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Research
My research interests include
Sustainable and Impact Investing;
Machine Learning Theory and Applications;
Market Microstructure and Liquidity;
Adaptive Markets, Evolutionary Foundations of Economic Behavior and Intelligence.
My Google Scholar profile.
AWARDS
GRANTS
国家重点研发计划，青年科学家项目，主持，“数据与机理融合的金融风险预警方法研究”，2023-2027
国家自然科学基金，面上项目，主持，“绿色投资组合和风险管理的理论与应用”，2023-2026
国家高层次人才计划青年项目，主持，2022-2024
国家自然科学基金，专项项目，参与，“多源时空数据协同的新型能源系统多尺度风险管理”，2024-2027
tyc234cc 太阳成集团基金会项目，“统计与人工智能模型前沿研究支持项目”，2023-2025
Society of Actuaries (SOA) Grant，参与，“ESG for the Insurance and Pension Industry in the Asia Pacific Market”, 2022
tyc234cc 太阳成集团启动经费，2021-2023
SELECTED PUBLICATIONS (BY TOPIC; INCLUDING PREPRINTS)
Book
Sustainable and Impact Investing
Portfolio Optimization for R&D Projects: A Real Options Dynamic Programming Approach
Leonid Kogan, Andrew W. Lo, Qingyang Xu, and Ruixun Zhang.
Under review.
Estimating Correlations Between Clinical Trial Outcomes Using Generalized Estimating Equation
Yuehao Dai, Andrew W. Lo, Manish Singh, Qingyang Xu, and Ruixun Zhang.
Under review.
Optimal Impact Portfolios with General Dependence and Marginals
Andrew W. Lo, Lan Wu, Ruixun Zhang, and Chaoyi Zhao.
Operations Research, 72(5), 1775-1789, 2024. [pdf][pdf of technical appendix][journal]
Quantifying the Returns of ESG Investing: An Empirical Analysis with Six ESG Metrics
Florian Berg, Andrew W. Lo, Roberto Rigobon, Manish Singh, and Ruixun Zhang.
The Journal of Portfolio Management, 50(8), 216-238, 2024. [SSRN] [journal]
Measuring and Optimizing the Risk and Reward of Green Portfolios
Andrew W. Lo, Ruixun Zhang, and Chaoyi Zhao.
Journal of Impact and ESG Investing, 3(2), 55-93, 2022. [pdf][journal]
Statistical Modeling and Machine Learning: Theory and Applications
On Consistency of Signature Using Lasso
Xin Guo, Ruixun Zhang, and Chaoyi Zhao.
Immediate revision, Operations Research. [arxiv]
The checkerboard copula and dependence concepts
Liyuan Lin, Ruodu Wang, Ruixun Zhang, and Chaoyi Zhao.
Major revision, SIAM Journal on Financial Mathematics. [arxiv]
Spectral Volume Models: High-Frequency Periodicities in Intraday Trading Activities
Lintong Wu, Ruixun Zhang, and Yuehao Dai.
Major revision, Management Science. [SSRN]
2024 Annual Chicago conference on Market Microstructure, Quantitative Trading, High Frequency and Large Data, INFORMS 2023, the 2023 Asian Meeting of the Econometric Society, 2022 CSIAM Financial Math Conference, Seventh PKU-NUS Annual International Conference on Quantitative Finance and Economics, Oxford Statistics and Machine Learning in Finance Seminar, HKUST-Guangzhou FinTech Thrust, Chinese Academy of Sciences, Beihang University seminar
Debiasing Watermarks for Large Language Models via Maximal Coupling
Yangxinyu Xie, Xiang Li, Tanwi Mallick, Weijie Su, and Ruixun Zhang.
Major revision, Journal of the American Statistical Association. [arxiv]
High-Frequency Liquidity in the Chinese Stock Market: Measurements, Patterns, and Determinants
Ruixun Zhang, Chaoyi Zhao, Yufan Chen, Lintong Wu, Yuehao Dai, Ermo Chen, and Lan Wu.
Major revision, Pacific-Basin Finance Journal. [SSRN]
Periodic Trading Activities in Financial Markets: Mean-field Liquidation Game with Major-Minor Players
Yufan Chen, Lan Wu, Renyuan Xu, and Ruixun Zhang.
