Online portfolio management via deep reinforcement learning with high-frequency data

Recently, models that based on Transformer (Vaswani et al., 2017) have yielded superior results in many sequence modeling tasks. The ability of Transformer to capture long-range dependencies and interactions makes it possible to apply it in the field of portfolio management (PM). However, the built-in quadratic complexity of the Transformer prevents its direct application to the PM task. To solve this problem, in this paper, we propose a deep reinforcement learning-based PM framework called LSRE-CAAN, with two important components: a long sequence representations extractor and a cross-asset attention network. Direct Policy Gradient is used to solve the sequential decision problem in the PM process. We conduct numerical experiments in three aspects using four different cryptocurrency datasets, and the empirical results show that our framework is more effective than both traditional and state-of-the-art (SOTA) online portfolio strategies, achieving a 6x return on the best dataset. In terms of risk metrics, our framework has an average volatility risk of 0.46 and an average maximum drawdown risk of 0.27 across the four datasets, both of which are lower than the vast majority of SOTA strategies. In addition, while the vast majority of SOTA strategies maintain a poor turnover rate of approximately greater than 50% on average, our framework enjoys a relatively low turnover rate on all datasets, efficiency analysis illustrates that our framework no longer has the quadratic dependency limitation.     

User-aware multilingual abusive content detection in social media

Despite growing efforts to halt distasteful content on social media, multilingualism has added a new dimension to this problem. The scarcity of resources makes the challenge even greater when it comes to low-resource languages. This work focuses on providing a novel method for abusive content detection in multiple low-resource Indic languages. Our observation indicates that a post’s tendency to attract abusive comments, as well as features such as user history and social context, significantly aid in the detection of abusive content. The proposed method first learns social and text context features in two separate modules. The integrated representation from these modules is learned and used for the final prediction. To evaluate the performance of our method against different classical and state-of-the-art methods, we have performed extensive experiments on SCIDN and MACI datasets consisting of 1.5M and 665K multilingual comments, respectively. Our proposed method outperforms state-of-the-art baseline methods with an average increase of 4.08% and 9.52% in the F1-score on SCIDN and MACI datasets, respectively.     

融合·冲突·缝合——从郭小川《深深的山谷》看知识分子与革命关系

在“十七年”政治——文化语境中,郭小川的《深深的山谷》出现了创作动机与实际效果之间有趣的相悖现象。形成这一现象的诱因在于文本的复杂性,诗歌表层上讲述的是从“合”到“分”的“爱情”故事,而在深层上则以“爱情”故事为依托。反观与思索知识分子与革命之间“融合——冲突——缝合”的动态过程,表层上讲述的是“他者”的悲欢离舍,深层上叙说的却是“自我”历史记忆及现实体验中的欢乐与痛苦。     

论原型批评与主题学研究之关系

世界文学中的原型是可数的,一个原型可以不断地衍生出无数个主题。原型与主题之间是一种渊源与支流的关系。主题学研究同一主题在不同时代和地区的演变,也研究主题在不同文学体系中的表现。主题学的研究必须先探索原型,寻求到同一主题演变的渊源关系。探究原型的根源,进行宏观研究分析,将会为主题学的研究开辟出一个崭新的天地,有利于促进比较文学的研究与发展,推进文学的发展与繁荣。     

基于椭球面拟合的股骨头修复建模(英文)

提出了一种可以获得目标病例健康时股骨头模型的新建模方法.首先利用一种精确的自动分割方法在髋骨部位CT序列图像中提取髋臼轮廓;然后使用基于等距栅格采样法与辐条式采样法相结合的混合采样法得到髋臼凹面的空间坐标点集,并剔除其中的误差采样点;最后采用基于二次曲面一般方程的方法拟合原始股骨头椭球面模型.通过对2倒不同坏死程度的男性患者进行修复性的对比仿真,以及对50例不同年龄(25～79岁)患者修复重建后的匹配误差统计分析,证明此方法可以良好地还原坏死的股骨头模型,既为骨科临床中的精确手术定位提供了理论模型,又为针对个体化制造的人工假体生产提供了新的实践方法.     

“死”类动词同义句式分析——以“死了一个人”和“一个人死了”为例

＂死了一个人＂和＂一个人死了＂是一价动词同义句式。国内对于同义句式的研究由来已久。本文准备在前人的基础上具体研究＂死了一个人＂和＂一个人死了＂这两个句式,对哪个是基本句式,哪个是派生句式进行确认,并分析由形式的差异所导致的意义的差异。     

实践意义与深度介入：“U—S”合作的京沪对话

由大学研究人员、中小学校长和教师组成的两支研究团队相会北京,就共同感兴趣的大中小学（即“U—S”）合作问题展开热烈对话,尽管双方对大中小学合作意义的认识“同中有异”,介入学校变革实践的过程与方式却是“异中有同”,对“U—S”合作的前景都充满信心,并且充分意识到自己在中国基础教育改革大业中不可旁贷的责任担当,对话留下的诸多问题也值得我们去继续更有深度的思索与行动。     

论海岩小说《深牢大狱》的人性光辉

人性是真理性在人身上的自由表达,是对真善美的追求。小说《深牢大狱》是一部全面反映监狱工作生活的作品,其中处处闪耀着人性的光辉,对国家和人民的忠诚、对事业的荣誉和使命感以及对爱情、亲情和友情的美好表达。     

Case Report: Coronary arterial spasm in single right coronary artery

We presented a case of anomalous single-coronary artery detected incidentally during routine coronary angiography. A 32-year-old male Chinese patient presented with recurrent pre-syncope and six episodes of syncope. Coronary angiography and coronary-computed tomography (CT)-angiography performed by a dual-source computed tomography (DSCT) revealed that the patient had a single large right coronary artery. A moderately large branch originated from the proximal part of the single right coronary artery and extended to the left, passing the anterior to the pulmonary artery, and divided into the anterior descending artery branch and circumflex branch at the base of the left auricular appendage. The episodes of the syncope were suspected to be caused by coronary arterial spasm, so this patient was on a regimen of 30 mg of diltiazem every 6 h and had no recurrence of syncope during follow-up.     

长期大运动量耐力训练对大鼠肾动脉组织学影响的研究

通过对耐力训练大鼠肾动脉的零应力状态下的张开角、组织学组成成份的变化,探讨耐力训练对肾动脉的张开角和微观组织结构的影响.结果表明,耐力训练组大鼠肾动脉张开角与对照组相比明显减小(P<0.05);耐力训练组大鼠肾动脉的弹性纤维、胶原纤维的含量与对照组没有显著性差异(p>0.05),C/E没有显著差异(p>0.05);耐力训练组大鼠的平滑肌的相对面积显著减小(p<0.05),而平滑肌的细胞核数并无显著差异(p>0.05),单个平滑肌的相对面积显著减小(P<0.05).因此,长期耐力运动训练主要导致肾动脉中平滑肌的重建.