{"description":"实验创建于9/10/2021","graph":{"edges":[{"to_node_id":"-8:instruments","from_node_id":"-30:data"},{"to_node_id":"-39:instruments","from_node_id":"-30:data"},{"to_node_id":"-8:options_data","from_node_id":"-39:data"}],"nodes":[{"node_id":"-8","module_id":"BigQuantSpace.hftrade.hftrade-v1","parameters":[{"name":"start_date","value":"","type":"Literal","bound_global_parameter":null},{"name":"end_date","value":"","type":"Literal","bound_global_parameter":null},{"name":"initialize","value":"# 交易引擎：初始化函数，只执行一次\ndef bigquant_run(context):\n # 加载预测数据\n context.closetime_day = \"14:58\"\n context.closetime_night = \"22:58\"\n #注册bar处理函数\n context.subscribe_bar(context.instruments, \"1m\", handle_bar)\n #打印控制开关\n context.PRINT = 0\n\n #提前计算开仓需要的均线信息，节省回测时间\n context.mydata = context.options[\"data\"].read()\n def cal_signal(df):\n df = df.sort_values(\"date\")\n df[\"ma\"] = df[\"close\"].rolling(20).mean()\n df[\"signal\"] = np.where((df['close'].shift(1)<df['ma'].shift(1)) & (df['close']>=df['ma']),1,0)\n df[\"signal\"] = np.where((df['close'].shift(1)>df['ma'].shift(1)) & (df['close']<df['ma']),-1,df[\"signal\"])\n return df\n context.mydata = context.mydata.groupby(\"instrument\").apply(cal_signal).reset_index(drop=True)\n \n\n","type":"Literal","bound_global_parameter":null},{"name":"before_trading_start","value":"# 交易引擎：每个单位时间开盘前调用一次。\ndef bigquant_run(context, data):\n pass\n","type":"Literal","bound_global_parameter":null},{"name":"handle_tick","value":"# 交易引擎：tick数据处理函数，每个tick执行一次\ndef bigquant_run(context, data):\n pass\n","type":"Literal","bound_global_parameter":null},{"name":"handle_data","value":"from datetime import datetime,timedelta\n# 交易引擎：bar数据处理函数，每个时间单位执行一次\ndef bigquant_run(context, data):\n #此函数是处理handle_data\n pass\n\n#处理handle_bar\ndef handle_bar(context, bar):\n #获取当前时间\n cur_date = bar.datetime\n cur_hm = cur_date.strftime('%H:%M')\n \n # 分别获取多头持仓和空头持仓，主要使用 current_qty 和 avail_qty 两个属性\n position_long = context.get_position(bar.symbol, Direction.LONG)\n position_short = context.get_position(bar.symbol, Direction.SHORT)\n\n # 获取账户资金，主要使用 balance 和 available 两个属性，本策略没有使用到账户信息，在此仅作展示获取方法\n trading_account = context.get_trading_account()\n\n # 获取当前k线最新收盘价格\n price = bar.close\n \n #尾盘平仓\n #部分品种夜盘收盘时间不一样，此时间表示指定的尾盘平仓时间往后偏移30分钟，这段时间内不能开新仓，只能平仓。给30分钟是为了足够的冗余\n closetime_nightshift = (datetime.strptime(context.closetime_night,'%H:%M') + timedelta(minutes = 30)).strftime('%H:%M')\n if((cur_hm>=context.closetime_day and cur_hm<=\"15:00\") or (cur_hm>=context.closetime_night and cur_hm<=closetime_nightshift)):\n if(position_long.current_qty != 0):\n rv = context.sell_close(bar.symbol, position_long.avail_qty, price, order_type=OrderType.MARKET)\n msg = \"{} 尾盘平多 for {} 最新价={} 下单函数返回 {}\".format(str(cur_date),bar.symbol,price,context.get_error_msg(rv))\n context.write_log(msg, stdout=context.PRINT) \n if(position_short.current_qty != 0):\n rv = context.buy_close(bar.symbol, position_short.avail_qty, price, order_type=OrderType.MARKET)\n msg = \"{} 尾盘平空 for {} 最新价={} 下单函数返回 {}\".format(str(cur_date),bar.symbol,price,context.get_error_msg(rv))\n context.write_log(msg, stdout=context.PRINT) \n #尾盘不开新仓，直接返回\n return\n \n #获取历史数据数据\n hist = context.mydata[(context.mydata.instrument==bar.symbol)&(context.mydata.date==cur_date)]\n #没有找到对应数据，直接返回\n if len(hist)==0:\n return\n\n #计算20均线\n hist['ma'] = hist['close'].rolling(20).mean()\n\n #价格向上穿越20均线\n if(hist[\"signal\"].iloc[0]==1):\n #有空单的先平掉\n if (position_short.avail_qty != 0):\n rv = context.buy_close(bar.symbol, position_short.avail_qty, price, order_type=OrderType.MARKET)\n msg = \"{} 平空 for {} 最新价={} 下单函数返回 {}\".format(bar.datetime,bar.symbol,price,context.get_error_msg(rv))\n context.write_log(msg, stdout=context.PRINT)\n #没有多单则开多1手\n if (position_long.current_qty == 0):\n rv = context.buy_open(bar.symbol, 1, price, order_type=OrderType.MARKET)\n msg = \"{} 开多 for {} 最新价={} 下单函数返回 {}\".format(bar.datetime,bar.symbol,price,context.get_error_msg(rv))\n context.write_log(msg, stdout=context.PRINT) \n #价格向下穿越20均线\n if (hist[\"signal\"].iloc[0]==-1):\n #有多单的先平掉\n if (position_long.avail_qty != 0):\n rv = context.sell_close(bar.symbol, position_long.avail_qty, price, order_type=OrderType.MARKET)\n msg = \"{} 平多 for {} 最新价={} 下单函数返回 {}\".format(bar.datetime,bar.symbol,price,context.get_error_msg(rv))\n context.write_log(msg, stdout=context.PRINT)\n #没有空单则开空1手 \n if (position_short.current_qty == 0):\n rv = context.sell_open(bar.symbol, 1, price, order_type=OrderType.MARKET)\n msg = \"{} 开空 for {} 最新价={} 下单函数返回 {}\".format(bar.datetime,bar.symbol,price,context.get_error_msg(rv))\n context.write_log(msg, stdout=context.PRINT) \n","type":"Literal","bound_global_parameter":null},{"name":"handle_trade","value":"# 交易引擎：成交回报处理函数，每个成交发生时执行一次\ndef bigquant_run(context, data):\n msg = \"handle_trade data:{}\".format(data.log_str())\n context.write_log(msg, stdout=context.PRINT) 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# 本代码由可视化策略环境自动生成 2021年10月28日 11:33
# 本代码单元只能在可视化模式下编辑。您也可以拷贝代码，粘贴到新建的代码单元或者策略，然后修改。


