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    {"description":"实验创建于2017/8/26","graph":{"edges":[{"to_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-15:instruments","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-8:data"},{"to_node_id":"-215:instruments","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-8:data"},{"to_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-53:data1","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-15:data"},{"to_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43:features","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24:data"},{"to_node_id":"-215:features","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24:data"},{"to_node_id":"-222:features","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24:data"},{"to_node_id":"-231:features","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24:data"},{"to_node_id":"-238:features","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24:data"},{"to_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-60:model","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43:model"},{"to_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-84:input_data","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-53:data"},{"to_node_id":"-231:instruments","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-62:data"},{"to_node_id":"-250:instruments","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-62:data"},{"to_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43:training_ds","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-84:data"},{"to_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-60:data","from_node_id":"-86:data"},{"to_node_id":"-222:input_data","from_node_id":"-215:data"},{"to_node_id":"-733:input_data","from_node_id":"-222:data"},{"to_node_id":"-238:input_data","from_node_id":"-231:data"},{"to_node_id":"-1003:input_data","from_node_id":"-238:data"},{"to_node_id":"-987:input_ds","from_node_id":"-733:data"},{"to_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-53:data2","from_node_id":"-987:sorted_data"},{"to_node_id":"-250:options_data","from_node_id":"-987:sorted_data"},{"to_node_id":"-1009:input_ds","from_node_id":"-1003:data"},{"to_node_id":"-86:input_data","from_node_id":"-1009:sorted_data"}],"nodes":[{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-8","module_id":"BigQuantSpace.instruments.instruments-v2","parameters":[{"name":"start_date","value":"2019-01-01","type":"Literal","bound_global_parameter":null},{"name":"end_date","value":"2019-12-30","type":"Literal","bound_global_parameter":null},{"name":"market","value":"CN_STOCK_A","type":"Literal","bound_global_parameter":null},{"name":"instrument_list","value":"\n","type":"Literal","bound_global_parameter":null},{"name":"max_count","value":"0","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"rolling_conf","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-8"}],"output_ports":[{"name":"data","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-8"}],"cacheable":true,"seq_num":1,"comment":"","comment_collapsed":true},{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-15","module_id":"BigQuantSpace.advanced_auto_labeler.advanced_auto_labeler-v2","parameters":[{"name":"label_expr","value":"# 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多个特征，每行一个，可以包含基础特征和衍生特征\n#return_5\n#pe_ttm_0\n\n#high_0/adjust_factor_0\n#low_0/adjust_factor_0\n\n#timeperiod移动平均线\n#zhouma34=ta_ma(close_0, timeperiod=166)/adjust_factor_0\nzhouma34=ta_ma(close_0, timeperiod=166)\n#timeperiod移动平均线\nzhouma55=ta_ma(close_0, timeperiod=258)\n\n#ts_max(high_0,10)/adjust_factor_0\n#ts_min(low_0,10)/adjust_factor_0\n\n#4年高点，1年按258个交易日算\nisgaodian=where(ts_argmax(high_0, 258*5)<200.0,1,0)\n#1年低点，1年按258个交易日算\n\nisdidian=where(ts_argmin(low_0, 258*1)<100.0,1,0)\n\n#半年高点，1年按258个交易日算\nisbanniangaodian=where(ts_argmax(high_0, 128)<80.0,1,0)\n#在周34-55均线区间，日166-258\niszaiquejian=where((close_0<zhouma34) & (close_0>zhouma55),1,0)\n#曾经前几天下过55线，触碰过日258线\nisdiyu258=where(ts_min(low_0, 3)<zhouma55,1,0)\n\n#tmax=ts_argmax(high_0, 258*5)\n\n#反弹比例,选比例最高的10-20只交易，后面调试\nyiniandadian=ts_min(low_0, 258*1)\nbianniangaodian=ts_max(high_0, 128*1)\nfantanbili=bianniangaodian/yiniandadian\n\n#排除ST\nst_status_0\n#时间序列函数， d 天内的最大值\n#ts_max(high_0, 258*4)\n#时间序列函数， d 天内的最小值\n#ts_min(low_0, 258*1)\n\n\n\n#isxiadie=where(ts_max(high_0, 258*4)>ts_min(low_0, 258*1),1,0)\n","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"features_ds","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24"}],"output_ports":[{"name":"data","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-24"}],"cacheable":true,"seq_num":3,"comment":"","comment_collapsed":true},{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43","module_id":"BigQuantSpace.stock_ranker_train.stock_ranker_train-v5","parameters":[{"name":"learning_algorithm","value":"排序","type":"Literal","bound_global_parameter":null},{"name":"number_of_leaves","value":30,"type":"Literal","bound_global_parameter":null},{"name":"minimum_docs_per_leaf","value":1000,"type":"Literal","bound_global_parameter":null},{"name":"number_of_trees","value":20,"type":"Literal","bound_global_parameter":null},{"name":"learning_rate","value":0.1,"type":"Literal","bound_global_parameter":null},{"name":"max_bins","value":1023,"type":"Literal","bound_global_parameter":null},{"name":"feature_fraction","value":1,"type":"Literal","bound_global_parameter":null},{"name":"m_lazy_run","value":"False","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"training_ds","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43"},{"name":"features","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43"},{"name":"test_ds","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43"},{"name":"base_model","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43"}],"output_ports":[{"name":"model","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43"},{"name":"feature_gains","