克隆策略

    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    In [5]:
    # 本代码由可视化策略环境自动生成 2021年10月30日 12:51
# 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。


m2 = M.instruments.v2(
    start_date='2018-01-01',
    end_date='2021-10-20',
    market='CN_STOCK_A',
    instrument_list='',
    max_count=0
)

m3 = M.input_features.v1(
    features="""close_0
open_0
high_0
low_0 
amount_0
turn_0 
return_0"""
)

m4 = M.general_feature_extractor.v7(
    instruments=m2.data,
    features=m3.data,
    start_date='',
    end_date='',
    before_start_days=90
)

m5 = M.derived_feature_extractor.v3(
    input_data=m4.data,
    features=m3.data,
    date_col='date',
    instrument_col='instrument',
    drop_na=False,
    remove_extra_columns=False,
    user_functions={}
)

m1 = M.genetic_algorithm.v1(
    instruments=m2.data,
    feature_datas=m5.data,
    all_start_date='',
    all_end_date='',
    short_date_range_ratio=0.7,
    return_field='wap_3_vwap_buy',
    rebalance_period=1,
    train_test_ratio=0.75,
    train_validate_ratio=0.75,
    mtime=2,
    init_ind_num=10,
    ngen=3,
    fitness_func='long_return',
    train_fitness=2,
    test_fitness=1.6,
    ir_type='ir',
    cxpb=0.5,
    mutpb=0.3,
    mutspb=0.3,
    mutnrpb=0.3,
    constant='1,11',
    pool_processes_limit=5,
    m_cached=False
)

    -- 开始第「1」次循环第「1」代挖掘 --

    去重前的个体数10
去重后的个体数10

    每代的平均适应度：[0.014992363024151838]
因子sma(high_0, 1)在训练集适应度值为0.8605557181242324
因子mean3(prod(open_0, 7), stddev(return_0, 10), argmin(return_0, 7))在训练集适应度值为0.8191720860629771
因子sma(standardation(return_0), constant(3))在训练集适应度值为3.3591763456667794
因子abs(sma(low_0, 6))在训练集适应度值为0.8338682778508668
因子sma(wap_3_vwap_buy, 3)在训练集适应度值为0.828682250393938
因子cov(amount_0, high_0, 6)在训练集适应度值为0.6680434976056022
因子prod(open_0, 9)在训练集适应度值为0.869169461817944
因子standardation(ts_max(wap_3_vwap_buy, 3))在训练集适应度值为0.8383507505397471
因子vsub(ts_rank(close_0, 8), min(turn_0, wap_3_vwap_buy))在训练集适应度值为0.5737397502018435
因子power(high_0, high_0)在训练集适应度值为0.7922422900875445

    因子sma(standardation(return_0), constant(3))在测试集适应度值为1.8014644530165738

    pass:1, record:10, population: 1

    下一代挖掘的个体数：10

    -- 开始第「1」次循环第「2」代挖掘 --

    去重前的个体数10
去重后的个体数8

    每代的平均适应度：[0.014992363024151838, -0.19277371635515714]
因子sma(standardation(return_0), 3)在训练集适应度值为0.608536374526242
因子sma(high_0, constant(3))在训练集适应度值为0.8271665269337954
因子sma(standardation(return_0), constant(3))在训练集适应度值为0.608536374526242
因子sma(close_0, constant(3))在训练集适应度值为0.8306588530067993
因子sma(rank(return_0), constant(4))在训练集适应度值为0.1473770140143686
因子clear_by_cond(return_0, high_0, wap_3_vwap_buy)在训练集适应度值为-0.40450131974237
因子sma(standardation(standardation(return_0)), constant(3))在训练集适应度值为0.608536374526242
因子sma(return_0, 3)在训练集适应度值为0.09948989298774549