# 交易引擎：初始化函数，只执行一次
def m1_initialize_bigquant_run(context):
    # 加载预测数据
    context.closetime_day = "14:58"
    context.closetime_night = "22:58"
    #注册bar处理函数
    context.subscribe_bar(context.instruments, "1m", handle_bar)
    #打印控制开关
    context.PRINT = 0

    #提前计算开仓需要的均线信息，节省回测时间
    context.mydata = context.options["data"].read()
    def cal_signal(df):
        df = df.sort_values("date")
        df["ma"] = df["close"].rolling(20).mean()
        df["signal"] = np.where((df['close'].shift(1)<df['ma'].shift(1)) & (df['close']>=df['ma']),1,0)
        df["signal"] = np.where((df['close'].shift(1)>df['ma'].shift(1)) & (df['close']<df['ma']),-1,df["signal"])
        return df
    context.mydata = context.mydata.groupby("instrument").apply(cal_signal).reset_index(drop=True)
    


# 交易引擎：每个单位时间开盘前调用一次。
def m1_before_trading_start_bigquant_run(context, data):
    pass

# 交易引擎：tick数据处理函数，每个tick执行一次
def m1_handle_tick_bigquant_run(context, data):
    pass

from datetime import datetime,timedelta
# 交易引擎：bar数据处理函数，每个时间单位执行一次
def m1_handle_data_bigquant_run(context, data):
    #此函数是处理handle_data
    pass