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43"},{"name":"m_lazy_run","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-43"}],"cacheable":true,"seq_num":6,"comment":"","comment_collapsed":true},{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-53","module_id":"BigQuantSpace.join.join-v3","parameters":[{"name":"on","value":"date,instrument","type":"Literal","bound_global_parameter":null},{"name":"how","value":"inner","type":"Literal","bound_global_parameter":null},{"name":"sort","value":"False","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"data1","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-53"},{"name":"data2","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-53"}],"output_ports":[{"name":"data","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-53"}],"cacheable":true,"seq_num":7,"comment":"","comment_collapsed":true},{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-60","module_id":"BigQuantSpace.stock_ranker_predict.stock_ranker_predict-v5","parameters":[{"name":"m_lazy_run","value":"False","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"model","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-60"},{"name":"data","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-60"}],"output_ports":[{"name":"predictions","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-60"},{"name":"m_lazy_run","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-60"}],"cacheable":true,"seq_num":8,"comment":"","comment_collapsed":true},{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-62","module_id":"BigQuantSpace.instruments.instruments-v2","parameters":[{"name":"start_date","value":"2019-01-01","type":"Literal","bound_global_parameter":"交易日期"},{"name":"end_date","value":"2019-12-30","type":"Literal","bound_global_parameter":"交易日期"},{"name":"market","value":"CN_STOCK_A","type":"Literal","bound_global_parameter":null},{"name":"instrument_list","value":"","type":"Literal","bound_global_parameter":null},{"name":"max_count","value":"0","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"rolling_conf","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-62"}],"output_ports":[{"name":"data","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-62"}],"cacheable":true,"seq_num":9,"comment":"预测数据，用于回测和模拟","comment_collapsed":false},{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-84","module_id":"BigQuantSpace.dropnan.dropnan-v1","parameters":[],"input_ports":[{"name":"input_data","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-84"}],"output_ports":[{"name":"data","node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-84"}],"cacheable":true,"seq_num":13,"comment":"","comment_collapsed":true},{"node_id":"-86","module_id":"BigQuantSpace.dropnan.dropnan-v1","parameters":[],"input_ports":[{"name":"input_data","node_id":"-86"}],"output_ports":[{"name":"data","node_id":"-86"}],"cacheable":true,"seq_num":14,"comment":"","comment_collapsed":true},{"node_id":"-215","module_id":"BigQuantSpace.general_feature_extractor.general_feature_extractor-v7","parameters":[{"name":"start_date","value":"","type":"Literal","bound_global_parameter":null},{"name":"end_date","value":"","type":"Literal","bound_global_parameter":null},{"name":"before_start_days","value":"2500","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"instruments","node_id":"-215"},{"name":"features","node_id":"-215"}],"output_ports":[{"name":"data","node_id":"-215"}],"cacheable":true,"seq_num":15,"comment":"","com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回测引擎：初始化函数，只执行一次\ndef bigquant_run(context):\n print('初始化函数，只执行一次')\n # 加载预测数据\n context.ranker_prediction = context.options['data'].read_df()\n\n # 系统已经设置了默认的交易手续费和滑点，要修改手续费可使用如下函数\n context.set_commission(PerOrder(buy_cost=0.0003, sell_cost=0.0013, min_cost=5))\n # 预测数据，通过options传入进来，使用 read_df 函数，加载到内存 (DataFrame)\n # 设置买入的股票数量，这里买入预测股票列表排名靠前的5只\n stock_count = 10\n # 每只的股票的权重，如下的权重分配会使得靠前的股票分配多一点的资金，[0.339160, 0.213986, 0.169580, ..]\n context.stock_weights = T.norm([1 / math.log(i + 2) for i in range(0, stock_count)])\n # 设置每只股票占用的最大资金比例\n context.max_cash_per_instrument = 0.1\n context.options['hold_days'] = 5\n","type":"Literal","bound_global_parameter":null},{"name":"handle_data","value":"# 回测引擎：每日数据处理函数，每天执行一次\ndef bigquant_run(context, data):\n # 按日期过滤得到今日的预测数据\n ranker_prediction = context.ranker_prediction[\n context.ranker_prediction.date == data.current_dt.strftime('%Y-%m-%d')]\n \n today = data.current_dt.strftime('%Y-%m-%d')\n #print('日期:',today)\n # 1. 资金分配\n # 平均持仓时间是hold_days，每日都将买入股票，每日预期使用 1/hold_days 的资金\n # 实际操作中，会存在一定的买入误差，所以在前hold_days天，等量使用资金；之后，尽量使用剩余资金（这里设置最多用等量的1.5倍）\n is_staging = context.trading_day_index < context.options['hold_days'] # 是否在建仓期间（前 hold_days 天）\n cash_avg = context.portfolio.portfolio_value / context.options['hold_days']\n #print('context.portfolio.portfolio_value:',context.portfolio.portfolio_value)\n cash_for_buy = min(context.portfolio.cash, (1 if is_staging else 1.5) * cash_avg)\n #print('cash_for_buy:',cash_for_buy,' context.portfolio.cash:',context.portfolio.cash)\n cash_for_sell = cash_avg - (context.portfolio.cash - cash_for_buy)\n #print('context.portfolio.portfolio_value:',context.portfolio.portfolio_value)\n positions = {e.symbol: p.amount * p.last_sale_price\n for e, p in context.portfolio.positions.items()}\n #print('is_staging:',is_staging,' cash_for_sell:',cash_for_sell)\n\n # 2. 