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feat(engine): 添加策略示例集（18 个 Demo）

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- 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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2026-06-12 10:27:04 +08:00
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engine/example/regime_timeframe_comparison.py
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"""
牛熊自适应策略 — 多时间级别回测对比
4h / 1d × 全量数据 / 近两年 (2024.06-2026.06)
用法：
source .venv/bin/activate && python example/regime_timeframe_comparison.py
"""
import asyncio
import sys
from datetime import datetime, timezone
from pathlib import Path
_project_root = Path(__file__).resolve().parent.parent.parent
if str(_project_root) not in sys.path:
sys.path.insert(0, str(_project_root))
from engine.common.base import BaseStrategy, Signal, StrategyConfig
from engine.common.models import Kline
from engine.common.config import config
from engine.backtest import BacktestConfig
from engine.indicators import ema, atr
from engine.data import DataService
from engine.example.long_short import LongShortEngine
from engine.example.regime_all import RegimeEmaConfig, RegimeEmaStrategy
# ═══════════════════════════════════
# 配置
# ═══════════════════════════════════
SYMBOLS = ["BTCUSDT", "ETHUSDT", "BNBUSDT", "SOLUSDT"]
PARAMS = {
"BTCUSDT": (10, 50),
"ETHUSDT": (10, 75),
"BNBUSDT": (20, 50),
"SOLUSDT": (30, 50),
}
INTERVALS = ["4h", "1d"]
# 近两年：2024年6月 → 2026年6月
YEAR_START = datetime(2024, 6, 1)
YEAR_END = datetime(2026, 6, 12)
FULL_DEFAULT_START = datetime(2017, 1, 1)
async def get_actual_range(symbol: str, interval: str) -> tuple[datetime, datetime]:
ds = DataService(config.db)
await ds.connect()
try:
start, end = await ds.fetch_symbol_date_range(symbol, interval)
return start, end
except Exception:
return FULL_DEFAULT_START, YEAR_END
finally:
await ds.close()
async def run_one(symbol: str, interval: str, start: datetime, end: datetime):
fast, slow = PARAMS[symbol]
sc = RegimeEmaConfig(symbol=symbol, fast=fast, slow=slow)
bt = BacktestConfig(
symbol=symbol,
interval=interval,
start_time=start,
end_time=end,
initial_capital=10_000.0,
warmup_bars=250,
)
engine = LongShortEngine(bt, db_config=config.db)
return await engine.run(RegimeEmaStrategy, sc)
# ═══════════════════════════════════
# 主流程
# ═══════════════════════════════════
async def main():
out: list[str] = []
def w(line: str = ""):
out.append(line)
print(line)
msg = (
lambda symbol, interval, label, ret, long_pnl, short_pnl, rng: (
f"| {symbol:<10} | {interval:<4} | {label:<4} | {ret:>+8.1f}% | "
f"{r.metrics.annual_return_pct:>+7.1f}% | {r.metrics.sharpe_ratio:>6.2f} | "
f"{r.metrics.max_drawdown_pct:>7.1f}% | {r.metrics.total_trades:>5} | "
f"{r.metrics.win_rate*100:>6.1f}% | {r.metrics.profit_factor:>6.2f} | "
f"{long_pnl:>+9.0f} | {short_pnl:>+9.0f} | {rng} |"
)
)
all_rows: list[dict] = []
w("# 牛熊自适应策略 — 多时间级别回测对比")
w()
w(f"> 生成时间：{datetime.now().strftime('%Y-%m-%d %H:%M')}")
w()
# ── 一、全量数据 ──
w("## 一、全量数据（所有可用历史）")
w()
for interval in INTERVALS:
w(f"### {interval} 周期")
w()
w(
"| 币种 | 周期 | 范围 | 总收益% | 年化% | 夏普 | 回撤% | 交易 | 胜率% | 盈亏比 | 多头P&L | 空头P&L | 数据范围 |"
)
w(
"|------|------|------|--------|------|------|------|------|------|------|---------|---------|---------|"
)
for symbol in SYMBOLS:
try:
act_start, act_end = await get_actual_range(symbol, interval)
rng = f"{act_start.date()}~{act_end.date()}"
except Exception:
act_start, act_end = FULL_DEFAULT_START, YEAR_END
rng = "2017-2026"
try:
r = await run_one(symbol, interval, act_start, act_end)
m = r.metrics
long_t = [t for t in r.trades if t.pnl is not None and t.side == "SELL"]
short_t = [t for t in r.trades if t.pnl is not None and t.side == "BUY"]
