1. # coding=utf-8
      2. from __future__ import print_function, absolute_import, unicode_literals
      4. import numpy as np
      5. from gm.api import *
      7. try:
      8.     import statsmodels.tsa.stattools as ts
      9. except:
      10.     print('请安装statsmodels库')
      12. '''
      13. 本策略根据EG两步法(1.序列同阶单整2.OLS残差平稳)判断序列具有协整关系之后(若无协整关系则全平仓位不进行操作)
      14. 通过计算两个真实价格序列回归残差的0.9个标准差上下轨,并在价差突破上轨的时候做空价差,价差突破下轨的时候做多价差
      15. 并在回归至标准差水平内的时候平仓
      16. 回测数据为:SHFE.rb1801和SHFE.rb1805的1min数据
      17. 回测时间为:2017-09-25 08:00:00到2017-10-01 15:00:00
      18. '''
      21. # 协整检验的函数
      22. def cointegration_test(series01, series02):
      23.     urt_rb1801 = ts.adfuller(np.array(series01), 1)[1]
      24.     urt_rb1805 = ts.adfuller(np.array(series01), 1)[1]
      25.     # 同时平稳或不平稳则差分再次检验
      26.     if (urt_rb1801 > 0.1 and urt_rb1805 > 0.1) or (urt_rb1801 < 0.1 and urt_rb1805 < 0.1):
      27.         urt_diff_rb1801 = ts.adfuller(np.diff(np.array(series01)), 1)[1]
      28.         urt_diff_rb1805 = ts.adfuller(np.diff(np.array(series01), 1))[1]
      29.         # 同时差分平稳进行OLS回归的残差平稳检验
      30.         if urt_diff_rb1801 < 0.1 and urt_diff_rb1805 < 0.1:
      31.             matrix = np.vstack([series02, np.ones(len(series02))]).T
      32.             beta, c = np.linalg.lstsq(matrix, series01)[0]
      33.             resid = series01 - beta * series02 - c
      34.             if ts.adfuller(np.array(resid), 1)[1] > 0.1:
      35.                 result = 0.0
      36.             else:
      37.                 result = 1.0
      38.             return beta, c, resid, result
      40.         else:
      41.             result = 0.0
      42.             return 0.0, 0.0, 0.0, result
      44.     else:
      45.         result = 0.0
      46.         return 0.0, 0.0, 0.0, result
      49. def init(context):
      50.     context.goods = ['SHFE.rb1801', 'SHFE.rb1805']
      51.     # 订阅品种
      52.     subscribe(symbols=context.goods, frequency='60s', count=801, wait_group=True)
      55. def on_bar(context, bars):
      56.     # 获取过去800个60s的收盘价数据
      57.     close_01 = context.data(symbol=context.goods[0], frequency='60s', count=801, fields='close')['close'].values
      58.     close_02 = context.data(symbol=context.goods[1], frequency='60s', count=801, fields='close')['close'].values
      59.     # 展示两个价格序列的协整检验的结果
      60.     beta, c, resid, result = cointegration_test(close_01, close_02)
      61.     # 如果返回协整检验不通过的结果则全平仓位等待
      62.     if not result:
      63.         print('协整检验不通过,全平所有仓位')
      64.         order_close_all()
      65.         return
      67.     # 计算残差的标准差上下轨
      68.     mean = np.mean(resid)
      69.     up = mean + 0.9 * np.std(resid)
      70.     down = mean - 0.9 * np.std(resid)
      71.     # 计算新残差
      72.     resid_new = close_01[-1] - beta * close_02[-1] - c
      73.     # 获取rb1801的多空仓位
      74.     position_01_long = context.account().position(symbol=context.goods[0], side=PositionSide_Long)
      75.     position_01_short = context.account().position(symbol=context.goods[0], side=PositionSide_Short)
      76.     if not position_01_long and not position_01_short:
      77.         # 上穿上轨时做空新残差
      78.         if resid_new > up:
      79.             order_target_volume(symbol=context.goods[0], volume=1, order_type=OrderType_Market,
      80.                                 position_side=PositionSide_Short)
      81.             print(context.goods[0] + '以市价单开空仓1手')
      82.             order_target_volume(symbol=context.goods[1], volume=1, order_type=OrderType_Market,
      83.                                 position_side=PositionSide_Long)
      84.             print(context.goods[1] + '以市价单开多仓1手')
      85.         # 下穿下轨时做多新残差
      86.         if resid_new < down:
      87.             order_target_volume(symbol=context.goods[0], volume=1, order_type=OrderType_Market,
      88.                                 position_side=PositionSide_Long)
      89.             print(context.goods[0], '以市价单开多仓1手')
      90.             order_target_volume(symbol=context.goods[1], volume=1, order_type=OrderType_Market,
      91.                                 position_side=PositionSide_Short)
      92.             print(context.goods[1], '以市价单开空仓1手')
      93.     # 新残差回归时平仓
      94.     elif position_01_short:
      95.         if resid_new <= up:
      96.             order_close_all()
      97.             print('价格回归,平掉所有仓位')
      98.         # 突破下轨反向开仓
      99.         if resid_new < down:
      100.             order_target_volume(symbol=context.goods[0], volume=1, order_type=OrderType_Market,
      101.                                 position_side=PositionSide_Long)
      102.             print(context.goods[0], '以市价单开多仓1手')
      103.             order_target_volume(symbol=context.goods[1], volume=1, order_type=OrderType_Market,
      104.                                 position_side=PositionSide_Short)
      105.             print(context.goods[1], '以市价单开空仓1手')
      106.     elif position_01_long:
      107.         if resid_new >= down:
      108.             order_close_all()
      109.             print('价格回归,平所有仓位')
      110.         # 突破上轨反向开仓
      111.         if resid_new > up:
      112.             order_target_volume(symbol=context.goods[0], volume=1, order_type=OrderType_Market,
      113.                                 position_side=PositionSide_Short)
      114.             print(context.goods[0], '以市价单开空仓1手')
      115.             order_target_volume(symbol=context.goods[1], volume=1, order_type=OrderType_Market,
      116.                                 position_side=PositionSide_Long)
      117.             print(context.goods[1], '以市价单开多仓1手')
      120. if __name__ == '__main__':
      121.     '''
      122.     strategy_id策略ID,由系统生成
      123.     filename文件名,请与本文件名保持一致
      124.     mode实时模式:MODE_LIVE回测模式:MODE_BACKTEST
      125.     token绑定计算机的ID,可在系统设置-密钥管理中生成
      126.     backtest_start_time回测开始时间
      127.     backtest_end_time回测结束时间
      128.     backtest_adjust股票复权方式不复权:ADJUST_NONE前复权:ADJUST_PREV后复权:ADJUST_POST
      129.     backtest_initial_cash回测初始资金
      130.     backtest_commission_ratio回测佣金比例
      131.     backtest_slippage_ratio回测滑点比例
      132.     '''
      133.     run(strategy_id='strategy_id',
      134.         filename='main.py',
      135.         mode=MODE_BACKTEST,
      136.         token='token_id',
      137.         backtest_start_time='2017-09-25 08:00:00',
      138.         backtest_end_time='2017-10-01 16:00:00',
      139.         backtest_adjust=ADJUST_PREV,
      140.         backtest_initial_cash=500000,
      141.         backtest_commission_ratio=0.0001,
      142.         backtest_slippage_ratio=0.0001)

    跨期套利(期货)

    原文: https://www.myquant.cn/docs/python_strategyies/107