生成卖出订单：hold_days天之后才开始卖出；对持仓的股票，按机器学习算法预测的排序末位淘汰\n if not is_staging and cash_for_sell > 0:\n equities = {e.symbol: e for e, p in context.portfolio.positions.items()}\n print(today,' equities:',equities)\n instruments = list(reversed(list(ranker_prediction.instrument[ranker_prediction.instrument.apply(\n lambda x: x in equities)])))\n\n print('sell instruments:',instruments)\n for instrument in instruments:\n context.order_target(context.symbol(instrument), 0)\n cash_for_sell -= positions[instrument]\n print(today,' instrument 滚动卖出 :',instrument,'context.symbol(instrument):',context.symbol(instrument))\n if cash_for_sell <= 0:\n break\n \n #加上持仓超过50天或者收益大于20%卖出\n if len(equities) > 0:\n for i in equities.keys():\n stock_market_price = data.current(context.symbol(i), 'price') # 最新市场价格\n stock_market_today_high = data.current(context.symbol(i), 'high') #今日最高价 \n stock_market_today_close = data.current(context.symbol(i), 'close') #今日收盘价\n last_sale_date = equities[i].last_sale_date # 上次交易日期\n last_cost_price = equities[i].cost_basis # 上次交易金额\n delta_days = data.current_dt - last_sale_date \n hold_days = delta_days.days # 持仓天数\n if hold_days>=50 :\n context.order_target(context.symbol(i), 0)\n print(today,' 盈利或者超期卖出 :',equities[i],' context.symbol(i):',context.symbol(i))\n \n\n # 3. 生成买入订单：按机器学习算法预测的排序，买入前面的stock_count只股票\n buy_cash_weights = context.stock_weights\n buy_instruments = list(ranker_prediction.instrument[:len(buy_cash_weights)])\n print('buy_instruments:',buy_instruments,'buy_cash_weights:',buy_cash_weights,'ranker_prediction:',ranker_prediction)\n max_cash_per_instrument = context.portfolio.portfolio_value * context.max_cash_per_instrument\n for i, instrument in enumerate(buy_instruments):\n cash = cash_for_buy * buy_cash_weights[i]\n if cash > max_cash_per_instrument - positions.get(instrument, 0):\n # 确保股票持仓量不会超过每次股票最大的占用资金量\n cash = max_cash_per_instrument - positions.get(instrument, 0)\n if cash > 0:\n context.order_value(context.symbol(instrument), cash)\n print(today,' 买入 ',instrument)\n","type":"Literal","bound_global_parameter":null},{"name":"prepare","value":"# 回测引擎：准备数据，只执行一次\ndef bigquant_run(context):\n # 加载预测数据\n print('准备数据，只执行一次')\n df = context.options['data'].read_df()\n # 函数：求满足开仓条件的股票列表\n def open_pos_con(df):\n return list(df[df['fantanbili']>0].instrument)\n # 函数：求满足平仓条件的股票列表\n def close_pos_con(df):\n return list(df[df['fantanbili']>0].instrument)\n \n # 每日卖出股票的数据框\n context.daily_sell_stock= df.groupby('date').apply(close_pos_con) \n # 每日买入股票的数据框\n context.daily_buy_stock= df.groupby('date').apply(open_pos_con) \n","type":"Literal","bound_global_parameter":null},{"name":"before_trading_start","value":"","type":"Literal","bound_global_parameter":null},{"name":"volume_limit","value":0.025,"type":"Literal","bound_global_parameter":null},{"name":"order_price_field_buy","value":"open","type":"Literal","bound_global_parameter":null},{"name":"order_price_field_sell","value":"close","type":"Literal","bound_global_parameter":null},{"name":"capital_base","value":1000000,"type":"Literal","bound_global_parameter":null},{"name":"auto_cancel_non_tradable_orders","value":"True","type":"Literal","bound_global_parameter":null},{"name":"data_frequency","value":"daily","type":"Literal","bound_global_parameter":null},{"name":"price_type","value":"真实价格","type":"Literal","bound_global_parameter":null},{"name":"product_type","value":"股票","type":"Literal","bound_global_parameter":null},{"name":"plot_charts","value":"True","type":"Literal","bound_global_parameter":null},{"name":"backtest_only","value":"False","type":"Literal","bound_global_parameter":null},{"name":"benchmark","value":"000300.HIX","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"instruments","node_id":"-250"},{"name":"options_data","node_id":"-250"},{"name":"history_ds","node_id":"-250"},{"name":"benchmark_ds","node_id":"-250"},{"name":"trading_calendar","node_id":"-250"}],"output_ports":[{"name":"raw_perf","node_id":"-250"}],"cacheable":false,"seq_num":19,"comment":"","comment_collapsed":true},{"node_id":"-733","module_id":"BigQuantSpace.filter.filter-v3","parameters":[{"name":"expr","value":"isgaodian==1&isdidian==1&isbanniangaodian==1&iszaiquejian==1&st_status_0==0&isdiyu258==1","type":"Literal","bound_global_parameter":null},{"name":"output_left_data","value":"True","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"input_data","node_id":"-733"}],"output_ports":[{"name":"data","node_id":"-733"},{"name":"left_data","node_id":"-733"}],"cacheable":true,"seq_num":5,"comment":"","comment_collapsed":true},{"node_id":"-987","module_id":"BigQuantSpace.sort.sort-v5","parameters":[{"name":"sort_by","value":"fantanbili","type":"Literal","bound_global_parameter":null},{"name":"group_by","value":"date","type":"Literal","bound_global_parameter":null},{"name":"keep_columns","value":"--","type":"Literal","bound_global_parameter":null},{"name":"ascending","value":"False","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"input_ds","node_id":"-987"},{"name":"sort_by_ds","node_id":"-987"}],"output_ports":[{"name":"sorted_data","node_id":"-987"}],"cacheable":true,"seq_num":10,"comment":"","comment_collapsed":true},{"node_id":"-1003","module_id":"BigQuantSpace.filter.filter-v3","parameters":[{"name":"expr","value":"isgaodian==1&isdidian==1&isbanniangaodian==1&iszaiquejian==1&st_status_0==0&isdiyu258==1","type":"Literal","bound_global_parameter":null},{"name":"output_left_data","value":"True","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"input_data","node_id":"-1003"}],"output_ports":[{"name":"data","node_id":"-1003"},{"name":"left_data","node_id":"-1003"}],"cacheable":true,"seq_num":12,"comment":"","comment_collapsed":true},{"node_id":"-1009","module_id":"BigQuantSpace.sort.sort-v5","parameters":[{"name":"sort_by","value":"fantanbili","type":"Literal","bound_global_parameter":null},{"name":"group_by","value":"date","type":"Literal","bound_global_parameter":null},{"name":"keep_columns","value":"--","type":"Literal","bound_global_parameter":null},{"name":"ascending","value":"False","type":"Literal","bound_global_parameter":null}],"input_ports":[{"name":"input_ds","node_id":"-1009"},{"name":"sort_by_ds","node_id":"-1009"}],"output_ports":[{"name":"sorted_data","node_id":"-1009"}],"cacheable":true,"seq_num":20,"comment":"","comment_collapsed":true}],"node_layout":"<node_postions><node_position 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    In [24]:
    # 本代码由可视化策略环境自动生成 2022年3月24日 15:12
# 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。