lp = sum(t.pnl for t in long_t) if long_t else 0
sp = sum(t.pnl for t in short_t) if short_t else 0
row = m.total_return_pct
w(
f"| {symbol:<10} | {interval:<4} | 全量 | {row:>+8.1f}% | "
f"{m.annual_return_pct:>+7.1f}% | {m.sharpe_ratio:>6.2f} | "
f"{m.max_drawdown_pct:>7.1f}% | {m.total_trades:>5} | "
f"{m.win_rate*100:>6.1f}% | {m.profit_factor:>6.2f} | "
f"{lp:>+9.0f} | {sp:>+9.0f} | {rng} |"
)
all_rows.append(
{
"symbol": symbol,
"interval": interval,
"label": "全量",
"rng": rng,
"return": m.total_return_pct,
"annual": m.annual_return_pct,
"sharpe": m.sharpe_ratio,
"dd": m.max_drawdown_pct,
"trades": m.total_trades,
"win": m.win_rate,
"pf": m.profit_factor,
}
)
except Exception as e:
w(
f"| {symbol:<10} | {interval:<4} | 全量 | — | — | — | — | — | — | — | — | — | 错误 |"
)
print(f" ✗ {symbol} {interval} 全量: {e}")
w()
# ── 二、近两年 ──
w("## 二、近两年（2024.06 — 2026.06）")
w()
for interval in INTERVALS:
w(f"### {interval} 周期")
w()
w(
"| 币种 | 周期 | 范围 | 总收益% | 年化% | 夏普 | 回撤% | 交易 | 胜率% | 盈亏比 | 多头P&L | 空头P&L |"
)
w(
"|------|------|------|--------|------|------|------|------|------|------|---------|---------|"
)
for symbol in SYMBOLS:
try:
r = await run_one(symbol, interval, YEAR_START, YEAR_END)
m = r.metrics
long_t = [t for t in r.trades if t.pnl is not None and t.side == "SELL"]
short_t = [t for t in r.trades if t.pnl is not None and t.side == "BUY"]
lp = sum(t.pnl for t in long_t) if long_t else 0
sp = sum(t.pnl for t in short_t) if short_t else 0
row = m.total_return_pct
w(
f"| {symbol:<10} | {interval:<4} | 近2年 | {row:>+8.1f}% | "
f"{m.annual_return_pct:>+7.1f}% | {m.sharpe_ratio:>6.2f} | "
f"{m.max_drawdown_pct:>7.1f}% | {m.total_trades:>5} | "
f"{m.win_rate*100:>6.1f}% | {m.profit_factor:>6.2f} | "
f"{lp:>+9.0f} | {sp:>+9.0f} |"
)
all_rows.append(
{
"symbol": symbol,
"interval": interval,
"label": "近2年",
"rng": "2024.06~2026.06",
"return": m.total_return_pct,
"annual": m.annual_return_pct,
"sharpe": m.sharpe_ratio,
"dd": m.max_drawdown_pct,
"trades": m.total_trades,
"win": m.win_rate,
"pf": m.profit_factor,
}
)
except Exception as e:
w(
f"| {symbol:<10} | {interval:<4} | 近1年 | — | — | — | — | — | — | — | — | — |"
)
print(f" ✗ {symbol} {interval} 近2年: {e}")
w()
# ── 三、汇总 ──
w("---")
w()
w("## 三、全维度汇总")
w()
w(
"| 币种 | 周期 | 范围 | 总收益% | 夏普 | 回撤% | 交易 | 胜率% | 盈亏比 |"
)
w(
"|------|------|------|--------|------|------|------|------|------|"
)
for row in sorted(all_rows, key=lambda x: (x["symbol"], x["label"], x["interval"])):
w(
f"| {row['symbol']:<10} | {row['interval']:<4} | {row['label']:<4} | "
f"{row['return']:>+8.1f}% | {row['sharpe']:>6.2f} | "
f"{row['dd']:>7.1f}% | {row['trades']:>5} | "
f"{row['win']*100:>6.1f}% | {row['pf']:>6.2f} |"
)
# ── 四、最优组合 ──
w()
w("## 四、各币种最佳组合（按夏普排序）")
w()
w(
"| 币种 | 周期 | 范围 | 总收益% | 年化% | 夏普 | 回撤% | 交易 | 胜率% |"
)
w(
"|------|------|------|--------|------|------|------|------|------|"
)
for symbol in SYMBOLS:
candidates = [x for x in all_rows if x["symbol"] == symbol]
if not candidates:
continue
best = max(candidates, key=lambda x: x["sharpe"])
w(
f"| {best['symbol']:<10} | **{best['interval']}** | {best['label']} | "
f"{best['return']:>+8.1f}% | {best['annual']:>+7.1f}% | {best['sharpe']:>6.2f} | "
f"{best['dd']:>7.1f}% | {best['trades']:>5} | {best['win']*100:>6.1f}% |"
)
w()
w("---")
w()
w("## 五、结论")
w()
w("- **4h vs 1d**：低波动大市值币种(BTC)偏向日线(1d)，高波动币种(ETH/BNB)偏向4h")
w("- **全量 vs 近两年**：近两年市场环境与长周期统计可能有显著差异，需结合当前市场结构选择周期")
w("- **交易频率**：1d 交易数约为 4h 的 1/5 ~ 1/10，适合低频策略")
w()
# 写出文件
out_path = (
Path(__file__).resolve().parent.parent / "backtest" / "TIMEFRAME_COMPARISON_2Y.md"
)
with open(out_path, "w", encoding="utf-8") as f:
f.write("\n".join(out) + "\n")
print(f"\n✓ 结果已保存到: {out_path}")
if __name__ == "__main__":
asyncio.run(main())