{"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":"-250:options_data","from_node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-60:predictions"},{"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":"287d2cb0-f53c-4101-bdf8-104b137c8601-53:data2","from_node_id":"-222:data"},{"to_node_id":"-238:input_data","from_node_id":"-231:data"},{"to_node_id":"-86:input_data","from_node_id":"-238:data"}],"nodes":[{"node_id":"287d2cb0-f53c-4101-bdf8-104b137c8601-8","module_id":"BigQuantSpace.instruments.instruments-v2","parameters":[{"name":"start_date","value":"2018-01-01","type":"Literal","bound_global_parameter":null},{"name":"end_date","value":"2020-12-31","type":"Literal","bound_global_parameter":null},{"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-bdf8-104b137c8601-8"}],"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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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 cash_for_buy = min(context.portfolio.cash, (1 if is_staging else 1.5) * cash_avg)\n cash_for_sell = cash_avg - (context.portfolio.cash - cash_for_buy)\n positions = {e.symbol: p.amount * p.last_sale_price\n for e, p in context.portfolio.positions.items()}\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 instruments = list(reversed(list(ranker_prediction.instrument[ranker_prediction.instrument.apply(\n lambda x: x in equities)])))\n\n for instrument in instruments:\n context.order_target(context.symbol(instrument), 0)\n cash_for_sell -= positions[instrument]\n if cash_for_sell <= 0:\n break\n\n # 3. 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[2022-05-20 09:58:59.303329] INFO: moduleinvoker: instruments.v2 开始运行..
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[2022-05-20 09:58:59.752706] INFO: moduleinvoker: instruments.v2 运行完成[0.007441s].
[2022-05-20 09:58:59.766900] INFO: moduleinvoker: general_feature_extractor.v7 开始运行..
[2022-05-20 09:59:03.308888] INFO: 基础特征抽取: 年份 2020, 特征行数=243745
[2022-05-20 09:59:10.499165] INFO: 基础特征抽取: 年份 2021, 特征行数=1061527
[2022-05-20 09:59:10.619129] INFO: 基础特征抽取: 总行数: 1305272
[2022-05-20 09:59:10.631985] INFO: moduleinvoker: general_feature_extractor.v7 运行完成[10.865075s].
[2022-05-20 09:59:10.648041] INFO: moduleinvoker: derived_feature_extractor.v3 开始运行..
[2022-05-20 09:59:14.007852] INFO: derived_feature_extractor: 提取完成 avg_amount_0/avg_amount_5, 0.006s
[2022-05-20 09:59:14.015174] INFO: derived_feature_extractor: 提取完成 avg_amount_5/avg_amount_20, 0.005s
[2022-05-20 09:59:14.020683] INFO: derived_feature_extractor: 提取完成 rank_avg_amount_0/rank_avg_amount_5, 0.004s
[2022-05-20 09:59:14.025908] INFO: derived_feature_extractor: 提取完成 rank_avg_amount_5/rank_avg_amount_10, 0.003s
[2022-05-20 09:59:14.031304] INFO: derived_feature_extractor: 提取完成 rank_return_0/rank_return_5, 0.004s
[2022-05-20 09:59:14.035919] INFO: derived_feature_extractor: 提取完成 rank_return_5/rank_return_10, 0.003s
[2022-05-20 09:59:14.969988] INFO: derived_feature_extractor: /y_2020, 243745
[2022-05-20 09:59:17.392254] INFO: derived_feature_extractor: /y_2021, 1061527
[2022-05-20 09:59:18.509725] INFO: moduleinvoker: derived_feature_extractor.v3 运行完成[7.861651s].
[2022-05-20 09:59:18.527959] INFO: moduleinvoker: dropnan.v1 开始运行..
[2022-05-20 09:59:19.072592] INFO: dropnan: /y_2020, 239876/243745
[2022-05-20 09:59:20.874157] INFO: dropnan: /y_2021, 1049627/1061527
[2022-05-20 09:59:20.981405] INFO: dropnan: 行数: 1289503/1305272
[2022-05-20 09:59:20.998331] INFO: moduleinvoker: dropnan.v1 运行完成[2.470383s].