    pass:0, record:8, population: 8

    下一代挖掘的个体数：10

    -- 开始第「1」次循环第「3」代挖掘 --

    去重前的个体数10
去重后的个体数9

    每代的平均适应度：[0.014992363024151838, -0.19277371635515714, -0.07490728778450059]
因子sma(return_0, constant(4))在训练集适应度值为0.608177547724697
因子sma(standardation(standardation(close_0)), constant(3))在训练集适应度值为0.8304277912617549
因子sma(mean2(open_0, amount_0), constant(2))在训练集适应度值为0.5153648897672801
因子sma(high_0, 3)在训练集适应度值为0.8271665269337954
因子sma(close_0, 3)在训练集适应度值为0.8306588530067993
因子sma(standardation(standardation(return_0)), constant(3))在训练集适应度值为0.608536374526242
因子sma(high_0, constant(3))在训练集适应度值为0.8271665269337954
因子sma(high_0, 4)在训练集适应度值为0.8202732148700856
因子sma(close_0, 2)在训练集适应度值为0.8456432736126808

    pass:0, record:9, population: 9

    下一代挖掘的个体数：10

    -- 开始第「2」次循环第「1」代挖掘 --

    去重前的个体数10
去重后的个体数10

    每代的平均适应度：[-0.018779241638940965]
因子min(min(wap_3_vwap_buy, close_0), cov(wap_3_vwap_buy, return_0, 10))在训练集适应度值为1.792060973612757
因子ts_min(return_0, 10)在训练集适应度值为0.6429795824874913
因子standardation(amount_0)在训练集适应度值为0.8324821918315465
因子vdiv(wap_3_vwap_buy, open_0)在训练集适应度值为1.7068164083094257
因子argmax(vneg(return_0), constant(9))在训练集适应度值为0.797080746385853
因子mean2(close_0, wap_3_vwap_buy)在训练集适应度值为0.8379155001549915
因子min(open_0, open_0)在训练集适应度值为0.8167695479833765
因子if_then_else(open_0, open_0, turn_0, wap_3_vwap_buy)在训练集适应度值为0.8407540998317315
因子sma(high_0, 5)在训练集适应度值为0.8147897062604205
因子sign(low_0)在训练集适应度值为nan

    pass:0, record:10, population: 10

    下一代挖掘的个体数：10

    -- 开始第「2」次循环第「2」代挖掘 --

    去重前的个体数10
去重后的个体数8

    每代的平均适应度：[-0.018779241638940965, 0.03550155009401186]
因子vdiv(close_0, turn_0)在训练集适应度值为0.6798557562281556
因子min(min(wap_3_vwap_buy, wap_3_vwap_buy), return_0)在训练集适应度值为1.9748884537233056
因子standardation(mean3(delta(close_0, 9), delay(open_0, 6), sign(return_0)))在训练集适应度值为0.9096297377293028
因子min(return_0, open_0)在训练集适应度值为2.1307065969560974
因子sma(turn_0, 5)在训练集适应度值为0.5644559519131452
因子mean2(turn_0, wap_3_vwap_buy)在训练集适应度值为0.8908015199936777
因子min(ts_max(low_0, 1), cov(wap_3_vwap_buy, return_0, 10))在训练集适应度值为1.7828513339325067
因子min(open_0, open_0)在训练集适应度值为0.8167695479833765

    因子min(return_0, open_0)在测试集适应度值为1.1433017597984974

    pass:1, record:8, population: 1

    下一代挖掘的个体数：10

    -- 开始第「2」次循环第「3」代挖掘 --

    去重前的个体数10
去重后的个体数4

    每代的平均适应度：[-0.018779241638940965, 0.03550155009401186, 0.09983868776809751]
因子min(open_0, open_0)在训练集适应度值为0.8167695479833765
因子min(return_0, return_0)在训练集适应度值为2.1311511112052175
因子min(return_0, open_0)在训练集适应度值为2.1307065969560974
因子min(min(min(amount_0, high_0), standardation(turn_0)), open_0)在训练集适应度值为0.7521329267996869

    因子min(return_0, return_0)在测试集适应度值为1.1484387405338683
因子min(return_0, open_0)在测试集适应度值为1.1433017597984974

    pass:2, record:4, population: 2

    下一代挖掘的个体数：10