ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
arXiv | December 2021
出版物
-
-
-
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
-
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
-
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
-
REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
The Web Conference | April 2021
-
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
-
-
-
Qlib: An AI-oriented Quantitative Investment Platform.
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
September 2020
arXiv | September 2020
-
Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction
Chi Chen, Li Zhao, Wei Cao, Jiang Bian, Chunxiao Xing
February 2020
arXiv | February 2020
-
-
-
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
-
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
-
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
-
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
-
-
-
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
-
-
-
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
arXiv | December 2021
-
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
-
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
-
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
-
REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
The Web Conference | April 2021
-
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
-
Qlib: An AI-oriented Quantitative Investment Platform.
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
September 2020
arXiv | September 2020
-
Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction
Chi Chen, Li Zhao, Wei Cao, Jiang Bian, Chunxiao Xing
February 2020
arXiv | February 2020
-
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
-
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
-
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
-
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
-
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
-
-
-
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
arXiv | December 2021
-
Qlib: An AI-oriented Quantitative Investment Platform.
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
September 2020
arXiv | September 2020
-
Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction
Chi Chen, Li Zhao, Wei Cao, Jiang Bian, Chunxiao Xing
February 2020
arXiv | February 2020
-
-
-
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
-
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
-
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
-
REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
The Web Conference | April 2021
-
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
-
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
-
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
-
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
-
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
-
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
-