Yuying Li

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Waterloo

 

 

 

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Description: Description: Yuying2018.JPG
Professor (PhD, Waterloo, 1988)
School of Computer Science
DC 3623
200 University Avenue West
University of Waterloo
Waterloo, Ontario, Canada, N2L 3G1

email: yuying@uwaterloo.ca
phone: 519 888 4567 ext. 37825
fax: 519 885 1208

Research and Publications

Google Scholar Link

Panda (Predictive Advanced Nonlinear Diagnostic Analyzer, Aditya Tayal, Yuying Li, Tom Coleman), ranks the fourth place in the Heritage Health Provider Network competition.

    My current research interest is data mining and computational finance. I am generally interested in design, analysis, and implementation of algorithms for scientific computing problems. More specifically, I am interested in:

    • Learning data driven optimal financial decisions, focusing particularly on robust and interpretable financial model learning
    • supervised, semi-supervised learning, feature selection, ordinal regression, similarity measures
    • rare class learning, e.g., Fraud detection, unsupervised auto insurance fraud detection
    • Computational finance

    Sample recent publications: ( More Publications here )

    • M. Chen, M. Shirazi, P. Forsyth and Y. Li, ''Machine learning and Hamilton-Jacobian Bellman equation for optimal decumulation'', submitted to Journal of Computational and Applied Mathematics, 2023.
    • P. van Staden, P. Forsyth and Y. Li, ''A parsimonious neural network approach to solve portfolio optimization problems without using dynamic programming'', submitted to Annals of Operation Research, 2023.
    • C. Ni, P. Forsyth and Y. Li, ''Optimal asset allocation in a high inflation regime: a leverage-feasible neural network approach'', submitted to Journal of Quantitative Finance, 2023.
    • P. van Staden, P. Forsyth and Y. Li, ''Across-time risk-aware strategies for outperforming benchmark'', to appear in European Journal of Operation Research, 2023.
    • P. van Staden and P. Forsyth and Y. Li, ''Beating a constant weight benchmark: easier done than said'', to appear in Journal of Theoretical and Applied Finance, 2023.
    • P. van Staden and P. Forsyth and Y. Li, ''Beating a benchmark: dynamic programming may not be the right numerical approach'', SIAM J. Financial Mathematics, 14:2 (2023) 407-451.
    • C. Ni, Y. Li, P. Forsyth, R. Carroll, ''Optimal asset allocation for outperforming stochastic benchmark target'', Quantitative Finance, 22(9), (2022) 1595-1626.
    • K. Nian, T. F. Coleman, Y. Li '' Learning Sequential Option Hedging Models from Market Data'', Journal of Banking and Finance, 133, 2021.
    • K. Zheng, Y. Li, W. Xu ''Regime switching model estimation: spectral clustering hidden Markov Model'', Annals of Operation Research, 303, 297-319, 2021.
    • C. Schofield, J. Wang, Y. Li ''Quantum walk inspired algorithm for graph similarity and isomorphism'', Quantum Information Processing, 19(9) 1-19, 2020.
    • H. Zhang, K. Nian, T.F. Coleman, Y. Li ''Spectral ranking and unsupervised feature selection for point, collective, and contextual anomaly detection'', International J. Data Science and Analytics, 9, 189-204, 2020.
    • Y. Li and P. Forsyth, ''A data-driven neural network approach to optimal asset allocation for target based defined contribution pension plans'', Insurance: Mathematics and Economics, 86, 189-204, 2019.
    • Coleman ,and Y. Li, ''Learning Minimum Variance Discrete Hedging from Market'', Journal of Quantitative Finance, 18(7), 1-14, 2018.
    • A. Tayal, T. F. Coleman ,and Y. Li, ''Bounding the Difference Between RankRC and RankSVM nd Application to Multi-Level Rare Class Kernel Ranking'', Data Mining and Knowledge Discovery, 32 (2), 417-452, 2018.
    • E. Cheung and Y. Li, ''Solving Separable Nonsmooth Problems using Frank-Wolfe with Uniform Affine Approximations'', IJCAI, 3035-3041, 2018.
    • E. Cheung and Y. Li, ''Self-training with adaptive regularization for S3VM'', Neural Networks (IJCNN), 2017 International Joint Conference on, 3633-3640, 2017
    • E. Cheung and Y. Li, ''Projection Free Rank Drop Steps'', IJCAI, 2017
    • K. Nian, H. Zhang.A. Tayal, T. F. Coleman ,and Y. Li, ''Auto insurance fraud detection using unsupervised spectral ranking for anomaly'', ,The Journal of Finance and Data Science 2 (1), 58-75, 2016
    • DM Dang, PA Forsyth, and Y. Li, ''Convergence of the embedded mean-variance optimal points with discrete sampling'', pdf, Numerische Mathematik, 132 (2), 271-302, 2016
    • A. Tayal, T. F. Coleman ,and Y. Li, ''RankRC: Large-scale Nonlinear Rare Class Ranking'', pdf , IEEE Transactions on Knowledge and Data Engineering, Vol 27, December 2015.
    • A. Tayal, T. F. Coleman ,and Y. Li, ''Primal Explicit Max Margin Feature Selection for Nonlinear Support Vector Machines'', pdf, Pattern Recognition 47 (6), 2153-2164, 2014.
