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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.perf_tracker.position_tracker.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.perf_tracker.position_tracker.positions.items()}\n instruments = list(reversed(list(ranker_prediction.instrument[ranker_prediction.instrument.apply(\n lambda x: x in equities and not context.has_unfinished_sell_order(equities[x]))])))\n # print('rank order for sell %s' % instruments)\n for instrument in instruments:\n 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[2019-07-20 15:25:59.683218] INFO: bigquant: instruments.v2 开始运行..
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[2019-07-20 15:25:59.773017] INFO: bigquant: advanced_auto_labeler.v2 开始运行..
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[2019-07-20 15:25:59.849448] INFO: bigquant: standardlize.v8 开始运行..
[2019-07-20 15:25:59.918860] INFO: bigquant: 命中缓存
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[2019-07-20 15:25:59.927747] INFO: bigquant: input_features.v1 开始运行..
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[2019-07-20 15:26:00.025017] INFO: bigquant: general_feature_extractor.v7 开始运行..
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[2019-07-20 15:26:00.084380] INFO: bigquant: derived_feature_extractor.v3 开始运行..
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[2019-07-20 15:26:00.194068] INFO: bigquant: standardlize.v8 开始运行..
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[2019-07-20 15:26:00.380464] INFO: bigquant: dl_convert_to_bin.v2 开始运行..
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[2019-07-20 15:26:00.517913] INFO: bigquant: instruments.v2 开始运行..
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[2019-07-20 15:26:00.709598] INFO: bigquant: general_feature_extractor.v7 开始运行..
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[2019-07-20 15:26:00.803253] INFO: bigquant: general_feature_extractor.v7 运行完成[0.093645s].
[2019-07-20 15:26:00.806967] INFO: bigquant: derived_feature_extractor.v3 开始运行..
[2019-07-20 15:26:00.849316] INFO: bigquant: 命中缓存
[2019-07-20 15:26:00.851691] INFO: bigquant: derived_feature_extractor.v3 运行完成[0.044715s].
[2019-07-20 15:26:00.855313] INFO: bigquant: standardlize.v8 开始运行..
[2019-07-20 15:26:00.898520] INFO: bigquant: 命中缓存
[2019-07-20 15:26:00.901521] INFO: bigquant: standardlize.v8 运行完成[0.046187s].
[2019-07-20 15:26:00.960752] INFO: bigquant: dl_convert_to_bin.v2 开始运行..
[2019-07-20 15:26:01.009647] INFO: bigquant: 命中缓存
[2019-07-20 15:26:01.012488] INFO: bigquant: dl_convert_to_bin.v2 运行完成[0.051732s].
[2019-07-20 15:26:01.017883] INFO: bigquant: cached.v3 开始运行..
[2019-07-20 15:26:01.089642] INFO: bigquant: 命中缓存
[2019-07-20 15:26:01.092497] INFO: bigquant: cached.v3 运行完成[0.074597s].
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[2019-07-20 15:26:01.443137] INFO: bigquant: 命中缓存
[2019-07-20 15:26:01.445891] INFO: bigquant: cached.v3 运行完成[0.066714s].
[2019-07-20 15:26:01.563017] INFO: bigquant: 命中缓存
[2019-07-20 15:26:01.566385] INFO: bigquant: dl_model_train.v1 运行完成[0.117266s].
[2019-07-20 15:26:01.646183] INFO: bigquant: 命中缓存
[2019-07-20 15:26:01.648509] INFO: bigquant: dl_model_predict.v1 运行完成[0.07935s].
[2019-07-20 15:26:01.654507] INFO: bigquant: cached.v3 开始运行..
[2019-07-20 15:26:01.705902] INFO: bigquant: 命中缓存
[2019-07-20 15:26:01.708622] INFO: bigquant: cached.v3 运行完成[0.054099s].
[2019-07-20 15:26:01.905786] INFO: bigquant: backtest.v8 开始运行..
[2019-07-20 15:26:02.000316] INFO: bigquant: 命中缓存
[2019-07-20 15:26:06.204740] INFO: bigquant: backtest.v8 运行完成[4.298953s].
DataSource(8aebe9b6f33a4036a5e4b713593316c8T, v3)
- 收益率266.63%
- 年化收益率95.6%
- 基准收益率-6.33%
- 阿尔法0.74
- 贝塔0.91
- 夏普比率1.73
- 胜率0.56
- 盈亏比1.06
- 收益波动率42.45%
- 信息比率0.15
- 最大回撤48.99%
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