[2022-05-20 09:59:21.014806] INFO: moduleinvoker: stock_ranker_predict.v5 开始运行..
[2022-05-20 09:59:21.484405] INFO: StockRanker预测: /y_2020 ..
[2022-05-20 09:59:22.901769] INFO: StockRanker预测: /y_2021 ..
[2022-05-20 09:59:26.670380] INFO: moduleinvoker: stock_ranker_predict.v5 运行完成[5.655576s].
[2022-05-20 09:59:28.512100] INFO: moduleinvoker: backtest.v8 开始运行..
[2022-05-20 09:59:28.519040] INFO: backtest: biglearning backtest:V8.6.2
[2022-05-20 09:59:28.520534] INFO: backtest: product_type:stock by specified
[2022-05-20 09:59:28.615241] INFO: moduleinvoker: cached.v2 开始运行..
[2022-05-20 09:59:28.630667] INFO: moduleinvoker: 命中缓存
[2022-05-20 09:59:28.632904] INFO: moduleinvoker: cached.v2 运行完成[0.017684s].
[2022-05-20 09:59:30.918628] INFO: algo: TradingAlgorithm V1.8.7
[2022-05-20 09:59:31.713518] INFO: algo: trading transform...
[2022-05-20 09:59:35.020742] INFO: algo: handle_splits get splits [dt:2021-05-21 00:00:00+00:00] [asset:Equity(5515 [688060.SHA]), ratio:0.9935547709465027]
[2022-05-20 09:59:35.022526] INFO: Position: position stock handle split[sid:5515, orig_amount:1700, new_amount:1711.0, orig_cost:57.802014189199355, new_cost:57.4295, ratio:0.9935547709465027, last_sale_price:57.03997802734375]
[2022-05-20 09:59:35.024689] INFO: Position: after split: PositionStock(asset:Equity(5515 [688060.SHA]), amount:1711.0, cost_basis:57.4295, last_sale_price:57.40999984741211)
[2022-05-20 09:59:35.026393] INFO: Position: returning cash: 1.5952
[2022-05-20 09:59:35.097415] INFO: algo: handle_splits get splits [dt:2021-05-25 00:00:00+00:00] [asset:Equity(5463 [300342.SZA]), ratio:0.9861623644828796]
[2022-05-20 09:59:35.099396] INFO: Position: position stock handle split[sid:5463, orig_amount:4200, new_amount:4258.0, orig_cost:10.900001078941374, new_cost:10.7492, ratio:0.9861623644828796, last_sale_price:10.690001487731934]
[2022-05-20 09:59:35.101044] INFO: Position: after split: PositionStock(asset:Equity(5463 [300342.SZA]), amount:4258.0, cost_basis:10.7492, last_sale_price:10.840001106262207)
[2022-05-20 09:59:35.102447] INFO: Position: returning cash: 9.9799
[2022-05-20 09:59:35.199177] INFO: algo: handle_splits get splits [dt:2021-05-28 00:00:00+00:00] [asset:Equity(1683 [300552.SZA]), ratio:0.981345534324646]
[2022-05-20 09:59:35.200684] INFO: algo: handle_splits get splits [dt:2021-05-28 00:00:00+00:00] [asset:Equity(856 [300462.SZA]), ratio:0.9876540899276733]
[2022-05-20 09:59:35.202106] INFO: Position: position stock handle split[sid:1683, orig_amount:2600, new_amount:2649.0, orig_cost:32.11000367238593, new_cost:31.511, ratio:0.981345534324646, last_sale_price:32.09000015258789]
[2022-05-20 09:59:35.203298] INFO: Position: after split: PositionStock(asset:Equity(1683 [300552.SZA]), amount:2649.0, cost_basis:31.511, last_sale_price:32.70000076293945)
[2022-05-20 09:59:35.204428] INFO: Position: returning cash: 13.5927
