389 lines
13 KiB
Python
389 lines
13 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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趋势分析模块
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基于均线和ADX判断趋势方向和强度
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"""
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from collections import defaultdict
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from typing import List, Dict, Optional
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from datetime import datetime
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import threading
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from .store import KlineData, normalize_symbol
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class TrendAnalyzer:
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"""趋势分析器"""
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# 支持的周期
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PERIODS = ['H4', 'H1', 'M15', 'M5', 'M1']
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# ADX阈值
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ADX_TREND_THRESHOLD = 25 # ADX > 25 表示有趋势
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ADX_STRONG_THRESHOLD = 40 # ADX > 40 表示强趋势
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# 均线周期
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MA_FAST = 10 # 快线周期
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MA_SLOW = 20 # 慢线周期
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def __init__(self):
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# 存储各周期趋势状态: {SYMBOL: {PERIOD: TrendState}}
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self._trend_states = defaultdict(lambda: defaultdict(dict))
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self._lock = threading.RLock()
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# 趋势转换历史
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self._trend_changes = defaultdict(list)
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print("[TrendAnalyzer] 趋势分析器已初始化")
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def analyze_trend(self, symbol: str, period: str, klines: List[KlineData]) -> Dict:
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"""
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分析单个周期的趋势
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Args:
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symbol: 交易品种
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period: 周期
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klines: K线数据
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Returns:
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{
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"trend": "up" / "down" / "sideways",
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"strength": 0-100,
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"adx": float,
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"ma_fast": float,
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"ma_slow": float,
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"price": float,
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"change_signal": bool, # 是否发生趋势转换
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"timestamp": str
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}
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"""
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if len(klines) < 30: # 至少需要30根K线
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return {
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"trend": "unknown",
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"strength": 0,
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"adx": 0,
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"ma_fast": 0,
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"ma_slow": 0,
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"price": 0,
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"change_signal": False,
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"reason": "K线数据不足(需≥30根)",
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"timestamp": datetime.now().isoformat()
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}
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# 计算均线
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closes = [k.close for k in klines]
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ma_fast = self._calculate_ma(closes, self.MA_FAST)
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ma_slow = self._calculate_ma(closes, self.MA_SLOW)
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current_price = closes[-1]
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# 计算ADX
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adx = self._calculate_adx(klines)
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# 判断趋势方向和原因
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reason_parts = []
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if adx < self.ADX_TREND_THRESHOLD:
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# ADX较低，震荡行情
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trend = "sideways"
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reason_parts.append(f"ADX={adx:.1f}<25 无明显趋势")
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else:
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# 根据均线和价格判断方向
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if ma_fast > ma_slow and current_price > ma_fast:
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trend = "up"
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reason_parts.append(f"MA{self.MA_FAST}({ma_fast:.2f}) > MA{self.MA_SLOW}({ma_slow:.2f})")
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reason_parts.append(f"价格({current_price:.2f}) > MA{self.MA_FAST}")
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reason_parts.append(f"ADX={adx:.1f}≥25 确认趋势")
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elif ma_fast < ma_slow and current_price < ma_fast:
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trend = "down"
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reason_parts.append(f"MA{self.MA_FAST}({ma_fast:.2f}) < MA{self.MA_SLOW}({ma_slow:.2f})")
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reason_parts.append(f"价格({current_price:.2f}) < MA{self.MA_FAST}")
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reason_parts.append(f"ADX={adx:.1f}≥25 确认趋势")
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else:
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trend = "sideways"
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if ma_fast > ma_slow:
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reason_parts.append(f"MA{self.MA_FAST}({ma_fast:.2f}) > MA{self.MA_SLOW}({ma_slow:.2f})")
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reason_parts.append(f"但价格({current_price:.2f})低于MA{self.MA_FAST}")
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else:
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reason_parts.append(f"MA{self.MA_FAST}({ma_fast:.2f}) < MA{self.MA_SLOW}({ma_slow:.2f})")
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reason_parts.append(f"且价格({current_price:.2f})高于MA{self.MA_FAST}")
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reason_parts.append("信号矛盾，判定震荡")
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reason = "；".join(reason_parts)
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# 计算趋势强度 (基于ADX)
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if adx >= self.ADX_STRONG_THRESHOLD:
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strength = min(100, int(adx + 20))
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elif adx >= self.ADX_TREND_THRESHOLD:
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strength = int(adx + 10)
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else:
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strength = int(adx)
