1. # coding=utf-8
      2. from __future__ import print_function, absolute_import, unicode_literals
      3. from gm.api import *
      4. import numpy as np
      6. '''
      7. 本策略根据计算滚动的.过去的30个1min的bar的均值正负2个标准差得到布林线
      8. 并在最新价差上穿上轨来做空价差,下穿下轨来做多价差
      9. 并在回归至上下轨水平内的时候平仓
      10. 回测数据为:SHFE.rb1801和SHFE.hc1801的1min数据
      11. 回测时间为:2017-09-01 08:00:00到2017-10-01 16:00:00
      12. '''
      15. def init(context):
      16.     # 进行套利的品种
      17.     context.goods = ['SHFE.rb1801', 'SHFE.hc1801']
      18.     # 订阅行情
      19.     subscribe(symbols=context.goods, frequency='60s', count=31, wait_group=True)
      22. def on_bar(context, bars):
      23.     # 获取两个品种的时间序列
      24.     data_rb = context.data(symbol=context.goods[0], frequency='60s', count=31, fields='close')
      25.     close_rb = data_rb.values
      26.     data_hc = context.data(symbol=context.goods[1], frequency='60s', count=31, fields='close')
      27.     close_hc = data_hc.values
      28.     # 计算价差
      29.     spread = close_rb[:-1] - close_hc[:-1]
      30.     # 计算布林带的上下轨
      31.     up = np.mean(spread) + 2 * np.std(spread)
      32.     down = np.mean(spread) - 2 * np.std(spread)
      33.     # 计算最新价差
      34.     spread_now = close_rb[-1] - close_hc[-1]
      35.     # 无交易时若价差上(下)穿布林带上(下)轨则做空(多)价差
      36.     position_rb_long = context.account().position(symbol=context.goods[0], side=PositionSide_Long)
      37.     position_rb_short = context.account().position(symbol=context.goods[0], side=PositionSide_Short)
      38.     if not position_rb_long and not position_rb_short:
      39.         if spread_now > up:
      40.             order_target_volume(symbol=context.goods[0], volume=1, order_type=OrderType_Market,
      41.                                 position_side=PositionSide_Short)
      42.             print(context.goods[0], '以市价单开空仓一手')
      43.             order_target_volume(symbol=context.goods[1], volume=1, order_type=OrderType_Market,
      44.                                 position_side=PositionSide_Long)
      45.             print(context.goods[1], '以市价单开多仓一手')
      46.         if spread_now < down:
      47.             order_target_volume(symbol=context.goods[0], volume=1, order_type=OrderType_Market,
      48.                                 position_side=PositionSide_Long)
      49.             print(context.goods[0], '以市价单开多仓一手')
      50.             order_target_volume(symbol=context.goods[1], volume=1, order_type=OrderType_Market,
      51.                                 position_side=PositionSide_Short)
      52.             print(context.goods[1], '以市价单开空仓一手')
      53.     # 价差回归时平仓
      54.     elif position_rb_short:
      55.         if spread_now <= up:
      56.             order_close_all()
      57.             print('价格回归,平所有仓位')
      58.             # 跌破下轨反向开仓
      59.         if spread_now < down:
      60.             order_target_volume(symbol=context.goods[0], volume=1, order_type=OrderType_Market,
      61.                                 position_side=PositionSide_Long)
      62.             print(context.goods[0], '以市价单开多仓一手')
      63.             order_target_volume(symbol=context.goods[1], volume=1, order_type=OrderType_Market,
      64.                                 position_side=PositionSide_Short)
      65.             print(context.goods[1], '以市价单开空仓一手')
      66.     elif position_rb_long:
      67.         if spread_now >= down:
      68.             order_close_all()
      69.             print('价格回归,平所有仓位')
      70.             # 涨破上轨反向开仓
      71.         if spread_now > up:
      72.             order_target_volume(symbol=context.goods[0], volume=1, order_type=OrderType_Market,
      73.                                 position_side=PositionSide_Short)
      74.             print(context.goods[0], '以市价单开空仓一手')
      75.             order_target_volume(symbol=context.goods[1], volume=1, order_type=OrderType_Market,
      76.                                 position_side=PositionSide_Long)
      77.             print(context.goods[1], '以市价单开多仓一手')
      80. if __name__ == '__main__':
      81.     '''
      82.     strategy_id策略ID,由系统生成
      83.     filename文件名,请与本文件名保持一致
      84.     mode实时模式:MODE_LIVE回测模式:MODE_BACKTEST
      85.     token绑定计算机的ID,可在系统设置-密钥管理中生成
      86.     backtest_start_time回测开始时间
      87.     backtest_end_time回测结束时间
      88.     backtest_adjust股票复权方式不复权:ADJUST_NONE前复权:ADJUST_PREV后复权:ADJUST_POST
      89.     backtest_initial_cash回测初始资金
      90.     backtest_commission_ratio回测佣金比例
      91.     backtest_slippage_ratio回测滑点比例
      92.     '''
      93.     run(strategy_id='strategy_id',
      94.         filename='main.py',
      95.         mode=MODE_BACKTEST,
      96.         token='token_id',
      97.         backtest_start_time='2017-09-01 08:00:00',
      98.         backtest_end_time='2017-10-01 16:00:00',
      99.         backtest_adjust=ADJUST_PREV,
      100.         backtest_initial_cash=500000,
      101.         backtest_commission_ratio=0.0001,
      102.         backtest_slippage_ratio=0.0001)

    跨品种套利(期货)

    原文: https://www.myquant.cn/docs/python_strategyies/106