[2022-05-20 09:59:35.205821] INFO: Position: position stock handle split[sid:856, orig_amount:13100, new_amount:13263.0, orig_cost:11.572981495151135, new_cost:11.4301, ratio:0.9876540899276733, last_sale_price:11.999998092651367]
[2022-05-20 09:59:35.207048] INFO: Position: after split: PositionStock(asset:Equity(856 [300462.SZA]), amount:13263.0, cost_basis:11.4301, last_sale_price:12.15000057220459)
[2022-05-20 09:59:35.208581] INFO: Position: returning cash: 9.0372
[2022-05-20 09:59:35.361886] INFO: algo: handle_splits get splits [dt:2021-06-04 00:00:00+00:00] [asset:Equity(978 [300107.SZA]), ratio:0.9817518591880798]
[2022-05-20 09:59:35.419835] INFO: algo: handle_splits get splits [dt:2021-06-08 00:00:00+00:00] [asset:Equity(804 [300833.SZA]), ratio:0.9923853874206543]
[2022-05-20 09:59:35.421795] INFO: algo: handle_splits get splits [dt:2021-06-08 00:00:00+00:00] [asset:Equity(477 [002730.SZA]), ratio:0.9940072894096375]
[2022-05-20 09:59:35.731675] INFO: algo: handle_splits get splits [dt:2021-06-24 00:00:00+00:00] [asset:Equity(3278 [300165.SZA]), ratio:0.9979838132858276]
[2022-05-20 09:59:35.733280] INFO: Position: position stock handle split[sid:3278, orig_amount:11500, new_amount:11523.0, orig_cost:5.040000605343489, new_cost:5.0298, ratio:0.9979838132858276, last_sale_price:4.950000286102295]
[2022-05-20 09:59:35.735668] INFO: Position: after split: PositionStock(asset:Equity(3278 [300165.SZA]), amount:11523.0, cost_basis:5.0298, last_sale_price:4.960000514984131)
[2022-05-20 09:59:35.737162] INFO: Position: returning cash: 1.1533
[2022-05-20 09:59:39.515202] INFO: algo: handle_splits get splits [dt:2021-12-31 00:00:00+00:00] [asset:Equity(123 [300278.SZA]), ratio:0.9283888339996338]
[2022-05-20 09:59:39.517007] INFO: Position: position stock handle split[sid:123, orig_amount:11600, new_amount:12494.0, orig_cost:3.6999999332015436, new_cost:3.435, ratio:0.9283888339996338, last_sale_price:3.630000114440918]
[2022-05-20 09:59:39.518642] INFO: Position: after split: PositionStock(asset:Equity(123 [300278.SZA]), amount:12494.0, cost_basis:3.435, last_sale_price:3.9099998474121094)
[2022-05-20 09:59:39.519725] INFO: Position: returning cash: 2.7757
[2022-05-20 09:59:39.548911] INFO: Performance: Simulated 243 trading days out of 243.
[2022-05-20 09:59:39.550374] INFO: Performance: first open: 2021-01-04 09:30:00+00:00
[2022-05-20 09:59:39.551451] INFO: Performance: last close: 2021-12-31 15:00:00+00:00
[2022-05-20 09:59:45.691021] INFO: moduleinvoker: backtest.v8 运行完成[17.178928s].
[2022-05-20 09:59:45.692805] INFO: moduleinvoker: trade.v4 运行完成[19.009259s].
bigcharts-data-start/{"__type":"tabs","__id":"bigchart-9493af562ea04486a4a4bd587f2b1736"}/bigcharts-data-end
- 收益率58.34%
- 年化收益率61.06%
- 基准收益率-5.2%
- 阿尔法0.66
- 贝塔0.39
- 夏普比率1.87
- 胜率0.51
- 盈亏比1.42
- 收益波动率25.72%
- 信息比率0.13
- 最大回撤15.12%
bigcharts-data-start/{"__type":"tabs","__id":"bigchart-6f8fbc7d5c8d4cf598832743aeb18ff1"}/bigcharts-data-end