Research

My research interests include

  • Sustainable and Impact Investing;

  • Market Microstructure and Liquidity;

  • Machine Learning Theory and Applications;

  • Adaptive Markets, Evolutionary Foundations of Economic Behavior and Intelligence.

My Google Scholar profile.

AWARDS and GRANTS

SELECTED PUBLICATIONS (BY TOPIC; INCLUDING PREPRINTS)

Book

  • The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics
    Andrew W. Lo and Ruixun Zhang.
    Oxford University Press, 2024. [Order on Amazon]

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.

  • Optimal Impact Portfolios with General Dependence and Marginals
    Andrew W. Lo, Lan Wu, Ruixun Zhang, and Chaoyi Zhao.
    Operations Research, forthcoming. [pdf][pdf of technical appendix][journal]

    • Best Paper Prize for Young Scholars, Annual Conference of the Operations Research Society of China (Financial Engineering and Risk Management Branch)

Microstructure, Liquidity, FinTech

  • Spectral Volume Models: High-Frequency Periodicities in Intraday Trading Activities
    Lintong Wu, Ruixun Zhang, and Yuehao Dai.
    Under review. [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

  • Estimating Market Liquidity from Daily Data: Marrying Microstructure Models and Machine Learning
    Yuehao Dai and Ruixun Zhang.
    Under review. [SSRN]

    • INFORMS 2023, the 2023 Asian Meeting of the Econometric Society, Seventh PKU-NUS Annual International Conference on Quantitative Finance and Economics

  • 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.
    Under review. [SSRN]

    • 2022 Bachelier Finance Society World Congress, 2022 INFORMS, 2022 CSIAM Financial Math Conference

  • When Do Models Make Make Money? An Analytical Estimation of Profitability Based on Return Predictability
    Ruixun Zhang, Yufan Chen, and Lan Wu.
    Under review.

    • 2022 Bachelier Finance Society World Congress, 2022 CSIAM Financial Math Conference, 2023 CFRI&CIRF Joint Conference

  • Toward Interpretable Machine Learning: Evaluating Models for Heterogeneous Predictions
    Ruixun Zhang.
    Annals of Operations Research, 2024. [pdf][journal].

  • 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, 2024. [pdf][journal]

  • 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]

  • 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, 2023. [pdf] [journal] [SSRN]

Machine Learning: Theory and Applications

  • Deep Partially Linear Models
    Zhiqu Bu, Yufan Chen, Weijie Su, Lintong Wu, and Ruixun Zhang.
    Under review.

  • On Consistency of Signatures Using Lasso
    Xin Guo, Ruixun Zhang, and Chaoyi Zhao.
    Under review. [arxiv]

    • 2023 ICIAM, Oxford-Man Institute of Quantitative Finance seminar, London School of Economics and Political Science (LSE) Joint Risk and Stochastics and Financial Mathematics Seminar

  • The checkerboard copula and dependence concepts
    Liyuan Lin, Ruodu Wang, Ruixun Zhang, and Chaoyi Zhao.
    Under review. [arxiv]

  • 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]

  • 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;

  • 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. [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

  1. 2024. The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics. Andrew W. Lo and Ruixun Zhang. Oxford University Press.

  2. 2024. Optimal Impact Portfolios with General Dependence and Marginals. Andrew W. Lo, Lan Wu, Ruixun Zhang, and Chaoyi Zhao. Operations Research, forthcoming. Winner of the Best Paper Prize for Young Scholars, Annual Conference of the Operations Research Society of China (Financial Engineering and Risk Management Branch).

  3. 2024. Toward Interpretable Machine Learning: Evaluating Models for Heterogeneous Predictions. Ruixun Zhang. Annals of Operations Research, forthcoming.

  4. 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, forthcoming.

  5. 2023. Quantifying the Impact of Impact Investing. Andrew W. Lo and Ruixun Zhang. Management Science, forthcoming. Winner of the International Centre for Pension Management (ICPM) Research Award, Honourable Mention.

  6. 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, 2023.

  7. 2023. Interpretable Image-Based Deep Learning for Price Trend Prediction in ETF Markets. Ruixun Zhang, Chaoyi Zhao, and Guanglian Lin. European Journal of Finance, 2023.

  8. 2023. 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, 2023.

  9. 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, 2023.

  10. 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), 2023.

  11. 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.

  12. 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).

  13. 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.

  14. 2021. The Evolutionary Origin of Bayesian Heuristics and Finite Memory. Andrew W. Lo and Ruixun Zhang. iScience, 24: 102853.

  15. 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.

  16. 2021. IBNet: Interactive branch network for salient object detection. Xian Fang, Jinchao Zhu, Ruixun Zhang, Xiuli Shao, and Hongpeng Wang. Neurocomputing, 465, 574-583.

  17. 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.

  18. 2021. Subspace Clustering with Block Diagonal Sparse Representation. Xian Fang, Ruixun Zhang, Zhengxin Li, Xiuli Shao. Neural Processing Letters, 53, 4293–4312.

  19. 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.

  20. 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.

  21. 2021. Discrete Mathematics, (Textbook, in Chinese). Ruixun Zhang, Xiuli Shao, and Mingming Ren. China Machine Press.

  22. 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.

  23. 2020. Scale-Recursive Network with point supervision for crowd scene analysis. Zihao Dong, Ruixun Zhang, Xiuli Shao, and Yumeng Li. Neurocomputing, 384, 314-324.

  24. 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.

  25. 2018. Biological Economics, (two-volume book). Andrew W. Lo and Ruixun Zhang (co-editor). Edward Elgar Publishing.

  26. 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.

  27. 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.

  28. 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.

  29. 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.

  30. 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.

  31. 2014. Group Selection as Behavioral Adaptation to Systematic Risk. Ruixun Zhang, Thomas J. Brennan, and Andrew W. Lo. PLoS ONE, 9(10), e110848.