# 回测引擎：初始化函数，只执行一次
def m19_initialize_bigquant_run(context):
    print('初始化函数，只执行一次')
    # 加载预测数据
    context.ranker_prediction = context.options['data'].read_df()

    # 系统已经设置了默认的交易手续费和滑点，要修改手续费可使用如下函数
    context.set_commission(PerOrder(buy_cost=0.0003, sell_cost=0.0013, min_cost=5))
    # 预测数据，通过options传入进来，使用 read_df 函数，加载到内存 (DataFrame)
    # 设置买入的股票数量，这里买入预测股票列表排名靠前的5只
    stock_count = 10
    # 每只的股票的权重，如下的权重分配会使得靠前的股票分配多一点的资金，[0.339160, 0.213986, 0.169580, ..]
    context.stock_weights = T.norm([1 / math.log(i + 2) for i in range(0, stock_count)])
    # 设置每只股票占用的最大资金比例
    context.max_cash_per_instrument = 0.1
    context.options['hold_days'] = 5

# 回测引擎：每日数据处理函数，每天执行一次
def m19_handle_data_bigquant_run(context, data):
    # 按日期过滤得到今日的预测数据
    ranker_prediction = context.ranker_prediction[
        context.ranker_prediction.date == data.current_dt.strftime('%Y-%m-%d')]
    
    today = data.current_dt.strftime('%Y-%m-%d')
    #print('日期:',today)
    # 1. 资金分配
    # 平均持仓时间是hold_days，每日都将买入股票，每日预期使用 1/hold_days 的资金
    # 实际操作中，会存在一定的买入误差，所以在前hold_days天，等量使用资金；之后，尽量使用剩余资金（这里设置最多用等量的1.5倍）
    is_staging = context.trading_day_index < context.options['hold_days'] # 是否在建仓期间（前 hold_days 天）
    cash_avg = context.portfolio.portfolio_value / context.options['hold_days']
    #print('context.portfolio.portfolio_value:',context.portfolio.portfolio_value)
    cash_for_buy = min(context.portfolio.cash, (1 if is_staging else 1.5) * cash_avg)
    #print('cash_for_buy:',cash_for_buy,' context.portfolio.cash:',context.portfolio.cash)
    cash_for_sell = cash_avg - (context.portfolio.cash - cash_for_buy)
    #print('context.portfolio.portfolio_value:',context.portfolio.portfolio_value)
    positions = {e.symbol: p.amount * p.last_sale_price
                 for e, p in context.portfolio.positions.items()}
    #print('is_staging:',is_staging,' cash_for_sell:',cash_for_sell)

    # 2. 生成卖出订单：hold_days天之后才开始卖出；对持仓的股票，按机器学习算法预测的排序末位淘汰
    if not is_staging and cash_for_sell > 0:
        equities = {e.symbol: e for e, p in context.portfolio.positions.items()}
        print(today,' equities:',equities)
        instruments = list(reversed(list(ranker_prediction.instrument[ranker_prediction.instrument.apply(
                lambda x: x in equities)])))

        print('sell instruments:',instruments)
        for instrument in instruments:
            context.order_target(context.symbol(instrument), 0)
            cash_for_sell -= positions[instrument]
            print(today,' instrument 滚动卖出 :',instrument,'context.symbol(instrument):',context.symbol(instrument))
            if cash_for_sell <= 0:
                break
                