Under review. [SSRN]
Deep Partially Linear Models
Zhiqu Bu, Yufan Chen, Weijie Su, Lintong Wu, and Ruixun Zhang.
Under review.
A Hawkes Process Analysis of High-Frequency Price Endogeneity and Market Efficiency
Jingbin Zhuo, Yufan Chen, Bang Zhou, Baiming Lang, Lan Wu, and Ruixun Zhang$.
European Journal of Finance, 30(9), 949-979, 2024. [pdf][journal]
Explainable Machine Learning Models of Consumer Credit Risk
Randall Davis, Andrew W. Lo, Sudhanshu Mishra, Arash Nourian, Manish Singh, Nicholas Wu, and Ruixun Zhang.
Journal of Financial Data Science, 6(3), 9-39, 2023. [pdf] [journal] [SSRN]
Interpretable Image-Based Deep Learning for Price Trend Prediction in ETF Markets
Ruixun Zhang, Chaoyi Zhao, and Guanglian Lin.
European Journal of Finance, 2023. [pdf][journal]
Lighting Every Darkness in Two Pairs: A Calibration-Free Pipeline for RAW Denoising
Xin Jin, Jia-Wen Xiao, Ling-Hao Han, Chunle Guo, Ruixun Zhang, Xialei Liu, and Chongyi Li
International Conference on Computer Vision (ICCV), 2023. [pdf]
Designing An Illumination-Aware Network for Deep Image Relighting
Zuo-Liang Zhu, Zhen Li, Ruixun Zhang, Chun-Le Guo, and Ming-Ming Cheng.
IEEE Transactions on Image Processing, 31, 5396-5411, 2022. [pdf] [journal]
IBNet: Interactive branch network for salient object detection
Xian Fang, Jinchao Zhu, Ruixun Zhang, Xiuli Shao, and Hongpeng Wang.
Neurocomputing, 465, 574-583, 2021. [pdf][journal]
Collaborative learning in bounding box regression for object detection
Xian Fang, Zengsheng Kuang, Ruixun Zhang, Xiuli Shao, and Hongpeng Wang.
Pattern Recognition Letters, 148, 121-127, 2021. [pdf][journal]
Subspace Clustering with Block Diagonal Sparse Representation
Xian Fang, Ruixun Zhang, Zhengxin Li, and Xiuli Shao.
Neural Processing Letters, 1-20, 2021. [pdf][journal]
A Plug and Play Fast Intersection Over Union Loss for Boundary Box Regression
Zengsheng Kuang, Xian Fang, Ruixun Zhang, Xiuli Shao, and Hongpeng Wang.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1705-1709. [journal]
Learning Sparse Features with Lightweight ScatterNet for Small Sample Training
Zihao Dong, Ruixun Zhang, Xiuli Shao, and Zengsheng Kuang.
Knowledge Based Systems, 205, 106315, 2020. [pdf][journal]
Scale-Recursive Network with point supervision for crowd scene analysis
Zihao Dong, Ruixun Zhang, Xiuli Shao, and Yumeng Li.
Neurocomputing, 384, 314-324, 2020. [pdf][journal]
Recurrent Collaborative Filtering for Unifying General and Sequential Recommender
Disheng Dong, Xiaolin Zheng, Ruixun Zhang, and Yan Wang.
International Joint Conference on Artificial Intelligence (IJCAI), 3350-3356, 2018. [pdf][conference]
Adaptive Markets, Evolutionary Foundations of Economic Behavior and Intelligence;
Social Contagion and the Evolutionary Survival of Diverse Investment Styles
David Hirshleifer, Andrew W. Lo, and Ruixun Zhang.
Journal of Economic Dynamics and Control, 154, 1-36, 2023. [pdf] [journal]
The Wisdom of Crowds vs. the Madness of Mobs: An Evolutionary Model of Bias, Polarization, and Other Challenges to Collective Intelligence
Andrew W. Lo and Ruixun Zhang.
Collective Intelligence, 1(1), 1-22, 2022. [pdf][journal]
The evolutionary origin of Bayesian heuristics and finite memory
Andrew W. Lo and Ruixun Zhang.
iScience, 24, 102853, 2021. [pdf][journal]
To maximize or randomize? An experimental study of probability matching in financial decision making
Andrew W. Lo, Katherine P. Marlowe, and Ruixun Zhang.
