About

ShanghaiTech FinTech Initiative aims at integrating AI technology and finance to make financial services more efficient, secure, and trustworthy at the level of software and hardware infrastructure. On this basis, new data and methods are used to make analysis and modeling more intelligent, and novel mechanisms are designed to comprehensively and deeply understand market participants and designing efficient and fair rules. Our research direction mainly includes three aspects: 1) Safe, Efficient and Green Financial Infrastructure; 2）Data-driven Financial Intelligence; and 3) Market Mechanism and Rule Design.

Research Areas

Safe, Efficient and Green Financial Infrastructure

Block Chain, Cryptography, Privacy Computing, etc.

Data-driven Financial Intelligence

Intelligent Investment, Intelligent Risk Control, Intelligent Marketing, Anti-Money Laundering, Anti-Fraud, Abnormal Transaction Detection, etc.

Market Mechanism and Rule Design

Market Game Theory, Incentive Mechanism, Transaction Mechanism Design, etc.

Our Team

Haipeng Zhang Assistant Professor, SIST
Ziping Zhao Assistant Professor, SIST
Quan Li Assistant Professor, SIST

Collaboration

hkust
msra
shenzhenstockexchange
chinaforeign

ant
didi
tencent
webank
bfam
penn
unilu

Publications

One Step Ahead: A Framework for Detecting Unexpected Incidents and Predicting the Stock Markets.
Ziyue Li, Shiwei Lyu, Haipeng Zhang, Tianpei Jiang.
IEEE Access. 2021 Feb 12;9:30292-305.

[ paper ]

'Could You Describe the Reason for the Transfer?': A Reinforcement Learning Based Voice-Enabled Bot Protecting Customers from Financial Frauds.
Zihao Wang, Fudong Wang, Haipeng Zhang, Minghui Yang, Shaosheng Cao, Zujie Wen, Zhe Zhang.
Proceedings of ACM Conference on Information and Knowledge Management (CIKM) 2021.

[ paper ]

Multi-Period Portfolio Optimization for Index Tracking in Finance.
Xiuyuan Huang, Zepeng Zhang, and Ziping Zhao.
Proceedings of the 55th Annual Asilomar Conference on Signals, Systems, and Computers (ACSSC/Asilomar), Pacific Grove, CA, USA, Oct. 31st - Nov. 3rd, 2021.

[ paper ]

Sparse Reduced-Rank Regression With Adaptive Selection of Groups of Predictors.
Quan Wei, Yujia Zhang, and Ziping Zhao.
Proceedings of the 55th Annual Asilomar Conference on Signals, Systems, and Computers (ACSSC/Asilomar), Pacific Grove, CA, USA, Oct. 31st - Nov. 3rd, 2021.

[ paper ]

Vast Portfolio Selection With Submodular Norm Regularization.
Zepeng Zhang and Ziping Zhao.
Proceedings of the 29th European Signal Processing Conference (EUSIPCO), Dublin, Ireland, Aug. 23-27, 2021.
[ paper ]
Scalable Financial Index Tracking With Graph Neural Networks.
Zepeng Zhang and Ziping Zhao.
Proceedings of the 21st IEEE Statistical Signal Processing Workshop (SSP), Rio de Janeiro, Brazil, July 11-14, 2021.

[ paper ]

Globally Convergent Algorithms For Learning Multivariate Generalized Gaussian Distributions.
Bin Wang, Huanyu Zhang, Ziping Zhao, and Ying Sun.
Proceedings of the 21st IEEE Statistical Signal Processing Workshop (SSP), Rio de Janeiro, Brazil, July 11-14, 2021.

[ paper ]

Inspecting the Running Process of Horizontal Federated Learning via Visual Analytics.
Quan Li, Xiguang Wei, Huanbin Lin, Yang Liu, Tianjian Chen, and Xiaojuan Ma.
IEEE Transactions on Visualization and Computer Graphics, 2021, PP. DOI (identifier) 10.1109/TVCG.2021.3074010

[ paper ]

Inspecting the Process of Bank Credit Rating via Visual Analytics.
Qiangqiang Liu, Quan Li, Zhihua Zhu, Tangzhi Ye, and Xiaojuan Ma.
In Proceedings of IEEE VIS 2021.

[ paper ]

Knowledge Graph Enhanced Event Extraction in Financial Documents.
Kaihao Guo, Tianpei Jiang, and Haipeng Zhang.
Proceedings of the 2020 IEEE International Conference on Big Data (Big Data) (pp. 1322-1329).

[ paper ]

A Deep Learning-Aided Approach to Portfolio Design for Financial Index Tracking.
Zepeng Zhang and Ziping Zhao
Proceedings of the 54th Annual Asilomar Conference on Signals, Systems, and Computers (ACSSC/Asilomar), Pacific Grove, CA, USA, Nov. 1-4, 2020.

[ paper ]

Online Robust Reduced-Rank Regression.
Fin Yang and Ziping Zhao.
Proceedings of the 11th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, June 8-11, 2020 (Best Student Paper Award Finalist).

[ paper ]

Large-Scale Regularized Portfolio Selection via Convex Optimization.
Ziping Zhao and Daniel P. Palomar.
Proceedings of the 7th IEEE Global Conference on Signal and Information Processing (GlobalSIP), Ottawa, ON, Canada, Nov. 11-14, 2019 (invited).

[ paper ]

Optimal Mean-Reverting Portfolio With Leverage Constraint for Statistical Arbitrage in Finance.
Ziping Zhao, Rui Zhou, and Daniel P. Palomar.
IEEE Transactions on Signal Processing (TSP), vol. 67, no. 7, pp. 1681-1695, April 2019.

[ paper ]

Optimal Portfolio Design for Statistical Arbitrage in Finance.
Ziping Zhao, Rui Zhou, Zhongju Wang, and Daniel P. Palomar.
Proceedings of the 20th IEEE Statistical Signal Processing Workshop (SSP), Freiburg, Germany, June 10-13, 2018.

[ paper ]

Mean-Reverting Portfolio with Budget Constraint.
Ziping Zhao and Daniel P. Palomar.
IEEE Transactions on Signal Processing (TSP), vol. 66, no. 9, pp. 2342-2357, May 2018.

[ paper ]

Mean-Reverting Portfolio Design via Majorization-Minimization Method.
Ziping Zhao and Daniel P. Palomar
Proceedings of the 50th Asilomar Conference on Signals, Systems, and Computers (ACSSC/Asilomar), Pacific Grove, CA, USA, Nov. 6-9, 2016.

[ paper ]