1. # coding=utf-8
      2. from __future__ import print_function, absolute_import, unicode_literals
      3. from gm.api import *
      5. '''
      6. 本策略通过获取SHSE.000300沪深300的成份股数据并统计其30天内
      7. 开盘价大于前收盘价的天数,并在该天数大于阈值10的时候加入股票池
      8. 随后对不在股票池的股票平仓并等权配置股票池的标的,每次交易间隔1个月.
      9. 回测数据为:SHSE.000300在2015-01-15的成份股
      10. 回测时间为:2017-07-01 08:00:00到2017-10-01 16:00:00
      11. '''
      14. def init(context):
      15.     # 每月第一个交易日的09:40 定时执行algo任务
      16.     schedule(schedule_func=algo, date_rule='1m', time_rule='09:40:00')
      17.     # context.count_bench累计天数阙值
      18.     context.count_bench = 10
      19.     # 用于对比的天数
      20.     context.count = 30
      21.     # 最大交易资金比例
      22.     context.ratio = 0.8
      25. def algo(context):
      26.     # 获取当前时间
      27.     now = context.now
      28.     # 获取上一个交易日
      29.     last_day = get_previous_trading_date(exchange='SHSE', date=now)
      30.     # 获取沪深300成份股
      31.     context.stock300 = get_history_constituents(index='SHSE.000300', start_date=last_day,
      32.                                                 end_date=last_day)[0]['constituents'].keys()
      33.     # 获取当天有交易的股票
      34.     not_suspended_info = get_history_instruments(symbols=context.stock300, start_date=now, end_date=now)
      35.     not_suspended_symbols = [item['symbol'] for item in not_suspended_info if not item['is_suspended']]
      37.     trade_symbols = []
      38.     if not not_suspended_symbols:
      39.         print('没有当日交易的待选股票')
      40.         return
      42.     for stock in not_suspended_symbols:
      43.         recent_data = history_n(symbol=stock, frequency='1d', count=context.count, fields='pre_close,open',
      44.                                 fill_missing='Last', adjust=ADJUST_PREV, end_time=now, df=True)
      45.         diff = recent_data['open'] - recent_data['pre_close']
      46.         # 获取累计天数超过阙值的标的池.并剔除当天没有交易的股票
      47.         if len(diff[diff > 0]) >= context.count_bench:
      48.             trade_symbols.append(stock)
      50.     print('本次股票池有股票数目: ', len(trade_symbols))
      51.     # 计算权重
      52.     percent = 1.0 / len(trade_symbols) * context.ratio
      53.     # 获取当前所有仓位
      54.     positions = context.account().positions()
      55.     # 如标的池有仓位,平不在标的池的仓位
      56.     for position in positions:
      57.         symbol = position['symbol']
      58.         if symbol not in trade_symbols:
      59.             order_target_percent(symbol=symbol, percent=0, order_type=OrderType_Market,
      60.                                  position_side=PositionSide_Long)
      61.             print('市价单平不在标的池的', symbol)
      63.     # 对标的池进行操作
      64.     for symbol in trade_symbols:
      65.         order_target_percent(symbol=symbol, percent=percent, order_type=OrderType_Market,
      66.                              position_side=PositionSide_Long)
      67.         print(symbol, '以市价单调整至权重', percent)
      70. if __name__ == '__main__':
      71.     '''
      72.     strategy_id策略ID,由系统生成
      73.     filename文件名,请与本文件名保持一致
      74.     mode实时模式:MODE_LIVE回测模式:MODE_BACKTEST
      75.     token绑定计算机的ID,可在系统设置-密钥管理中生成
      76.     backtest_start_time回测开始时间
      77.     backtest_end_time回测结束时间
      78.     backtest_adjust股票复权方式不复权:ADJUST_NONE前复权:ADJUST_PREV后复权:ADJUST_POST
      79.     backtest_initial_cash回测初始资金
      80.     backtest_commission_ratio回测佣金比例
      81.     backtest_slippage_ratio回测滑点比例
      82.     '''
      83.     run(strategy_id='strategy_id',
      84.         filename='main.py',
      85.         mode=MODE_BACKTEST,
      86.         token='token_id',
      87.         backtest_start_time='2017-07-01 08:00:00',
      88.         backtest_end_time='2017-10-01 16:00:00',
      89.         backtest_adjust=ADJUST_PREV,
      90.         backtest_initial_cash=10000000,
      91.         backtest_commission_ratio=0.0001,
      92.         backtest_slippage_ratio=0.0001)

    [集合竞价选股(股票)]

    原文: https://www.myquant.cn/docs/python_strategyies/102