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# 本代码由可视化策略环境自动生成 2020年9月23日 14:48
# 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：每日数据处理函数，每天执行一次
def m2_handle_data_bigquant_run(context, data):
    
    # 1. 按每个K线递增，记录策略运行天数
    context.extension['index']  += 1
    
    # 2. 每隔22个交易日进行换仓
    if context.extension['index'] % context.rebalance_days != 1:
        return 
    
    # 3. 买入股票列表
    stock_to_buy = context.daily_stock_buy.ix[ata.current_dt.strftime('%Y-%m-%d')]
    
    # 4. 当前持仓列表    
    stock_hold_now = [equity.symbol for equity in context.portfolio.positions]

    # 5. 卖出股票列表 
    stock_to_sell = [i for i in stock_hold_now if i not in no_need_to_sell]
    
    # 6. 执行卖出
    for stock in stock_to_sell:
        if data.can_trade(context.symbol(stock)):
            context.order_target_percent(context.symbol(stock), 0)
            
    # 7. 执行买入
    if len(stock_to_buy)>0: 
        weight = 1 / len(stock_to_buy) # 等权重
        for  instrument in stock_to_buy:
            if data.can_trade(context.symbol(instrument)):
                context.order_target_percent(context.symbol(instrument), weight)
# 回测引擎：准备数据，只执行一次
def m2_prepare_bigquant_run(context):
    # 加载股票指标数据,数据继承自m4模块
    context.indicator_data = context.options['data'].read_df()

     # 设置股票数量
    context.stock_num = 30
    
    def open_pos_con(df):
        return list(df.instrument)[:context.stock_num]
    
    # 计算每日股票买入列表
    context.daily_stock_buy = context.indicator_data.groupby('date').apply(open_pos_con)
    
    # 调仓天数,22个交易日大概就是一个月。可以理解为一个月换仓一次
    context.rebalance_days = 22
    

# 回测引擎：初始化函数，只执行一次
def m2_initialize_bigquant_run(context):
    
    # 设置交易费用，买入是万三，卖出是千分之1.3，如果不足5元按5元算
    context.set_commission(PerOrder(buy_cost=0.0003, sell_cost=0.0013, min_cost=5))
    
    # 如果策略运行中，需要将数据(比如运行天数)进行保存，可以借用extension这个对象，类型为dict
    if 'index' not in context.extension:
        context.extension['index'] = 0

m3 = M.instruments.v2(
    start_date='2015-01-01',
    end_date='2019-04-23',
    market='CN_STOCK_A',
    instrument_list=''
)

m5 = M.input_features.v1(
    features="""pb_lf_0
pe_ttm_0
amount_0"""
)

m1 = M.general_feature_extractor.v7(
    instruments=m3.data,
    features=m5.data,
    start_date='',
    end_date='',
    before_start_days=90
)

m6 = M.sort.v4(
    input_ds=m1.data,
    sort_by='pe_ttm_0,pb_lf_0',
    group_by='date',
    keep_columns='--',
    ascending=True
)

m4 = M.filter.v3(
    input_data=m6.data_1,
    expr='pb_lf_0 < 1.5 & pe_ttm_0 < 15 & amount_0 > 0 & pb_lf_0 > 0 & pe_ttm_0 > 0',
    output_left_data=False
)

m2 = M.trade.v4(
    instruments=m3.data,
    options_data=m4.data,
    start_date='',
    end_date='',
    handle_data=m2_handle_data_bigquant_run,
    prepare=m2_prepare_bigquant_run,
    initialize=m2_initialize_bigquant_run,
    volume_limit=0.025,
    order_price_field_buy='open',
    order_price_field_sell='open',
    capital_base=1000000,
    auto_cancel_non_tradable_orders=True,
    data_frequency='daily',
    price_type='后复权',
    product_type='股票',
    plot_charts=True,
    backtest_only=False,
    benchmark=''
)

[2019-06-20 18:07:05.191215] INFO: bigquant: instruments.v2 开始运行..

[2019-06-20 18:07:05.276608] INFO: bigquant: 命中缓存

[2019-06-20 18:07:05.279447] INFO: bigquant: instruments.v2 运行完成[0.088224s].

[2019-06-20 18:07:05.283478] INFO: bigquant: input_features.v1 开始运行..

[2019-06-20 18:07:05.350128] INFO: bigquant: 命中缓存

[2019-06-20 18:07:05.354298] INFO: bigquant: input_features.v1 运行完成[0.070815s].

[2019-06-20 18:07:05.424673] INFO: bigquant: general_feature_extractor.v7 开始运行..

[2019-06-20 18:07:05.465420] INFO: bigquant: 命中缓存

[2019-06-20 18:07:05.467822] INFO: bigquant: general_feature_extractor.v7 运行完成[0.04315s].

[2019-06-20 18:07:05.472003] INFO: bigquant: sort.v4 开始运行..

[2019-06-20 18:07:05.542157] INFO: bigquant: 命中缓存

[2019-06-20 18:07:05.545135] INFO: bigquant: sort.v4 运行完成[0.073118s].

[2019-06-20 18:07:05.548176] INFO: bigquant: filter.v3 开始运行..

[2019-06-20 18:07:05.593775] INFO: bigquant: 命中缓存

[2019-06-20 18:07:05.596427] INFO: bigquant: filter.v3 运行完成[0.048231s].

[2019-06-20 18:07:05.641391] INFO: bigquant: backtest.v8 开始运行..

[2019-06-20 18:07:05.644802] INFO: bigquant: biglearning backtest:V8.2.2

[2019-06-20 18:07:05.835508] INFO: bigquant: product_type:stock by specified

[2019-06-20 18:07:06.119993] INFO: bigquant: cached.v2 开始运行..

[2019-06-20 18:07:06.182658] INFO: bigquant: 命中缓存

[2019-06-20 18:07:06.184680] INFO: bigquant: cached.v2 运行完成[0.064692s].

[2019-06-20 18:07:29.168738] INFO: algo: TradingAlgorithm V1.5.0

[2019-06-20 18:07:33.090069] INFO: algo: trading transform...

[2019-06-20 18:07:44.373614] INFO: Performance: Simulated 1049 trading days out of 1049.

[2019-06-20 18:07:44.378842] INFO: Performance: first open: 2015-01-05 09:30:00+00:00

[2019-06-20 18:07:44.380780] INFO: Performance: last close: 2019-04-23 15:00:00+00:00

[2019-06-20 18:07:52.685702] INFO: bigquant: backtest.v8 运行完成[47.044302s].

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