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同步公众号:arXiv每日学术速递,欢迎关注 q-fin金融,共计6篇
econ经济,共计6篇
1.q-fin金融:
【1】 Community detection and portfolio optimization
标题:社区检测和投资组合优化
链接:https://arxiv.org/abs/2112.13383
作者:Longfeng Zhao,Chao Wang,Gang-Jin Wang,H. Eugene Stanley,Lin Chen
【2】 Price Impact of Order Flow Imbalance: Multi-level, Cross-sectional and Forecasting
标题:订单流失衡的价格影响:多层次、横截面与预测
链接:https://arxiv.org/abs/2112.13213
作者:Rama Cont,Mihai Cucuringu,Chao Zhang
【3】 Using Network-based Causal Inference to Detect the Sources of Contagion in the Currency Market
标题:基于网络的因果推理在货币市场传染源检测中的应用
链接:https://arxiv.org/abs/2112.13127
作者:Katerina Rigana,Ernst-Jan Camiel Wit,Samantha Cook
【4】 Regime Switching Entropic Risk Measures on Crude Oil Pricing
标题:原油定价中的体制转换熵风险测度
链接:https://arxiv.org/abs/2112.13041
作者:Babacar Seck,Robert J. Elliott
备注:20 pages, 6 figures
【5】 Multi-modal Attention Network for Stock Movements Prediction
标题:多模态注意力网络在股市走势预测中的应用
链接:https://arxiv.org/abs/2112.13593
作者:Shwai He,Shi Gu
【6】 Reinforcement Learning with Dynamic Convex Risk Measures
标题:具有动态凸风险测度的强化学习
链接:https://arxiv.org/abs/2112.13414
作者:Anthony Coache,Sebastian Jaimungal
备注:19 pages, 7 figures
2.econ经济:
【1】 Random Rank-Dependent Expected Utility
标题:随机秩相关的预期效用
链接:https://arxiv.org/abs/2112.13649
作者:Nail Kashaev,Victor Aguiar
【2】 Omitted Variable Bias in Machine Learned Causal Models
标题:机器学习因果模型中忽略的变量偏差
链接:https://arxiv.org/abs/2112.13398
作者:Victor Chernozhukov,Carlos Cinelli,Whitney Newey,Amit Sharma,Vasilis Syrgkanis
备注:This version of the paper was prepared for the NeurIPS-21 Workshop "Causal Inference & Machine Learning: Why now?''; 31 pages; 4 figures
【3】 Identification of misreported beliefs
标题:识别错误报道的信念
链接:https://arxiv.org/abs/2112.12975
作者:Elias Tsakas
备注:12 pages, 1 figure
【4】 Estimation based on nearest neighbor matching: from density ratio to average treatment effect
标题:基于最近邻匹配的估计:从密度比到平均处理效果
链接:https://arxiv.org/abs/2112.13506
作者:Zhexiao Lin,Peng Ding,Fang Han
备注:73 pages
【5】 Multiple Randomization Designs
标题:多重随机化设计
链接:https://arxiv.org/abs/2112.13495
作者:Patrick Bajari,Brian Burdick,Guido W. Imbens,Lorenzo Masoero,James McQueen,Thomas Richardson,Ido M. Rosen
备注:57 pages, 7 figures
【6】 Robust Estimation of Average Treatment Effects from Panel Data
标题:面板数据平均处理效应的稳健估计
链接:https://arxiv.org/abs/2112.13228
作者:Sayoni Roychowdhury,Indrila Ganguly,Abhik Ghosh
备注:Preprint, Under review
机器翻译,仅供参考
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