feat(engine): 添加策略示例集（18 个 Demo）
- backtest_demo.py: 回测基础演示 - strategy_simple.py / three_ema.py / long_short.py: 基础策略（双均线/三均线/多空） - strategy_optimize*.py (3 版本): 参数优化示例（网格搜索/贝叶斯/遗传算法） - multi_tf_*.py (4 版本): 多时间框架策略（EMA200/多周期共振/混合信号） - regime_*.py (4 版本): 市场状态检测（趋势/震荡/波动率区间/全状态） - cross_section.py: 截面多品种策略 - factor_demo.py: 多因子模型演示 - strategy_battle.py / strategy_more.py: 策略对比与组合 - full_cycle.py: 全流程演示（数据→回测→分析） - data.py: 数据读取示例
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"""
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多周期策略回测 — 4h 定趋势，30m 找买点
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策略逻辑：
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1. 4h EMA20 判断大趋势：价格 > EMA20 = 上升趋势
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2. 30m RSI 寻找入场时机：上升趋势中 RSI < 35 = 回调买入
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3. 出场：RSI > 70（超买）或 4h 趋势反转向下
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用法：
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source .venv/bin/activate && python example/multi_tf_demo.py
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"""
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import asyncio
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import sys
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Optional
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_project_root = Path(__file__).resolve().parent.parent.parent
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if str(_project_root) not in sys.path:
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sys.path.insert(0, str(_project_root))
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from engine.common.base import BaseStrategy, Signal, StrategyConfig
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from engine.common.models import Kline
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from engine.common.config import config, DBConfig
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from engine.backtest import BacktestEngine, BacktestConfig
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from engine.data import DataService
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from engine.indicators import ema, rsi
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# ============================================================
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# 多周期趋势回调策略
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# ============================================================
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class MultiTFConfig(StrategyConfig):
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"""多周期策略配置"""
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# 4h 趋势参数
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trend_ema_period: int = 20
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# 30m 入场参数
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entry_rsi_period: int = 14
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entry_rsi_threshold: float = 35.0 # RSI 低于此值视为回调
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# 出场参数
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exit_rsi_threshold: float = 70.0 # RSI 高于此值出场
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# 数据范围（用于预加载 4h 数据）
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data_start: Optional[datetime] = None
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data_end: Optional[datetime] = None
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class MultiTimeframeStrategy(BaseStrategy):
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"""多周期趋势回调策略
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┌─────────────────────────────┐
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│ 4h K 线 → EMA20 判断趋势 │
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│ Price > EMA20 = 上升趋势 │
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└─────────────┬───────────────┘
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│ 上升趋势
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▼
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┌─────────────────────────────┐
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│ 30m K 线 → 寻找入场时机 │
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│ RSI < 35 = 回调买入 │
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└─────────────┬───────────────┘
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│ 持仓中
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▼
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┌─────────────────────────────┐
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│ 出场条件 │
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│ RSI > 70 或 4h 趋势反转 │
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└─────────────────────────────┘
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"""
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strategy_type = "multi_tf"
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def __init__(self, config: MultiTFConfig):
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super().__init__(config)
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self.cfg: MultiTFConfig = config
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# 4h 数据（在 on_start 中加载）
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self._klines_4h: list[Kline] = []
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self._ema_4h: list[float] = []
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# 30m 数据积累
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self._closes_30m: list[float] = []
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# 持仓状态
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self._has_position: bool = False
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async def on_start(self) -> None:
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"""预加载 4h K 线数据并计算 EMA"""
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from engine.common.config import config as app_config
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ds = DataService(app_config.db)
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await ds.connect()
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try:
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self._klines_4h = await ds.fetch_klines(
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symbol=self.cfg.symbol,
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interval="4h",
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start_time=self.cfg.data_start,
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end_time=self.cfg.data_end,
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limit=1_000_000,
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)
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closes_4h = [k.close for k in self._klines_4h]
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self._ema_4h = ema(closes_4h, self.cfg.trend_ema_period)
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finally:
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await ds.close()
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await super().on_start()
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def _get_4h_trend(self, ts: float) -> tuple[bool, float, float]:
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"""获取指定时间戳对应的 4h 趋势
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只使用已完成的 4h K 线（close_time <= ts），避免前视偏差。
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Returns:
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(is_uptrend, price, ema_value)
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"""
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if not self._klines_4h:
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return False, 0.0, 0.0
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# 从后往前找最近已完成的 4h bar
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for i in range(len(self._klines_4h) - 1, -1, -1):
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if self._klines_4h[i].close_time <= ts:
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price = self._klines_4h[i].close
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ema_val = self._ema_4h[i]
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if ema_val == 0.0:
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return False, price, ema_val
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return price > ema_val, price, ema_val
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return False, 0.0, 0.0
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async def on_kline(self, kline: Kline) -> Optional[Signal]:
