AI for Finance

Publications

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Year Research Area Publication Type

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• 2021

  • ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting

    Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian

    December 2021

    Publication

  • Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation

    Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian

    ICAIF 2021 | November 2021

    Publication

  • Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport

    Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian

    KDD 2021 | August 2021

    Publication

  • Temporally Correlated Task Scheduling for Sequence Learning

    Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu

    2021 International Conference on Machine Learning | July 2021

    Publication

  • REST: Relational Event-driven Stock Trend Forecasting

    Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu

    2021 The Web Conference | April 2021

    Publication

  • Universal Trading for Order Execution with Oracle Policy Distillation

    Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu

    AAAI | February 2021

    Publication

• 2020

  • Qlib: An AI-oriented Quantitative Investment Platform.

    Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu

    September 2020

    Publication PDF Github

  • Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction

    Chi Chen, Li Zhao, Wei Cao, Jiang Bian, Chunxiao Xing

    February 2020

    Publication

• 2019

  • A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies

    Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian

    2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019

    Publication

  • Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction

    Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian

    2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019

    Publication

  • Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding

    Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu

    25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | August 2019

    Publication

  • Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction

    Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu

    25th ACM SIGKDD Conference on Knowledge Discover and Data Mining(KDD 2019) | August 2019

    Publication

• 2018

  • Investor-Imitator: A Framework for Trading Knowledge Extraction

    Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu

    Knowledge Discovery & Data Mining | July 2018

    Publication

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• Artificial intelligence

  • ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting

    Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian

    December 2021

    Publication

  • Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation

    Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian

    ICAIF 2021 | November 2021

    Publication

  • Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport

    Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian

    KDD 2021 | August 2021

    Publication

  • Temporally Correlated Task Scheduling for Sequence Learning

    Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu

    2021 International Conference on Machine Learning | July 2021

    Publication

  • REST: Relational Event-driven Stock Trend Forecasting

    Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu

    2021 The Web Conference | April 2021

    Publication

  • Universal Trading for Order Execution with Oracle Policy Distillation

    Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu

    AAAI | February 2021

    Publication

  • Qlib: An AI-oriented Quantitative Investment Platform.

    Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu

    September 2020

    Publication PDF Github

  • Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction

    Chi Chen, Li Zhao, Wei Cao, Jiang Bian, Chunxiao Xing

    February 2020

    Publication

  • Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction

    Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian

    2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019

    Publication

  • A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies

    Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian

    2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019

    Publication

  • Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding

    Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu

    25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | August 2019

    Publication

  • Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction

    Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu

    25th ACM SIGKDD Conference on Knowledge Discover and Data Mining(KDD 2019) | August 2019

    Publication

  • Investor-Imitator: A Framework for Trading Knowledge Extraction

    Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu

    Knowledge Discovery & Data Mining | July 2018

    Publication

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• Miscellaneous

  • ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting

    Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian

    December 2021

    Publication

  • Qlib: An AI-oriented Quantitative Investment Platform.

    Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu

    September 2020

    Publication PDF Github

  • Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction

    Chi Chen, Li Zhao, Wei Cao, Jiang Bian, Chunxiao Xing

    February 2020

    Publication

• Inproceedings (Conference)

  • Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation

    Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian

    ICAIF 2021 | November 2021

    Publication

  • Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport

    Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian

    KDD 2021 | August 2021

    Publication

  • Temporally Correlated Task Scheduling for Sequence Learning

    Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu

    2021 International Conference on Machine Learning | July 2021

    Publication

  • REST: Relational Event-driven Stock Trend Forecasting

    Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu

    2021 The Web Conference | April 2021

    Publication

  • Universal Trading for Order Execution with Oracle Policy Distillation

    Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu

    AAAI | February 2021

    Publication

  • Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction

    Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian

    2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019

    Publication

  • A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies

    Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian

    2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019

    Publication

  • Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding

    Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu

    25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | August 2019

    Publication

  • Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction

    Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu

    25th ACM SIGKDD Conference on Knowledge Discover and Data Mining(KDD 2019) | August 2019

    Publication

  • Investor-Imitator: A Framework for Trading Knowledge Extraction

    Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu

    Knowledge Discovery & Data Mining | July 2018

    Publication