基准指数收益如何表达


(LeioC) #1

请问在可视化策略的自动数据标注内该如何表达基准指数的前N日的收益


(iQuant) #2

比如,希望以未来5日相对收益率作为排序依据。(相对收益=收益-基准收益)

参考代码:

# 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) - shift(benchmark_close, -5) / shift(benchmark_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)

在可视化界面的截图为:

如果还未解决您的问题,欢迎来信。

克隆策略

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    In [12]:
    # 本代码由可视化策略环境自动生成 2017年11月13日 12:14
    # 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。
    
    
    m1 = M.instruments.v2(
        start_date='2014-01-01',
        end_date='2015-01-01',
        market='CN_STOCK_A',
        instrument_list='',
        max_count=20
    )
    
    m2 = M.advanced_auto_labeler.v2(
        instruments=m1.data,
        label_expr="""# 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) - shift(benchmark_close, -5) / shift(benchmark_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.SHA',
        drop_na_label=True,
        cast_label_int=True
    )
    
    [2017-11-13 12:14:06.862396] INFO: bigquant: instruments.v2 开始运行..
    [2017-11-13 12:14:06.866008] INFO: bigquant: 命中缓存
    [2017-11-13 12:14:06.867002] INFO: bigquant: instruments.v2 运行完成[0.004596s].
    [2017-11-13 12:14:06.879928] INFO: bigquant: advanced_auto_labeler.v2 开始运行..
    [2017-11-13 12:14:06.882657] INFO: bigquant: 命中缓存
    [2017-11-13 12:14:06.883962] INFO: bigquant: advanced_auto_labeler.v2 运行完成[0.004042s].