#处理handle_bar
def handle_bar(context, bar):
    #获取当前时间
    cur_date = bar.datetime
    cur_hm = cur_date.strftime('%H:%M')
     
    # 分别获取多头持仓和空头持仓，主要使用 current_qty 和 avail_qty 两个属性
    position_long = context.get_position(bar.symbol, Direction.LONG)
    position_short = context.get_position(bar.symbol, Direction.SHORT)

    # 获取账户资金，主要使用 balance 和 available 两个属性，本策略没有使用到账户信息，在此仅作展示获取方法
    trading_account = context.get_trading_account()

    # 获取当前k线最新收盘价格
    price = bar.close
    
    #尾盘平仓
    #部分品种夜盘收盘时间不一样，此时间表示指定的尾盘平仓时间往后偏移30分钟，这段时间内不能开新仓，只能平仓。给30分钟是为了足够的冗余
    closetime_nightshift = (datetime.strptime(context.closetime_night,'%H:%M') + timedelta(minutes = 30)).strftime('%H:%M')
    if((cur_hm>=context.closetime_day and cur_hm<="15:00") or (cur_hm>=context.closetime_night and cur_hm<=closetime_nightshift)):
        if(position_long.current_qty != 0):
            rv = context.sell_close(bar.symbol, position_long.avail_qty, price, order_type=OrderType.MARKET)
            msg = "{} 尾盘平多 for {}  最新价={} 下单函数返回 {}".format(str(cur_date),bar.symbol,price,context.get_error_msg(rv))
            context.write_log(msg, stdout=context.PRINT) 
        if(position_short.current_qty != 0):
            rv = context.buy_close(bar.symbol, position_short.avail_qty, price, order_type=OrderType.MARKET)
            msg = "{} 尾盘平空 for {}  最新价={} 下单函数返回 {}".format(str(cur_date),bar.symbol,price,context.get_error_msg(rv))
            context.write_log(msg, stdout=context.PRINT) 
        #尾盘不开新仓，直接返回
        return
    
    #获取历史数据数据
    hist = context.mydata[(context.mydata.instrument==bar.symbol)&(context.mydata.date==cur_date)]
    #没有找到对应数据，直接返回
    if len(hist)==0:
        return

    #计算20均线
    hist['ma'] = hist['close'].rolling(20).mean()

    #价格向上穿越20均线
    if(hist["signal"].iloc[0]==1):
        #有空单的先平掉
        if (position_short.avail_qty != 0):
            rv = context.buy_close(bar.symbol, position_short.avail_qty, price, order_type=OrderType.MARKET)
            msg = "{} 平空 for {}  最新价={} 下单函数返回 {}".format(bar.datetime,bar.symbol,price,context.get_error_msg(rv))
            context.write_log(msg, stdout=context.PRINT)
        #没有多单则开多1手
        if (position_long.current_qty == 0):
            rv = context.buy_open(bar.symbol, 1, price, order_type=OrderType.MARKET)
            msg = "{} 开多 for {}  最新价={} 下单函数返回 {}".format(bar.datetime,bar.symbol,price,context.get_error_msg(rv))
            context.write_log(msg, stdout=context.PRINT) 
    #价格向下穿越20均线
    if (hist["signal"].iloc[0]==-1):
        #有多单的先平掉
        if (position_long.avail_qty != 0):
            rv = context.sell_close(bar.symbol, position_long.avail_qty, price, order_type=OrderType.MARKET)
            msg = "{} 平多 for {}  最新价={} 下单函数返回 {}".format(bar.datetime,bar.symbol,price,context.get_error_msg(rv))
            context.write_log(msg, stdout=context.PRINT)
        #没有空单则开空1手    
        if (position_short.current_qty == 0):
            rv = context.sell_open(bar.symbol, 1, price, order_type=OrderType.MARKET)
            msg = "{} 开空 for {}  最新价={} 下单函数返回 {}".format(bar.datetime,bar.symbol,price,context.get_error_msg(rv))
            context.write_log(msg, stdout=context.PRINT)  

