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@Channelchan 2017-08-08T07:37:19.000000Z 字数 3351 阅读 30875

引擎设置持有时间的策略

  1. #coding=utf-8
  2. # run_code_demo
  3. from rqalpha import run_code
  5. code = """
  6. import rqalpha
  7. from rqalpha.api import *
  8. import pandas as pd
  10. def init(context):
  11.     codes = pd.read_excel('C:/Users/small/Desktop/july_first/lflo.xlsx')
  12.     codes.index = codes.pop('date')
  13.     context.codes = codes
  14.     scheduler.run_weekly(find_pool, tradingday=1)
  15.     scheduler.run_weekly(buy, tradingday=1)
  16.     #设置持有时间，可以设置为五天，十天等。
  17.     context.holdperiod = 10
  18.     context.stocks = []
  19.     context.time = []
  21. def find_pool(context, bar_dict):
  22.     try:
  23.         codes = context.codes.loc[context.now]
  24.     except KeyError:
  25.         return
  26.     stocks = codes.index[codes == True]
  27.     context.stocks = stocks
  29. def handle_bar(context, bar_dict):
  30.     hold_period(context, bar_dict)
  32. def buy(context, bar_dict):
  33.     pool = context.stocks
  34.     if pool is not None:
  35.         stocks_len = len(pool)
  36.     cur_value = context.portfolio.market_value
  37.     for stock in pool:
  38.         if cur_value==0:
  39.             order_target_percent(stock, 1.0/stocks_len)
  40.             buy_time = context.now.replace(tzinfo=None)
  41.             context.time = buy_time
  43. def hold_period( context,bar_dict):
  44.     for stock in context.portfolio.positions:
  45.         buytime=context.time # 获取买入时间
  46.         currenttime=context.now.replace(tzinfo=None) # 获取当前时间
  47.         print ('buytime='+str(buytime))
  48.         print('currenttime='+str(currenttime))
  49.         hold_time=(currenttime-buytime).days # 计算持有天数
  50.         if hold_time>context.holdperiod:
  51.             order_target_percent(stock, 0)
  53. config = {
  54.   "base": {
  55.     #设置回测开始时间
  56.     "start_date": "2016-05-23",
  57.     #设置回测结束时间
  58.     "end_date": "2017-06-01",
  59.     #设置回测的品种与初始资金
  60.     "accounts": {'stock':1000000},
  61.     #设置基准收益
  62.     "benchmark": "000300.XSHG",
  63.   },
  64.   "extra": {
  65.     #查看最详细的日志，'error'只看错误。
  66.     "log_level": "verbose",
  67.   },
  68.   "mod": {
  69.     "sys_analyser": {
  70.         #保存report至当下文件
  71.         "report_save_path": '.',
  72.         #启动策略逐行性能分析
  73.         "enabled": True,
  74.         #打印图形
  75.         "plot": True
  76.      },
  77.     "sys_simulation": {
  78.         #是否限制买入涨停板
  79.         "price_limit":False,
  80.         "enabled": True,
  81.         #设置手续费的倍数，默认是10
  82.         "commission_multiplier": 0,
  83.         #设置滑点
  84.         "slippage": 0
  85.     }
  86.   }
  87. }
  89. run_code(code, config)
  1. #coding=utf-8
  2. import rqalpha
  3. from rqalpha.api import *
  4. import os
  5. import pandas as pd
  7. def init(context):
  8.     codes = pd.read_excel('C:/Users/small/Desktop/july_first/lflo.xlsx')
  9.     codes.index = codes.pop('date')
  10.     context.codes = codes
  11.     scheduler.run_weekly(find_pool, tradingday=1)
  12.     scheduler.run_weekly(buy, tradingday=1)
  13.     #设置持有时间，可以设置为五天，十天等。
  14.     context.holdperiod = 10
  15.     context.stocks = []
  16.     context.time = []
  18. def find_pool(context, bar_dict):
  19.     try:
  20.         codes = context.codes.loc[context.now]
  21.     except KeyError:
  22.         return
  23.     stocks = codes.index[codes == True]
  24.     context.stocks = stocks
  26. def handle_bar(context, bar_dict):
  27.     hold_period(context, bar_dict)
  29. def buy(context, bar_dict):
  30.     pool = context.stocks
  31.     if pool is not None:
  32.         stocks_len = len(pool)
  33.     cur_value = context.portfolio.market_value
  34.     for stock in pool:
  35.         if cur_value==0:
  36.             order_target_percent(stock, 1.0/stocks_len)
  37.             buy_time = context.now.replace(tzinfo=None)
  38.             context.time = buy_time
  40. def hold_period( context,bar_dict):
  41.     for stock in context.portfolio.positions:
  42.         buytime=context.time # 获取买入时间
  43.         currenttime=context.now.replace(tzinfo=None) # 获取当前时间
  44.         print ('buytime='+str(buytime))
  45.         print('currenttime='+str(currenttime))
  46.         hold_time=(currenttime-buytime).days # 计算持有天数
  47.         if hold_time>context.holdperiod:
  48.             order_target_percent(stock, 0)
  50. config = {
  51.   "base": {
  52.     #设置回测开始时间
  53.     "start_date": "2016-05-23",
  54.     #设置回测结束时间
  55.     "end_date": "2017-06-01",
  56.     #设置回测的品种与初始资金
  57.     "accounts": {'stock':1000000},
  58.     #设置基准收益
  59.     "benchmark": "000300.XSHG",
  60.     #运行当下策略文件
  61.     "strategy_file_path": os.path.abspath(__file__)
  62.   },
  63.   "extra": {
  64.     #查看最详细的日志，'error'只看错误。
  65.     "log_level": "verbose",
  66.   },
  67.   "mod": {
  68.     "sys_analyser": {
  69.         #保存report至当下文件
  70.         "report_save_path": '.',
  71.         #启动策略逐行性能分析
  72.         "enabled": True,
  73.         #打印图形
  74.         "plot": True
  75.      },
  76.     "sys_simulation": {
  77.         #是否限制买入涨停板
  78.         "price_limit":False,
  79.         "enabled": True,
  80.         #设置手续费的倍数，默认是10
  81.         "commission_multiplier": 0,
  82.         #设置滑点
  83.         "slippage": 0
  84.     }
  85.   }
  86. }
  88. rqalpha.run_func(init=init, handle_bar=handle_bar, config=config)
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