clean(rotation): add simple rotation strategy and remove unused files
New: - rotation/simple_rotation.py: daily-iteration rotation strategy (584 lines) - rotation/config_loader.py: standalone config loader - rotation/config_simple.yaml: 11 assets, 7 groups - rotation/README_SIMPLE.md: usage guide - scripts/get_trading_calendar.py: trading calendar fetcher Removed: - rotation/example_usage.py, run_strategy.py (replaced by simple_rotation.py) - rotation/results/ output files (gitignored) - scripts/verify_*.py, calculate_returns_from_detail.py (one-off scripts) - scripts/README_TRADING_CALENDAR.md Backtest result (2020-01-10 ~ 2026-06-01): - Total return: 1237.6%, Annual: 52.66% - Max drawdown: -11.71%, Sharpe: 2.50
This commit is contained in:
@@ -121,13 +121,13 @@ def run_strategy(config_path: str = "strategies/rotation/config.yaml") -> dict:
|
||||
|
||||
logger.info(f"执行命令: {' '.join(cmd)}")
|
||||
|
||||
# 执行策略
|
||||
# 执行策略（增加超时到15分钟，因为需要获取多市场数据）
|
||||
result = subprocess.run(
|
||||
cmd,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
cwd=project_root,
|
||||
timeout=300 # 5分钟超时
|
||||
timeout=900 # 15分钟超时（原5分钟不够，数据获取串行需要更长时间）
|
||||
)
|
||||
|
||||
if result.returncode != 0:
|
||||
|
||||
348
scripts/get_trading_calendar.py
Normal file
348
scripts/get_trading_calendar.py
Normal file
@@ -0,0 +1,348 @@
|
||||
"""
|
||||
获取 A 股交易日历脚本
|
||||
|
||||
使用 Flask API 交易日历服务获取 A 股交易日历
|
||||
支持多市场、多年份的交易日查询
|
||||
|
||||
用法:
|
||||
python scripts/get_trading_calendar.py
|
||||
python scripts/get_trading_calendar.py --year 2024
|
||||
python scripts/get_trading_calendar.py --start 2024-01-01 --end 2024-12-31
|
||||
"""
|
||||
|
||||
import sys
|
||||
import argparse
|
||||
from pathlib import Path
|
||||
from datetime import datetime, timedelta
|
||||
import pandas as pd
|
||||
|
||||
# 添加项目根目录到路径
|
||||
project_root = Path(__file__).parent.parent
|
||||
if str(project_root) not in sys.path:
|
||||
sys.path.insert(0, str(project_root))
|
||||
|
||||
# 加载环境变量
|
||||
from dotenv import load_dotenv
|
||||
load_dotenv()
|
||||
|
||||
# 导入 Flask API 数据源
|
||||
from datasource.flask_api_source import FlaskAPIDataSource
|
||||
|
||||
|
||||
def get_calendar_for_year(source: FlaskAPIDataSource, year: int, market: str = 'A'):
|
||||
"""
|
||||
获取指定年份的交易日历
|
||||
|
||||
Args:
|
||||
source: Flask API 数据源实例
|
||||
year: 年份（如 2024）
|
||||
market: 市场代码（'A', 'US', 'HK'）
|
||||
|
||||
Returns:
|
||||
pd.DatetimeIndex: 交易日序列
|
||||
"""
|
||||
start_date = f"{year}-01-01"
|
||||
end_date = f"{year}-12-31"
|
||||
|
||||
print(f"\n获取 {year} 年 {market} 市场交易日历...")
|
||||
|
||||
trading_dates = source.get_trading_calendar(
|
||||
market=market,
|
||||
start_date=start_date,
|
||||
end_date=end_date
|
||||
)
|
||||
|
||||
if trading_dates is None or len(trading_dates) == 0:
|
||||
print(f"✗ {year} 年 {market} 市场无交易日数据")
|
||||
return None
|
||||
|
||||
return trading_dates
|
||||
|
||||
|
||||
def analyze_calendar(trading_dates: pd.DatetimeIndex, year: int):
|
||||
"""
|
||||
分析交易日历统计信息
|
||||
|
||||
Args:
|
||||
trading_dates: 交易日序列
|
||||
year: 年份
|
||||
"""
|
||||
if trading_dates is None or len(trading_dates) == 0:
|
||||
return
|
||||
|
||||
print(f"\n{'=' * 60}")
|
||||
print(f"{year} 年 A 股交易日历分析")
|
||||
print(f"{'=' * 60}")
|
||||
|
||||
# 基本统计
|
||||
total_days = len(trading_dates)
|
||||
print(f"\n基本统计:")
|
||||
print(f" 总交易日: {total_days} 天")
|
||||
print(f" 起始日期: {trading_dates.min().strftime('%Y-%m-%d')}")
|
||||
print(f" 结束日期: {trading_dates.max().strftime('%Y-%m-%d')}")
|
||||
|
||||
# 按月份统计
|
||||
print(f"\n按月份统计:")
|
||||
monthly_counts = {}
|
||||
for date in trading_dates:
|
||||