# 交易引擎：成交回报处理函数，每个成交发生时执行一次
def m1_handle_trade_bigquant_run(context, data):
    msg = "handle_trade data:{}".format(data.log_str())
    context.write_log(msg, stdout=context.PRINT) 

# 交易引擎：委托回报处理函数，每个委托变化时执行一次
def m1_handle_order_bigquant_run(context, data):
    msg = "handle_order data:{}".format(data.log_str())
    context.write_log(msg, stdout=context.PRINT) 

# 交易引擎：盘后处理函数，每日盘后执行一次
def m1_after_trading_bigquant_run(context, data):
    pass


m2 = M.instruments.v2(
    start_date='2021-09-01',
    end_date='2021-09-08',
    market='CN_FUTURE',
    instrument_list="""RB2201.SHF
FG2201.CZC""",
    max_count=0
)

m3 = M.use_datasource.v1(
    instruments=m2.data,
    datasource_id='bar1m_CN_FUTURE',
    start_date='',
    end_date='',
    m_cached=False
)

m1 = M.hftrade.v1(
    instruments=m2.data,
    options_data=m3.data,
    start_date='',
    end_date='',
    initialize=m1_initialize_bigquant_run,
    before_trading_start=m1_before_trading_start_bigquant_run,
    handle_tick=m1_handle_tick_bigquant_run,
    handle_data=m1_handle_data_bigquant_run,
    handle_trade=m1_handle_trade_bigquant_run,
    handle_order=m1_handle_order_bigquant_run,
    after_trading=m1_after_trading_bigquant_run,
    capital_base=1000000,
    frequency='minute',
    price_type='真实价格',
    product_type='期货',
    before_start_days='',
    benchmark='000300.HIX',
    plot_charts=True,
    disable_cache=False,
    show_debug_info=False,
    backtest_only=False
)

[2021-09-13 19:31:33.564261] INFO: moduleinvoker: instruments.v2 开始运行..

[2021-09-13 19:31:33.599303] INFO: moduleinvoker: instruments.v2 运行完成[0.035041s].

[2021-09-13 19:31:33.603976] INFO: moduleinvoker: use_datasource.v1 开始运行..

[2021-09-13 19:31:33.850416] INFO: moduleinvoker: use_datasource.v1 运行完成[0.24644s].

[2021-09-13 19:31:33.872964] INFO: moduleinvoker: hfbacktest.v1 开始运行..

[2021-09-13 19:31:33.877631] INFO: hfbacktest: biglearning V1.2.5

[2021-09-13 19:31:33.878733] INFO: hfbacktest: bigtrader v1.7.8

[2021-09-13 19:31:33.931726] INFO: moduleinvoker: cached.v2 开始运行..

[2021-09-13 19:31:34.249566] INFO: moduleinvoker: cached.v2 运行完成[0.317838s].

[2021-09-13 19:31:34.297988] INFO: moduleinvoker: cached.v2 开始运行..

[2021-09-13 19:31:34.636799] INFO: moduleinvoker: cached.v2 运行完成[0.338807s].

[2021-09-13 19:31:34.696575] INFO: moduleinvoker: cached.v2 开始运行..

[2021-09-13 19:31:35.174397] INFO: moduleinvoker: cached.v2 运行完成[0.477826s].

[2021-09-13 19:31:45.693420] INFO: hfbacktest: backtest done, raw_perf_ds:DataSource(45642a1e2a0d4fb2b5f7ff6a8bb03e1dT)

[2021-09-13 19:31:46.189608] INFO: moduleinvoker: hfbacktest.v1 运行完成[12.31663s].

[2021-09-13 19:31:46.191441] INFO: moduleinvoker: hftrade.v1 运行完成[12.335341s].

2021-09-13 19:31:35.239618 run trading v1.7.8 
2021-09-13 19:31:35.240254 init history datas... 
2021-09-13 19:31:35.249282 init trading env... 

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