Plos ONE, 16(8), e0252540, 2021. [pdf][journal]
The Growth of Relative Wealth and the Kelly Criterion
Andrew W. Lo, H. Allen Orr, and Ruixun Zhang.
Journal of Bioeconomics, 20(1), 49-67, 2018. [pdf][journal]
Variety is the Spice of Life: Irrational Behavior as Adaptation to Stochastic Environments
Thomas J. Brennan, Andrew W. Lo, and Ruixun Zhang.
Quarterly Journal of Finance, 8(3), 1850009, 2018. [pdf][journal]
The Origin of Risk Aversion
Ruixun Zhang, Thomas J. Brennan, and Andrew W. Lo.
Proceedings of the National Academy of Sciences, 111(50), 17777-17782, 2014. [pdf][journal]
Group Selection as Behavioral Adaptation to Systematic Risk
Ruixun Zhang, Thomas J. Brennan, and Andrew W. Lo.
PLoS ONE, 9(10), e110848, 2014. [pdf][journal]
FULL LIST OF PUBLICATIONS
2024. The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics. Andrew W. Lo and Ruixun Zhang. Oxford University Press.
2024. Performance Attribution for Portfolio Constraints. Andrew W. Lo and Ruixun Zhang. Management Science, forthcoming. Winner of the 2024 Commodity and Energy Markets Association (CEMA) Questrom-CEMA Best Paper Prize. Winner of the CFRI&CIRF-China Finance Review International Research Excellence Award (Asset Management).
2024. Optimal Impact Portfolios with General Dependence and Marginals. Andrew W. Lo, Lan Wu, Ruixun Zhang, and Chaoyi Zhao. Operations Research, 72(5), 1775-1789. Winner of the Best Paper Prize for Young Scholars, Annual Conference of the Operations Research Society of China (Financial Engineering and Risk Management Branch).
2024. Toward Interpretable Machine Learning: Evaluating Models for Heterogeneous Predictions. Ruixun Zhang. Annals of Operations Research, forthcoming.
2024. Quantifying the Returns of ESG Investing: An Empirical Analysis with Six ESG Metrics. Florian Berg, Andrew W. Lo, Roberto Rigobon, Manish Singh, and Ruixun Zhang. The Journal of Portfolio Management, 50(8), 216-238, 2024.
2024. Quantifying the Impact of Impact Investing. Andrew W. Lo and Ruixun Zhang. Management Science, 70(10), 7161-7186. Winner of the International Centre for Pension Management (ICPM) Research Award, Honourable Mention.
2024. A Hawkes Process Analysis of High-Frequency Price Endogeneity and Market Efficiency. Jingbin Zhuo, Yufan Chen, Bang Zhou, Baiming Lang, Lan Wu, and Ruixun Zhang. European Journal of Finance, 30(9), 949-979.
2023. Social Contagion and the Evolutionary Survival of Diverse Investment Styles. David Hirshleifer, Andrew W. Lo, and Ruixun Zhang. Journal of Economic Dynamics and Control, 154, 1-36.
2023. Interpretable Image-Based Deep Learning for Price Trend Prediction in ETF Markets. Ruixun Zhang, Chaoyi Zhao, and Guanglian Lin. European Journal of Finance, forthcoming.
2023. Explainable Machine Learning Models of Consumer Credit Risk. Randall Davis, Andrew W. Lo, Sudhanshu Mishra, Arash Nourian, Manish Singh, Nicholas Wu, and Ruixun Zhang. Journal of Financial Data Science, 6(3), 9-39.
2023. Lighting Every Darkness in Two Pairs: A Calibration-Free Pipeline for RAW Denoising. Xin Jin, Jia-Wen Xiao, Ling-Hao Han, Chunle Guo, Ruixun Zhang, Xialei Liu, Chongyi Li. International Conference on Computer Vision (ICCV).
2022. Measuring and Optimizing the Risk and Reward of Green Portfolios. Andrew W. Lo, Ruixun Zhang, and Chaoyi Zhao. Journal of Impact and ESG Investing, 3(2), 55-93. Winner of the S&P Global Academic ESG Research Award.