month = date.month
|
||||
monthly_counts[month] = monthly_counts.get(month, 0) + 1
|
||||
|
||||
for month in range(1, 13):
|
||||
count = monthly_counts.get(month, 0)
|
||||
month_name = datetime(2024, month, 1).strftime('%B')
|
||||
print(f" {month:02d}月 ({month_name}): {count} 天")
|
||||
|
||||
# 按季度统计
|
||||
print(f"\n按季度统计:")
|
||||
quarterly_counts = {1: 0, 2: 0, 3: 0, 4: 0}
|
||||
for date in trading_dates:
|
||||
quarter = (date.month - 1) // 3 + 1
|
||||
quarterly_counts[quarter] += 1
|
||||
|
||||
for quarter, count in quarterly_counts.items():
|
||||
print(f" Q{quarter}: {count} 天")
|
||||
|
||||
# 特殊日期统计
|
||||
print(f"\n特殊日期:")
|
||||
first_date = trading_dates.min()
|
||||
last_date = trading_dates.max()
|
||||
print(f" 首个交易日: {first_date.strftime('%Y-%m-%d')} ({first_date.strftime('%A')})")
|
||||
print(f" 最后交易日: {last_date.strftime('%Y-%m-%d')} ({last_date.strftime('%A')})")
|
||||
|
||||
# 查找节假日后的首个交易日（通过间隔判断）
|
||||
gaps = []
|
||||
for i in range(1, len(trading_dates)):
|
||||
prev_date = trading_dates[i-1]
|
||||
curr_date = trading_dates[i]
|
||||
gap_days = (curr_date - prev_date).days
|
||||
if gap_days > 3: # 超过3天视为可能节假日
|
||||
gaps.append({
|
||||
'prev': prev_date,
|
||||
'curr': curr_date,
|
||||
'gap': gap_days
|
||||
})
|
||||
|
||||
if gaps:
|
||||
print(f"\n可能的节假日（间隔 > 3天）:")
|
||||
for gap_info in gaps[:5]: # 只显示前5个
|
||||
print(f" {gap_info['prev'].strftime('%Y-%m-%d')} → {gap_info['curr'].strftime('%Y-%m-%d')} "
|
||||
f"(间隔 {gap_info['gap']} 天)")
|
||||
|
||||
print(f"\n{'=' * 60}")
|
||||
|
||||
|
||||
def compare_markets(source: FlaskAPIDataSource, year: int):
|
||||
"""
|
||||
比较不同市场的交易日历
|
||||
|
||||
Args:
|
||||
source: Flask API 数据源实例
|
||||
year: 年份
|
||||
"""
|
||||
print(f"\n{'=' * 60}")
|
||||
print(f"{year} 年不同市场交易日历对比")
|
||||
print(f"{'=' * 60}")
|
||||
|
||||
markets = {
|
||||
'A': 'A股（上交所/深交所）',
|
||||
'US': '美股（NYSE）',
|
||||
'HK': '港股（HKEX）'
|
||||
}
|
||||
|
||||
results = {}
|
||||
for market_code, market_name in markets.items():
|
||||
print(f"\n获取 {market_name} 交易日历...")
|
||||
trading_dates = get_calendar_for_year(source, year, market_code)
|
||||
|
||||
if trading_dates is not None and len(trading_dates) > 0:
|
||||
results[market_code] = {
|
||||
'name': market_name,
|
||||
'dates': trading_dates,
|
||||
'count': len(trading_dates)
|
||||
}
|
||||
|
||||
# 对比统计
|
||||
print(f"\n交易日对比:")
|
||||
print(f"{'市场':<20} {'交易日数':<10} {'起始日期':<12} {'结束日期':<12}")
|
||||
print("-" * 60)
|
||||
|
||||
for market_code, data in results.items():
|
||||
print(f"{data['name']:<20} {data['count']:<10} "
|
||||
f"{data['dates'].min().strftime('%Y-%m-%d'):<12} "
|
||||
f"{data['dates'].max().strftime('%Y-%m-%d'):<12}")
|
||||
|
||||
# 计算差异
|
||||
if len(results) >= 2:
|
||||
print(f"\n交易日差异:")
|
||||
market_codes = list(results.keys())
|
||||
for i in range(len(market_codes)):
|
||||
for j in range(i+1, len(market_codes)):
|
||||
m1 = market_codes[i]
|
||||
m2 = market_codes[j]
|
||||
diff = results[m1]['count'] - results[m2]['count']
|
||||
print(f" {results[m1]['name']} vs {results[m2]['name']}: "
|
||||
f"相差 {abs(diff)} 天 ({'+' if diff > 0 else ''}{diff})")
|
||||
|
||||
print(f"\n{'=' * 60}")
|
||||
|
||||
|
||||
def show_recent_dates(trading_dates: pd.DatetimeIndex, n: int = 10):
|
||||
"""
|
||||
显示最近的交易日
|
||||
|
||||
Args:
|
||||
trading_dates: 交易日序列
|
||||
n: 显示数量
|
||||
"""
|
||||
if trading_dates is None or len(trading_dates) == 0:
|
||||
return
|
||||
|
||||
print(f"\n最近 {n} 个交易日:")
|
||||
recent_dates = trading_dates[-n:] if len(trading_dates) >= n else trading_dates
|
||||
|
||||
for date in recent_dates:
|
||||