         #加上持仓超过50天或者收益大于20%卖出
        if len(equities) > 0:
            for i in equities.keys():
                stock_market_price = data.current(context.symbol(i), 'price')  # 最新市场价格
                stock_market_today_high = data.current(context.symbol(i), 'high') #今日最高价      
                stock_market_today_close = data.current(context.symbol(i), 'close') #今日收盘价
                last_sale_date = equities[i].last_sale_date   # 上次交易日期
                last_cost_price = equities[i].cost_basis # 上次交易金额
                delta_days = data.current_dt - last_sale_date  
                hold_days = delta_days.days # 持仓天数
                if hold_days>=50 :
                    context.order_target(context.symbol(i), 0)
                    print(today,' 盈利或者超期卖出 :',equities[i],' context.symbol(i):',context.symbol(i))
                

    # 3. 生成买入订单：按机器学习算法预测的排序，买入前面的stock_count只股票
    buy_cash_weights = context.stock_weights
    buy_instruments = list(ranker_prediction.instrument[:len(buy_cash_weights)])
    print('buy_instruments:',buy_instruments,'buy_cash_weights:',buy_cash_weights,'ranker_prediction:',ranker_prediction)
    max_cash_per_instrument = context.portfolio.portfolio_value * context.max_cash_per_instrument
    for i, instrument in enumerate(buy_instruments):
        cash = cash_for_buy * buy_cash_weights[i]
        if cash > max_cash_per_instrument - positions.get(instrument, 0):
            # 确保股票持仓量不会超过每次股票最大的占用资金量
            cash = max_cash_per_instrument - positions.get(instrument, 0)
        if cash > 0:
            context.order_value(context.symbol(instrument), cash)
            print(today,' 买入 ',instrument)

# 回测引擎：准备数据，只执行一次
def m19_prepare_bigquant_run(context):
    # 加载预测数据
    print('准备数据，只执行一次')
    df = context.options['data'].read_df()
    # 函数：求满足开仓条件的股票列表
    def open_pos_con(df):
        return list(df[df['fantanbili']>0].instrument)
    # 函数：求满足平仓条件的股票列表
    def close_pos_con(df):
        return list(df[df['fantanbili']>0].instrument)
    
    # 每日卖出股票的数据框
    context.daily_sell_stock= df.groupby('date').apply(close_pos_con)  
    # 每日买入股票的数据框
    context.daily_buy_stock= df.groupby('date').apply(open_pos_con)  


m1 = M.instruments.v2(
    start_date='2019-01-01',
    end_date='2019-12-30',
    market='CN_STOCK_A',
    instrument_list="""
""",
    max_count=0
)

m2 = M.advanced_auto_labeler.v2(
    instruments=m1.data,
    label_expr="""# #号开始的表示注释
# 0. 每行一个，顺序执行，从第二个开始，可以使用label字段
# 1. 可用数据字段见 https://bigquant.com/docs/develop/datasource/deprecated/history_data.html
#   添加benchmark_前缀，可使用对应的benchmark数据
# 2. 可用操作符和函数见 `表达式引擎 <https://bigquant.com/docs/develop/bigexpr/usage.html>`_

# 计算收益：5日收盘价(作为卖出价格)除以明日开盘价(作为买入价格)
shift(close, -5) / shift(open, -1)

# 极值处理：用1%和99%分位的值做clip
clip(label, all_quantile(label, 0.01), all_quantile(label, 0.99))

# 将分数映射到分类，这里使用20个分类
all_wbins(label, 20)

# 过滤掉一字涨停的情况 (设置label为NaN，在后续处理和训练中会忽略NaN的label)
where(shift(high, -1) == shift(low, -1), NaN, label)
""",
    start_date='',
    end_date='',
    benchmark='000300.HIX',
    drop_na_label=True,
    cast_label_int=True
)

m3 = M.input_features.v1(
    features="""# #号开始的表示注释
# 多个特征，每行一个，可以包含基础特征和衍生特征
#return_5
#pe_ttm_0

#high_0/adjust_factor_0
#low_0/adjust_factor_0

#timeperiod移动平均线
#zhouma34=ta_ma(close_0, timeperiod=166)/adjust_factor_0
zhouma34=ta_ma(close_0, timeperiod=166)
#timeperiod移动平均线
zhouma55=ta_ma(close_0, timeperiod=258)

#ts_max(high_0,10)/adjust_factor_0
#ts_min(low_0,10)/adjust_factor_0

#4年高点，1年按258个交易日算
isgaodian=where(ts_argmax(high_0, 258*5)<200.0,1,0)
#1年低点，1年按258个交易日算

isdidian=where(ts_argmin(low_0, 258*1)<100.0,1,0)

#半年高点，1年按258个交易日算
isbanniangaodian=where(ts_argmax(high_0, 128)<80.0,1,0)
#在周34-55均线区间，日166-258
iszaiquejian=where((close_0<zhouma34) & (close_0>zhouma55),1,0)
#曾经前几天下过55线，触碰过日258线
isdiyu258=where(ts_min(low_0, 3)<zhouma55,1,0)