2022. The Wisdom of Crowds vs. the Madness of Mobs: An Evolutionary Model of Bias, Polarization, and Other Challenges to Collective Intelligence. Andrew W. Lo and Ruixun Zhang. Collective Intelligence, 1(1).
2022. Designing An Illumination-Aware Network for Deep Image Relighting. Zuo-Liang Zhu, Zhen Li, Ruixun Zhang, Chun-Le Guo, and Ming-Ming Cheng. IEEE Transactions on Image Processing, 31, 5396-5411.
2021. The Evolutionary Origin of Bayesian Heuristics and Finite Memory. Andrew W. Lo and Ruixun Zhang. iScience, 24: 102853.
2021. To Maximize or Randomize? An Experimental Study of Probability Matching in Financial Decision Making. Andrew W. Lo, Katherine P. Marlowe, and Ruixun Zhang. PLoS ONE, 16(8): e0252540.
2021. IBNet: Interactive branch network for salient object detection. Xian Fang, Jinchao Zhu, Ruixun Zhang, Xiuli Shao, and Hongpeng Wang. Neurocomputing, 465, 574-583.
2021. Collaborative learning in bounding box regression for object detection. Xian Fang, Zengsheng Kuang, Ruixun Zhang, Xiuli Shao, and Hongpeng Wang. Pattern Recognition Letters, 148, 121-127.
2021. Subspace Clustering with Block Diagonal Sparse Representation. Xian Fang, Ruixun Zhang, Zhengxin Li, Xiuli Shao. Neural Processing Letters, 53, 4293–4312.
2021. A Plug and Play Fast Intersection Over Union Loss for Boundary Box Regression. Zengsheng Kuang, Xian Fang, Ruixun Zhang, Xiuli Shao, and Hongpeng Wang. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1705-1709.
2021. Detection of Defect Proportion for Workpiece Surface Based on a Fusion Prediction Model. Sikai Tao, Ruixun Zhang, and Yumeng Li. IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), 1093-1098.
2021. Discrete Mathematics, (Textbook, in Chinese). Ruixun Zhang, Xiuli Shao, and Mingming Ren. China Machine Press.
2020. Learning Sparse Features with Lightweight ScatterNet for Small Sample Training. Zihao Dong, Ruixun Zhang, Xiuli Shao, and Zengsheng Kuang. Knowledge Based Systems, 205, 106315.
2020. Scale-Recursive Network with point supervision for crowd scene analysis. Zihao Dong, Ruixun Zhang, Xiuli Shao, and Yumeng Li. Neurocomputing, 384, 314-324.
2019. Multi-scale Discriminative Location-Aware Network for Few-Shot Semantic Segmentation. Zihao Dong, Ruixun Zhang, Xiuli Shao and Hongyu Zhou. IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), 42-47.
2018. Biological Economics, (two-volume book). Andrew W. Lo and Ruixun Zhang (co-editor). Edward Elgar Publishing.
2018. The Growth of Relative Wealth and the Kelly Criterion. Andrew W. Lo, H. Allen Orr, and Ruixun Zhang. Journal of Bioeconomics, 20(1), 49-67.
2018. Variety is the Spice of Life: Irrational Behavior as Adaptation to Stochastic Environments. Thomas J. Brennan, Andrew W. Lo, and Ruixun Zhang. Quarterly Journal of Finance, 8(3), 1850009.
2018. Recurrent Collaborative Filtering for Unifying General and Sequential Recommender. Disheng Dong, Xiaolin Zheng, Ruixun Zhang, and Yan Wang. The 27th International Joint Conference on Artificial Intelligence (IJCAI), 3350-3356.
2018. A New Combined CNN-RNN Model for Sector Stock Price Analysis. Ruixun Zhang, Zhaozheng Yuan, and Xiuli Shao. IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), 546-551.
2014. The Origin of Risk Aversion. Ruixun Zhang, Thomas J. Brennan, and Andrew W. Lo. Proceedings of the National Academy of Sciences, 111(50), 17777-17782.
2014. Group Selection as Behavioral Adaptation to Systematic Risk. Ruixun Zhang, Thomas J. Brennan, and Andrew W. Lo. PLoS ONE, 9(10), e110848.
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