weekday = date.strftime('%A')
|
||||
print(f" {date.strftime('%Y-%m-%d')} ({weekday})")
|
||||
|
||||
|
||||
def export_calendar(trading_dates: pd.DatetimeIndex, output_path: str, year: int):
|
||||
"""
|
||||
导出交易日历到 CSV
|
||||
|
||||
Args:
|
||||
trading_dates: 交易日序列
|
||||
output_path: 输出路径
|
||||
year: 年份
|
||||
"""
|
||||
if trading_dates is None or len(trading_dates) == 0:
|
||||
return
|
||||
|
||||
# 创建 DataFrame
|
||||
df = pd.DataFrame({
|
||||
'date': trading_dates,
|
||||
'year': trading_dates.year,
|
||||
'month': trading_dates.month,
|
||||
'quarter': (trading_dates.month - 1) // 3 + 1,
|
||||
'weekday': [d.strftime('%A') for d in trading_dates]
|
||||
})
|
||||
|
||||
# 导出到 CSV
|
||||
filename = f"{output_path}/trading_calendar_A_{year}.csv"
|
||||
df.to_csv(filename, index=False)
|
||||
print(f"\n✓ 交易日历已导出到: {filename}")
|
||||
print(f" 文件包含 {len(df)} 条记录")
|
||||
|
||||
|
||||
def main():
|
||||
"""主函数"""
|
||||
parser = argparse.ArgumentParser(description='获取 A 股交易日历')
|
||||
|
||||
parser.add_argument(
|
||||
'--year',
|
||||
type=int,
|
||||
default=datetime.now().year,
|
||||
help='年份（默认当前年份）'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--start',
|
||||
type=str,
|
||||
help='起始日期 YYYY-MM-DD'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--end',
|
||||
type=str,
|
||||
help='结束日期 YYYY-MM-DD'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--market',
|
||||
type=str,
|
||||
default='A',
|
||||
choices=['A', 'US', 'HK'],
|
||||
help='市场代码（A=A股, US=美股, HK=港股）'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--compare',
|
||||
action='store_true',
|
||||
help='对比不同市场交易日历'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--export',
|
||||
action='store_true',
|
||||
help='导出交易日历到 CSV'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--output',
|
||||
type=str,
|
||||
default='data',
|
||||
help='导出目录（默认 data）'
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
# 初始化 Flask API 数据源
|
||||
print("\n初始化 Flask API 数据源...")
|
||||
source = FlaskAPIDataSource()
|
||||
|
||||
# 检查服务健康状态
|
||||
health = source.get_health()
|
||||
if health.get('status') != 'healthy':
|
||||
print(f"✗ Flask API 服务不可用: {health}")
|
||||
sys.exit(1)
|
||||
|
||||
print(f"✓ Flask API 服务可用 ({source.base_url})")
|
||||
|
||||
# 获取交易日历信息
|
||||
calendar_info = source.get_calendar_info()
|
||||
if 'error' not in calendar_info:
|
||||
print(f"\n交易日历服务信息:")
|
||||
print(f" 支持市场: {', '.join(calendar_info.get('markets', []))}")
|
||||
print(f" 数据源: {calendar_info.get('source', 'pandas_market_calendars')}")
|
||||
|
||||
# 执行不同功能
|
||||
if args.compare:
|
||||
# 对比不同市场
|
||||
compare_markets(source, args.year)
|
||||
|
||||
elif args.start and args.end:
|
||||
# 自定义日期范围
|
||||
print(f"\n获取 {args.market} 市场交易日历 ({args.start} ~ {args.end})...")
|
||||
trading_dates = source.get_trading_calendar(
|
||||
market=args.market,
|
||||
start_date=args.start,
|
||||
end_date=args.end
|
||||
)
|
||||
|
||||
if trading_dates is not None:
|
||||
print(f"✓ 获取到 {len(trading_dates)} 个交易日")
|
||||
show_recent_dates(trading_dates)
|
||||
|
||||
if args.export:
|
||||
export_calendar(trading_dates, args.output, args.year)
|
||||
|
||||
else:
|
||||
# 获取指定年份交易日历
|
||||
trading_dates = get_calendar_for_year(source, args.year, args.market)
|
||||
|
||||
if trading_dates is not None:
|
||||
# 分析统计
|
||||
analyze_calendar(trading_dates, args.year)
|
||||
|
||||
# 显示最近交易日
|
||||
show_recent_dates(trading_dates)
|
||||
|
||||
# 导出
|
||||
if args.export:
|
||||
export_calendar(trading_dates, args.output, args.year)
|
||||
|
||||
print("\n✓ 完成！")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user