#tmax=ts_argmax(high_0, 258*5)

#反弹比例,选比例最高的10-20只交易，后面调试
yiniandadian=ts_min(low_0, 258*1)
bianniangaodian=ts_max(high_0, 128*1)
fantanbili=bianniangaodian/yiniandadian

#排除ST
st_status_0
#时间序列函数， d 天内的最大值
#ts_max(high_0, 258*4)
#时间序列函数， d 天内的最小值
#ts_min(low_0, 258*1)



#isxiadie=where(ts_max(high_0, 258*4)>ts_min(low_0, 258*1),1,0)
"""
)

m15 = M.general_feature_extractor.v7(
    instruments=m1.data,
    features=m3.data,
    start_date='',
    end_date='',
    before_start_days=2500
)

m16 = M.derived_feature_extractor.v3(
    input_data=m15.data,
    features=m3.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=True,
    remove_extra_columns=False
)

m5 = M.filter.v3(
    input_data=m16.data,
    expr='isgaodian==1&isdidian==1&isbanniangaodian==1&iszaiquejian==1&st_status_0==0&isdiyu258==1',
    output_left_data=True
)

m10 = M.sort.v5(
    input_ds=m5.data,
    sort_by='fantanbili',
    group_by='date',
    keep_columns='--',
    ascending=False
)

m7 = M.join.v3(
    data1=m2.data,
    data2=m10.sorted_data,
    on='date,instrument',
    how='inner',
    sort=False
)

m13 = M.dropnan.v1(
    input_data=m7.data
)

m6 = M.stock_ranker_train.v5(
    training_ds=m13.data,
    features=m3.data,
    learning_algorithm='排序',
    number_of_leaves=30,
    minimum_docs_per_leaf=1000,
    number_of_trees=20,
    learning_rate=0.1,
    max_bins=1023,
    feature_fraction=1,
    m_lazy_run=False
)

m9 = M.instruments.v2(
    start_date=T.live_run_param('trading_date', '2019-01-01'),
    end_date=T.live_run_param('trading_date', '2019-12-30'),
    market='CN_STOCK_A',
    instrument_list='',
    max_count=0
)

m17 = M.general_feature_extractor.v7(
    instruments=m9.data,
    features=m3.data,
    start_date='',
    end_date='',
    before_start_days=2500
)

m18 = M.derived_feature_extractor.v3(
    input_data=m17.data,
    features=m3.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=True,
    remove_extra_columns=False
)

m12 = M.filter.v3(
    input_data=m18.data,
    expr='isgaodian==1&isdidian==1&isbanniangaodian==1&iszaiquejian==1&st_status_0==0&isdiyu258==1',
    output_left_data=True
)

m20 = M.sort.v5(
    input_ds=m12.data,
    sort_by='fantanbili',
    group_by='date',
    keep_columns='--',
    ascending=False
)

m14 = M.dropnan.v1(
    input_data=m20.sorted_data
)

m8 = M.stock_ranker_predict.v5(
    model=m6.model,
    data=m14.data,
    m_lazy_run=False
)

m19 = M.trade.v4(
    instruments=m9.data,
    options_data=m10.sorted_data,
    start_date='',
    end_date='',
    initialize=m19_initialize_bigquant_run,
    handle_data=m19_handle_data_bigquant_run,
    prepare=m19_prepare_bigquant_run,
    volume_limit=0.025,
    order_price_field_buy='open',
    order_price_field_sell='close',
    capital_base=1000000,
    auto_cancel_non_tradable_orders=True,
    data_frequency='daily',
    price_type='真实价格',
    product_type='股票',
    plot_charts=True,
    backtest_only=False,
    benchmark='000300.HIX'
)

    准备数据，只执行一次

    初始化函数，只执行一次

    buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:       close_0       date     high_0  instrument       low_0  st_status_0  \
93  143.54068 2019-01-21  144.59375  002353.SZA  137.789337          0.0   

      zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
93  148.030594  139.085663          1         1                 1   

    iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
93             1          1    100.155167        189.06543    1.887725  
2019-01-21  买入  002353.SZA
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date      high_0  instrument       low_0  st_status_0  \
94  142.568619 2019-01-22  145.565811  002353.SZA  141.029526          0.0   

      zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
94  147.904205  139.229156          1         1                 1   

    iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
94             1          1    100.155167        189.06543    1.887725  
2019-01-22  买入  002353.SZA
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date      high_0  instrument       low_0  st_status_0  \
95  141.758575 2019-01-23  143.459671  002353.SZA  140.219482          0.0   

      zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
95  147.801743  139.353317          1         1                 1   

    iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
95             1          1    100.155167        189.06543    1.887725  
2019-01-23  买入  002353.SZA
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date      high_0  instrument       low_0  st_status_0  \
96  141.110535 2019-01-24  142.811646  002353.SZA  138.518372          0.0   

      zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
96  147.690475  139.478683          1         1                 1   

    iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
96             1          1    100.155167        189.06543    1.887725  
2019-01-24  买入  002353.SZA
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date     high_0  instrument       low_0  st_status_0  \
97  142.811646 2019-01-25  144.26973  002353.SZA  141.272552          0.0   

      zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
97  147.623138  139.568573          1         1                 1   

    iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
97             1          1    100.155167        189.06543    1.887725  
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date     high_0  instrument       low_0  st_status_0  \
98  141.596558 2019-01-28  144.59375  002353.SZA  141.353546          0.0   

      zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
98  147.567017  139.659042          1         1                 1   

    iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
98             1          1    100.155167        189.06543    1.887725  
2019-01-28  买入  002353.SZA
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date      high_0  instrument       low_0  st_status_0  \
99  140.300491 2019-01-29  141.677567  002353.SZA  136.169235          0.0   

      zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
99  147.521637  139.739807          1         1                 1   

    iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
99             1          1    100.155167        189.06543    1.887725  
2019-01-29  买入  002353.SZA
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:         close_0       date      high_0  instrument       low_0  st_status_0  \
100  142.568619 2019-02-11  142.973648  002353.SZA  138.923401          0.0   

       zhouma34   zhouma55  isgaodian  isdidian  isbanniangaodian  \
100  147.333267  140.00293          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
100             1          1    100.155167        189.06543    1.887725  
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:         close_0       date      high_0  instrument       low_0  st_status_0  \
101  146.375854 2019-02-12  146.375854  002353.SZA  141.029526          0.0   

       zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
101  147.312286  140.098831          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
101             1          1    100.155167        189.06543    1.887725  
buy_instruments: ['002353.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:         close_0       date      high_0  instrument      low_0  st_status_0  \
102  146.942886 2019-02-13  147.995956  002353.SZA  144.91777          0.0   

       zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
102  147.320099  140.214386          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
102             1          1    100.155167        189.06543    1.887725  
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []

    buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: ['300052.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date     high_0  instrument     low_0  st_status_0  \
103  27.488829 2019-07-05  27.622921  300052.SZA  27.14019          0.0   

      zhouma34   zhouma55  isgaodian  isdidian  isbanniangaodian  \
103  27.637466  27.399664          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
103             1          1     20.393978        38.539799    1.889764  
2019-07-05  买入  300052.SZA
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: ['000788.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date     high_0  instrument      low_0  st_status_0  \
104  23.650465 2019-08-01  24.025869  000788.SZA  23.387682          0.0   

      zhouma34   zhouma55  isgaodian  isdidian  isbanniangaodian  \
104  24.264864  23.620771          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
104             1          1      17.06823        36.606861    2.144737  
2019-08-01  买入  000788.SZA
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: ['601901.SHA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:       close_0       date    high_0  instrument     low_0  st_status_0  \
105  6.747332 2019-08-06  6.860992  601901.SHA  6.530342          0.0   

     zhouma34  zhouma55  isgaodian  isdidian  isbanniangaodian  iszaiquejian  \
105  7.111844  6.691337          1         1                 1             1   

     isdiyu258  yiniandadian  bianniangaodian  fantanbili  
105          1      4.577439         9.092881    1.986456  
2019-08-06  买入  601901.SHA
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: ['601901.SHA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:       close_0       date    high_0  instrument     low_0  st_status_0  \
106  6.767997 2019-08-08  6.891991  601901.SHA  6.736999          0.0   

     zhouma34  zhouma55  isgaodian  isdidian  isbanniangaodian  iszaiquejian  \
106  7.123857  6.692015          1         1                 1             1   

     isdiyu258  yiniandadian  bianniangaodian  fantanbili  
106          1      4.577439         9.092881    1.986456  
2019-08-08  买入  601901.SHA

    buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: ['601901.SHA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:       close_0       date    high_0  instrument     low_0  st_status_0  \
107  6.819897 2019-08-12  6.830277  601901.SHA  6.726473          0.0   

     zhouma34  zhouma55  isgaodian  isdidian  isbanniangaodian  iszaiquejian  \
107  7.134998  6.691733          1         1                 1             1   

     isdiyu258  yiniandadian  bianniangaodian  fantanbili  
107          1      4.577439         9.092881    1.986456  
buy_instruments: ['601901.SHA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:       close_0       date    high_0  instrument     low_0  st_status_0  \
108  6.788755 2019-08-13  6.799136  601901.SHA  6.736854          0.0   

     zhouma34  zhouma55  isgaodian  isdidian  isbanniangaodian  iszaiquejian  \
108  7.142032  6.690533          1         1                 1             1   

     isdiyu258  yiniandadian  bianniangaodian  fantanbili  
108          1      4.577439         9.092881    1.986456  
2019-08-13  买入  601901.SHA
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: ['601901.SHA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:       close_0       date    high_0  instrument     low_0  st_status_0  \
109  6.799136 2019-08-15  6.819897  601901.SHA  6.591528          0.0   

     zhouma34  zhouma55  isgaodian  isdidian  isbanniangaodian  iszaiquejian  \
109  7.156723  6.688254          1         1                 1             1   

     isdiyu258  yiniandadian  bianniangaodian  fantanbili  
109          1      4.577439         9.092881    1.986456  
2019-08-15  买入  601901.SHA
buy_instruments: ['601901.SHA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:       close_0       date    high_0  instrument     low_0  st_status_0  \
110  6.799136 2019-08-16  6.892559  601901.SHA  6.778375          0.0   