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self._closes_30m.append(kline.close)
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# ── 获取 4h 趋势 ──
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is_uptrend, price_4h, ema_4h = self._get_4h_trend(kline.open_time)
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# ── 计算 30m RSI ──
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rsi_vals = rsi(self._closes_30m, self.cfg.entry_rsi_period)
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cur_rsi = rsi_vals[-1]
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if cur_rsi == 0.0:
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return None
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# ── 出场逻辑 ──
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if self._has_position:
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# 4h 趋势反转（价格跌破 EMA）→ 止损出场
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if not is_uptrend and price_4h > 0:
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self._has_position = False
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return Signal(
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symbol=self.cfg.symbol,
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side="SELL",
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signal_type="MARKET",
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confidence=0.9,
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reason=f"4h趋势反转 Price={price_4h:.2f}<EMA={ema_4h:.2f}",
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timestamp=kline.open_time,
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)
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# 30m RSI 过热 → 止盈出场
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if cur_rsi > self.cfg.exit_rsi_threshold:
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self._has_position = False
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return Signal(
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symbol=self.cfg.symbol,
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side="SELL",
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signal_type="MARKET",
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confidence=0.8,
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reason=f"30m RSI过热 {cur_rsi:.1f}>{self.cfg.exit_rsi_threshold}",
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timestamp=kline.open_time,
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)
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# ── 入场逻辑 ──
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if not self._has_position:
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# 条件1：4h 上升趋势
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if not is_uptrend:
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return None
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# 条件2：30m RSI 回调到超卖区
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if cur_rsi < self.cfg.entry_rsi_threshold:
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self._has_position = True
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return Signal(
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symbol=self.cfg.symbol,
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side="BUY",
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signal_type="MARKET",
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confidence=0.7,
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reason=(
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f"4h升势回调买入 | "
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f"4hPrice={price_4h:.0f}>EMA={ema_4h:.0f} | "
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f"30mRSI={cur_rsi:.1f}"
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),
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timestamp=kline.open_time,
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)
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return None
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# ============================================================
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# 主函数
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# ============================================================
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async def main():
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bt_config = BacktestConfig(
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symbol="ETHUSDT",
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interval="30m",
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start_time=datetime(2024, 1, 1),
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end_time=datetime(2026, 1, 1),
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initial_capital=10_000.0,
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commission_pct=0.001,
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slippage_pct=0.0005,
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warmup_bars=100,
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)
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strategy_config = MultiTFConfig(
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name="multi_tf_eth",
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symbol="ETHUSDT",
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trend_ema_period=20,
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entry_rsi_period=14,
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entry_rsi_threshold=35.0,
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exit_rsi_threshold=70.0,
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data_start=bt_config.start_time,
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data_end=bt_config.end_time,
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)
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print()
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print("╔" + "═" * 60 + "╗")
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print("║" + " 多周期策略 — 4h 定趋势 / 30m 找买点".center(54) + "║")
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print("╠" + "═" * 60 + "╣")
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print(f"║ {'交易对:':<8} {bt_config.symbol:<14} {'周期:':<6} {bt_config.interval:<12} ║")
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print(f"║ {'时间:':<8} {bt_config.start_time.date()} ~ {bt_config.end_time.date()} ║")
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print("╠" + "═" * 60 + "╣")
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print("║ 策略逻辑: ║")
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print(f"║ 4h EMA{strategy_config.trend_ema_period} → 判断趋势方向 ║")
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print(f"║ 30m RSI{strategy_config.entry_rsi_period} < {strategy_config.entry_rsi_threshold} → 回调买入 ║")
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print(f"║ 30m RSI{strategy_config.entry_rsi_period} > {strategy_config.exit_rsi_threshold} → 止盈 / 4h趋势反转 → 止损 ║")
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print("╚" + "═" * 60 + "╝")
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print()
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engine = BacktestEngine(bt_config, db_config=config.db)
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result = await engine.run(MultiTimeframeStrategy, strategy_config)
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print(result.summary())
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# 打印最近交易
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sells = [t for t in result.trades if t.pnl is not None]
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if sells:
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print(f"\n最近 10 笔平仓交易:")
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print(f"{'时间':<22} {'方向':<6} {'价格':>10} {'盈亏':>10} 原因")
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print("-" * 85)
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for t in sells[-10:]:
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dt = datetime.fromtimestamp(t.timestamp / 1000, tz=timezone.utc).strftime("%Y-%m-%d %H:%M")
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print(f"{dt:<22} {t.side:<6} {t.price:>10.2f} {t.pnl:>+10.2f} {t.reason}")
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print("\n回测完成。")
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if __name__ == "__main__":
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asyncio.run(main())
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