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# 检查趋势转换
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symbol_key = normalize_symbol(symbol)
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change_signal = False
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previous_trend = None
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with self._lock:
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if period in self._trend_states[symbol_key]:
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previous_trend = self._trend_states[symbol_key][period].get('trend')
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if previous_trend and previous_trend != trend and previous_trend != "unknown":
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change_signal = True
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# 记录转换历史
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self._trend_changes[symbol_key].append({
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"period": period,
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"from_trend": previous_trend,
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"to_trend": trend,
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"timestamp": datetime.now().isoformat(),
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"price": current_price
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})
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# 只保留最近20条
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if len(self._trend_changes[symbol_key]) > 20:
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self._trend_changes[symbol_key] = self._trend_changes[symbol_key][-20:]
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# 更新状态
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self._trend_states[symbol_key][period] = {
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"trend": trend,
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"strength": strength,
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"adx": round(adx, 2),
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"ma_fast": round(ma_fast, 4),
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"ma_slow": round(ma_slow, 4),
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"price": current_price,
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"change_signal": change_signal,
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"previous_trend": previous_trend,
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"reason": reason,
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"timestamp": datetime.now().isoformat()
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}
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return self._trend_states[symbol_key][period]
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def analyze_resonance(self, symbol: str) -> Dict:
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"""
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分析多周期共振
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Returns:
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{
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"resonance": "up" / "down" / "none",
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"strength": 0-100,
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"periods": {period: trend_state},
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"aligned_count": int,
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"signal": str
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}
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"""
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symbol_key = normalize_symbol(symbol)
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with self._lock:
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states = dict(self._trend_states[symbol_key])
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if not states:
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return {
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"resonance": "none",
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"strength": 0,
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"periods": {},
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"aligned_count": 0,
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"signal": "等待数据"
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}
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# 统计各趋势数量
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up_count = sum(1 for s in states.values() if s.get('trend') == 'up')
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down_count = sum(1 for s in states.values() if s.get('trend') == 'down')
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sideways_count = sum(1 for s in states.values() if s.get('trend') == 'sideways')
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# 计算平均强度
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strengths = [s.get('strength', 0) for s in states.values() if s.get('trend') != 'sideways']
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avg_strength = sum(strengths) / len(strengths) if strengths else 0
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# 判断共振
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total = len(states)
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if up_count >= total * 0.6: # 60%以上周期趋势一致
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resonance = "up"
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aligned_count = up_count
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signal = f"多周期向上共振 ({up_count}/{total})"
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elif down_count >= total * 0.6:
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resonance = "down"
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aligned_count = down_count
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signal = f"多周期向下共振 ({down_count}/{total})"
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else:
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resonance = "none"
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aligned_count = max(up_count, down_count)
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signal = f"趋势分歧 (↑{up_count} ↓{down_count} →{sideways_count})"
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return {
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"resonance": resonance,
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"strength": int(avg_strength),
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"periods": states,
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"aligned_count": aligned_count,
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"up_count": up_count,
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"down_count": down_count,
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"sideways_count": sideways_count,
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"signal": signal
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}
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def get_trend_state(self, symbol: str, period: str = None) -> Dict:
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"""获取趋势状态"""
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symbol_key = normalize_symbol(symbol)
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with self._lock:
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if period:
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return self._trend_states[symbol_key].get(period, {})
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return dict(self._trend_states[symbol_key])
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def get_trend_changes(self, symbol: str, count: int = 10) -> List[Dict]:
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"""获取趋势转换历史"""