     zhouma34  zhouma55  isgaodian  isdidian  isbanniangaodian  iszaiquejian  \
110  7.164381  6.687375          1         1                 1             1   

     isdiyu258  yiniandadian  bianniangaodian  fantanbili  
110          1      4.577439         9.092881    1.986456  
buy_instruments: ['601901.SHA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:       close_0       date    high_0  instrument     low_0  st_status_0  \
111  7.131307 2019-08-19  7.141688  601901.SHA  6.809516          0.0   

     zhouma34  zhouma55  isgaodian  isdidian  isbanniangaodian  iszaiquejian  \
111  7.173976  6.687743          1         1                 1             1   

     isdiyu258  yiniandadian  bianniangaodian  fantanbili  
111          1      4.577439         9.092881    1.986456  
buy_instruments: ['000788.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date     high_0  instrument     low_0  st_status_0  \
112  23.575384 2019-08-20  23.800627  000788.SZA  23.23752          0.0   

      zhouma34   zhouma55  isgaodian  isdidian  isbanniangaodian  \
112  24.424109  23.470503          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
112             1          1      17.06823        36.606861    2.144737  
2019-08-20  买入  000788.SZA
buy_instruments: ['000788.SZA', '300052.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date     high_0  instrument      low_0  st_status_0  \
113  23.688005 2019-08-21  23.838167  000788.SZA  23.387682          0.0   
114  27.488829 2019-08-21  28.427473  300052.SZA  27.354738          0.0   

      zhouma34   zhouma55  isgaodian  isdidian  isbanniangaodian  \
113  24.447977  23.464680          1         1                 1   
114  27.810076  27.056776          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
113             1          1     17.068230        36.606861    2.144737  
114             1          1     20.393978        38.539799    1.889764  
2019-08-21  买入  300052.SZA
buy_instruments: ['000788.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date     high_0  instrument      low_0  st_status_0  \
115  23.537844 2019-08-22  23.688005  000788.SZA  23.387682          0.0   

      zhouma34   zhouma55  isgaodian  isdidian  isbanniangaodian  \
115  24.471617  23.460449          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
115             1          1      17.06823        36.606861    2.144737  
buy_instruments: ['000788.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:        close_0       date    high_0  instrument      low_0  st_status_0  \
116  23.875708 2019-08-23  24.06341  000788.SZA  23.462763          0.0   

      zhouma34   zhouma55  isgaodian  isdidian  isbanniangaodian  \
116  24.497293  23.458691          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
116             1          1      17.06823        36.606861    2.144737  
buy_instruments: ['000788.SZA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:       close_0       date     high_0  instrument     low_0  st_status_0  \
117  24.10095 2019-08-26  25.001919  000788.SZA  23.23752          0.0   

      zhouma34   zhouma55  isgaodian  isdidian  isbanniangaodian  \
117  24.525002  23.459253          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
117             1          1      17.06823        36.606861    2.144737  
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: [] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction: Empty DataFrame
Columns: [close_0, date, high_0, instrument, low_0, st_status_0, zhouma34, zhouma55, isgaodian, isdidian, isbanniangaodian, iszaiquejian, isdiyu258, yiniandadian, bianniangaodian, fantanbili]
Index: []
buy_instruments: ['600016.SHA'] buy_cash_weights: [0.22009176629808014, 0.1388624438735545, 0.11004588314904007, 0.09478836436955078, 0.08514311764162097, 0.07839826897867533, 0.07336392209936006, 0.06943122193677725, 0.06625422345438903, 0.0636207881989517] ranker_prediction:         close_0       date      high_0  instrument       low_0  st_status_0  \
118  151.527328 2019-09-02  152.300415  600016.SHA  149.981125          0.0   

       zhouma34    zhouma55  isgaodian  isdidian  isbanniangaodian  \
118  152.001816  150.550476          1         1                 1   

     iszaiquejian  isdiyu258  yiniandadian  bianniangaodian  fantanbili  
118             1          1    136.204605       168.913239    1.240143  
2019-09-02  买入  600016.SHA
2019-09-03  equities: {'002353.SZA': Equity(2924 [002353.SZA]), '300052.SZA': Equity(868 [300052.SZA]), '000788.SZA': Equity(2748 [000788.SZA]), '601901.SHA': Equity(524 [601901.SHA]), '600016.SHA': Equity(2754 [600016.SHA])}
sell instruments: ['600016.SHA', '300052.SZA']
2019-09-03  instrument 滚动卖出 : 600016.SHA context.symbol(instrument): Equity(2754 [600016.SHA])

    ---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-24-f99b5e77271b> in <module>
    203 )
    204 
--> 205 m19 = M.trade.v4(
    206     instruments=m9.data,
    207     options_data=m10.sorted_data,

<ipython-input-24-f99b5e77271b> in m19_handle_data_bigquant_run(context, data)
     63                 stock_market_today_high = data.current(context.symbol(i), 'high') #今日最高价
     64                 stock_market_today_close = data.current(context.symbol(i), 'close') #今日收盘价
---> 65                 last_sale_date = equities[i].last_sale_date   # 上次交易日期
     66                 last_cost_price = equities[i].cost_basis # 上次交易金额
     67                 delta_days = data.current_dt - last_sale_date

AttributeError: 'zipline.assets._assets.Equity' object has no attribute 'last_sale_date'
    In [ ]:
    m10.sorted_data.read_df()