
||
logger.debug(
|
||
f"循环数据: price={price:.2f}, ema={ema_value:.2f}, dev={dev * 100:.3f}%, "
|
||
f"atr_ratio={atr_ratio * 100:.3f}%, base_ratio={base_ratio * 100:.3f}%, "
|
||
f"entry_dev={entry_dev * 100:.3f}%"
|
||
)
|
||
|
||
# 5. 风控检查
|
||
self.risk_kill_switch()
|
||
|
||
# 6. 获取持仓状态
|
||
if not self.get_position_status():
|
||
time.sleep(1)
|
||
continue
|
||
|
||
# 7. 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
|
||
|
||
# 8. 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
|
||
|
||
# 9. 执行交易逻辑
|
||
self.maybe_exit(price, tp, sl, vol_scale)
|
||
self.maybe_enter(price, ema_value, entry_dev)
|
||
|
||
# 10. 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
|
||
)
|
||
|
||
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)
|
||
|
||
# 设置日志级别为INFO以便查看详细计算过程
|
||
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
|
||
|
||
# 目前动态计算阀值的速度是多少 |