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symbol_key = normalize_symbol(symbol)
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with self._lock:
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return self._trend_changes[symbol_key][-count:]
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def _calculate_ma(self, data: List[float], period: int) -> float:
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"""计算移动平均线"""
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if len(data) < period:
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return data[-1] if data else 0
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return sum(data[-period:]) / period
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def _calculate_adx(self, klines: List[KlineData], period: int = 14) -> float:
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"""
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计算ADX (Average Directional Index)
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ADX > 25: 有趋势
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ADX > 40: 强趋势
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ADX < 20: 无明显趋势
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"""
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if len(klines) < period + 1:
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return 0
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# 计算 +DM 和 -DM
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plus_dm = []
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minus_dm = []
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tr_list = []
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for i in range(1, len(klines)):
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high = klines[i].high
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low = klines[i].low
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prev_high = klines[i-1].high
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prev_low = klines[i-1].low
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prev_close = klines[i-1].close
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# +DM
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up_move = high - prev_high
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down_move = prev_low - low
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if up_move > down_move and up_move > 0:
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plus_dm.append(up_move)
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else:
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plus_dm.append(0)
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# -DM
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if down_move > up_move and down_move > 0:
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minus_dm.append(down_move)
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else:
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minus_dm.append(0)
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# True Range
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tr = max(
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high - low,
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abs(high - prev_close),
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abs(low - prev_close)
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)
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tr_list.append(tr)
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if len(tr_list) < period:
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return 0
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# 计算平滑值
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atr = sum(tr_list[-period:]) / period
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smoothed_plus_dm = sum(plus_dm[-period:]) / period
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smoothed_minus_dm = sum(minus_dm[-period:]) / period
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# 计算 +DI 和 -DI
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if atr == 0:
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return 0
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plus_di = (smoothed_plus_dm / atr) * 100
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minus_di = (smoothed_minus_dm / atr) * 100
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# 计算 DX
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di_sum = plus_di + minus_di
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if di_sum == 0:
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return 0
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dx = abs(plus_di - minus_di) / di_sum * 100
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return dx
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def generate_trade_suggestion(self, symbol: str, pivots: List[Dict],
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current_price: float) -> Optional[Dict]:
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"""
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基于趋势和转折点生成交易建议
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Args:
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symbol: 交易品种
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pivots: 转折点数据
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current_price: 当前价格
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Returns:
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交易建议 或 None
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"""
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symbol_key = normalize_symbol(symbol)
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# 获取趋势状态
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resonance = self.analyze_resonance(symbol)
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if resonance['resonance'] == 'none':
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return None
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if resonance['strength'] < 30:
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return None
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trend = resonance['resonance']
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# 根据趋势找最近的转折点作为止损止盈
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recent_pivots = sorted(pivots, key=lambda x: x['timestamp'], reverse=True)[:10]
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sl = None
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|||
|
|
tp = None
|
|||
|
|
action = None
|
|||
|
|
reason = ""
|
|||
|
|
|
|||
|
|
if trend == "up":
|
|||
|
|
# 上升趋势，找最近的低点作为止损
|
|||
|
|
action = "b"
|
|||
|
|
low_pivots = [p for p in recent_pivots if p['direction'] == 'low']
|
|||
|
|
if low_pivots:
|
|||
|
|
# 找最近的低点作为止损
|
|||
|
|
sl = low_pivots[0]['price']
|
|||
|
|
# 止盈设为止损的1.5-2倍距离
|
|||
|
|
if sl and current_price > sl:
|
|||
|
|
distance = current_price - sl
|
|||
|
|
tp = current_price + distance * 1.5
|
|||
|
|
reason = f"多周期向上共振，建议买入，止损参考最近低点 {sl}"
|
|||
|
|
else:
|
|||
|
|
return None
|
|||
|
|
|
|||
|
|
elif trend == "down":
|
|||
|
|
# 下降趋势，找最近的高点作为止损
|
|||
|
|
action = "s"
|
|||
|
|
high_pivots = [p for p in recent_pivots if p['direction'] == 'high']
|
|||
|
|
if high_pivots:
|
|||
|
|
sl = high_pivots[0]['price']
|
|||
|
|
if sl and current_price < sl:
|
|||
|
|
distance = sl - current_price
|
|||
|
|
tp = current_price - distance * 1.5
|
|||
|
|
reason = f"多周期向下共振，建议卖出，止损参考最近高点 {sl}"
|
|||
|
|
else:
|
|||
|
|
return None
|
|||
|
|
|
|||
|
|
if not all([action, sl, tp]):
|
|||
|
|
return None
|
|||
|
|
|
|||
|
|
return {
|
|||
|
|
"symbol": symbol_key,
|
|||
|
|
"action": action,
|
|||
|
|
"price": current_price,
|
|||
|
|
"sl": round(sl, 4),
|
|||
|
|
"tp": round(tp, 4),
|
|||
|
|
"reason": reason,
|
|||
|
|
"trend_strength": resonance['strength'],
|
|||
|
|
"resonance_periods": resonance['aligned_count'],
|
|||
|
|
"generated_at": datetime.now().isoformat()
|
|||
|
|
}
|