    • J. Xi,T. F. Coleman ,and Y. Li, ''A Gradual Non-convexification Method for Minimizing VaR'', pdf. Journal of Risk, vol 26, (3), 23-47,2014.
    • S. Moazeni,T. F. Coleman ,and Y. Li, ''Regularized Optimal Portfolio Optimization, an Optimal Execution Case'', pdf , Journal of Computational Optimization and Application, 55(2), 341-377, 2013.
    • S. T. Tse, P. A. Forsyth, and Y. Li, ''Preservation of Scalarization Optimal Points in the Embedding Technique for Continuous Time Mean Variance Optimization'', pdfpdf. SIAM Journal on Control and Optimization 52 (3), 1527-1536, 2015
    • T. F. Coleman,Y. Li and C. Wang, ''Stable Local Volatility Calibration Using Kernel Splines'', pdf.  Journal of Computational Optimization and Application, 55(3), 675-702, 2013.
    • T. F. Coleman and Y. Li, Optimization & Finance, Encyclopedia of Quantitative Finance, R. Cont (Ed), John Wiley \& Sons Ltd. Chichester, UK. pp. 1322-1327. 2010.
    • S. Moazeni, T. F. Coleman and Y. Li, ''Optimal Portfolio Execution Strategies and Sensitivity to Price Impact Parameters'', pdf . SIAM J. Optimization, 30, 1620-1654, 2010.
    • L. Zhu, T. F. Coleman and Y. Li, ''Min-Max Robust and CVaR Robust Mean-Variance Portfolios'', pdf . Submitted to Journal of Risk, 2007.
    • S. Moazeni, Y. Li, K. Larson, ''Execution Costs in financial markets with several institutional investors'', pdf . Proceedings of the Fourth IASTED International Conference, Financial Engineering and Application , pp 31-37, 2007.
    • T. F. Coleman, Y. Kim, Y. Li and M. Patron, '' Robustly Hedging Variable Annuities with Guarantee Under Jump and Volatility Risks'', pdf . Journal of Risk and Insurance , Vol 74, pp 347-376, June 2007.
    • C. He, T. F. Coleman, and Y. Li, ''Calibrating Volatility Function Bounds for An Uncertain Volatility Model '', pdf. Journal of Computational Finance, 13, 69-93, 2010 2006
    • C. He, T. F. Coleman, and Y. Li, ''Computation and Analysis for a Constrained Entropy Optimization Problem in Finance '', pdf . 2006. Journal of Computational and Applied Mathematics, 222(1), 159-174
    • S. Alexander, T. F. Coleman, and Yuying Li, ''Minimizing VaR and CVaR for a Por tfolio of Derivatives'', pdf. Journal of Banking and Finance, Vol. 30, no. 2, pp. 583-605, 2006.
    • T. F. Coleman, J. Henninger, Y. Li, '' Minimizing Tracking Error While Restricting the Number of Assets'', pdf. Journal of Risk, vol 8, pp. 33-56, 2006.
    • T. F. Coleman, Y. Li and M. Patron, '' Hedging Guarantees in Variable Annuities (Under Both Market and Interest Rate Risks)'', pdf, . Insurance: Mathematics and Economics , vol 38, pp. 215-228, 2006.
    • T.F. Colemanm, Y. Li, and C. Patron ``Total risk minimization'', pdf . Handbook of Financial Engineering. Published by Elsevier, Edited by John R. Birge and Vadim Linetsky, pp. 593-635, 2007.
    • C. He, J. S. Kennedy, T. F. Coleman, P. A. Forsyth, Y. Li and K. Vetzal, pdf . ''Calibration and Hedging under Jump Diffusion'', Review of Derivative Research, vol 9, pp 1-35, 2006.
    • T. F. Coleman, D. Levchenkov and Y. Li, ''Discrete hedging of American-type options using local risk minimization'', pdf. Journal of Banking and Finance, vol 31, pp 3398-3419, 2007.
    • S. Alexander, T. F. Coleman and Y. Li, ''Derivative Portfolio Hedging Based on CVaR'', pdf. New Risk Measures for the 21st Century, edited by G. Szego, pp. 3 39-363, 2004.
    • T. F. Coleman, Y. Li and M. Patron, ''Discrete Hedging under Piecewise Linear Ri sk Minimization'', pdf. Journal of Risk , Vol. 5, pp. 39-65, 2003.
    • K. Boyle, T. F. Coleman and Y. Li, ''Hedging a Portfolio of Derivatives by Modeling Cost'', pdf. IEEE Proceedings of the 2003 International Conference on Computational Intelligence for Financial Engineering (CIFEr2003), March 21-23, 2003, Hong Kong.
    • T. F. Coleman, Y. Li and A. Verma, ''A Newton Method for American Option Pricing'', pdf. Journal of Computational Finance. Vol. 5, No 3, Spring 2002: 51-78.
    • T. F. Coleman, Y. Li, Y. Kim and A. Verma, ''Dynamic Hedging with a Deterministic Volatility Function Model'', pdf. Journal of Risk , pp. 64-90, Vol. 4, 2001.
    • T. F. Coleman, Y. Li and A. Mariano, ''Segmentation of Pulmonary Nodule Image Using 1-norm Minimization'', pdf . Computational Optimization and Applications , Vol. 19, September 2001, pp. 243-272.
    • T. F. Coleman and Y. Li, ''A Trust Region and Affine Scaling Interior Point Method for Nonconvex Minimization with Linear Inequality Constraints'', pdf, . Mathematical Programming Series A , 88(1), 2000, pp. 1-32.
    • T. F. Coleman, Y. Li and Arun Verma, '' Reconstructing the Unknown Local Volatility Function'', pdf. Journal of Computational Finance, Vol. 2, 1999, pp. 77-102.
    • M. Branch, T. F. Coleman and Y. Li, ''A Subspace, Interior and Conjugate Gradient Method for Large-scale Bound-constrained Minimization Problems'', pdf. SIAM Journal on Scientific Computing, Vol. 21, 1999 pp. 1-21.