Lingfei Li (Rw)                              


Assistant Professor

Department of Systems Engineering and Engineering Management

The Chinese University of Hong Kong


Office: Room 608, William M.M.W. Engineering Building

Phone: (852) 3943-8329

Fax: (852) 2603-5505

Email: lfli at


Biography   Research Interests   Publications   Teaching   Grants   Prospective Students  




       Ph.D. Industrial Engineering and Management Sciences, Northwestern University, Evanston IL, USA, 2012.

       M.S. Industrial Engineering and Management Sciences, Northwestern University, Evanston IL, USA, 2008.

       B.S. Applied Mathematics, Peking University, Beijing, China, 2007.



       Assistant Professor, Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, June 2012 to present.

       Associate Quantitative Analyst, Commodities Strategies Group, Morgan Stanley, 2009 Summer.


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Research Interests

Financial Engineering, Mathematical Finance, Computational Finance.

My research is currently focused on stochastic modelling in finance, and developing analytical and computational methods for pricing and hedging various types of financial derivatives.


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     1.            L. Li and G. Zhang (2016). Option pricing in some non-Lvy jump models. SIAM Journal on Scientific Computing 38(4), B539-B569. (PDF, Link)

     2.            J. Li, L. Li and R. Mendoza-Arriaga (2016). Additive subordination and its applications in finance. Finance and Stochastics 20(3), 589-634. (PDF, Link)

     3.            L. Li, R. Mendoza-Arriaga and D. Mitchell (2016). Analytical representations for the basic affine jump diffusion. Operations Research Letters 44(1), 121-128. (PDF, Link)

     4.            L. Li, R. Mendoza-Arriaga, Z. Mo and D. Mitchell (2016). Modelling electricity prices: a time change approach. Quantitative Finance 16(7), 1089-1109. (PDF, Link)

     5.            L. Li, X. Qu and G. Zhang (2016). An efficient algorithm based on eigenfunction expansions for some optimal timing problems in finance. Journal of Computational and Applied Mathematics 294(1), 225-250. (PDF, Link)

     6.            L. Li and V. Linetsky (2015). Discretely monitored first passage problems and barrier options: an eigenfunction expansion approach. Finance and Stochastics 19(4), 941-977. (PDF, Link)

     7.            L. Li and V. Linetsky (2014). Time-changed Ornstein-Uhlenbeck processes and their applications in commodity derivative models. Mathematical Finance 24(2), 289-330. (PDF, Link)

     8.            L. Li and V. Linetsky (2014). Optimal stopping in infinite horizon: an eigenfunction expansion approach. Statistics and Probability Letters 85(1), 122-128. (PDF, Link)

     9.            L. Li and R. Mendoza-Arriaga (2013). Ornstein-Uhlenbeck processes time-changed with additive subordinators and their application in commodity derivative models. Operations Research Letters 41(5), 521-525. (PDF, Link)

 10.            L. Li and V. Linetsky (2013). Optimal stopping and early exercise: an eigenfunction expansion approach. Operations Research 61(3), 625-643. (PDF, Link)

 11.            D. Lim, L. Li and V. Linetsky (2012). Evaluating callable and putable bonds: an eigenfunction expansion approach. Journal of Economic Dynamics and Control 36(12), 1888-1908. (PDF, Link)


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       SEEM 2440 Engineering Economics, Fall of 2012, 2013, 2014, 2015, 2016.

       SEEM 2520 Fundamentals in Financial Engineering, Spring of 2014, Fall of 2015, 2016.

       SEEM 5340 Stochastic Calculus, Spring of 2015, 2016, 2017.


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       Principal Investigator, HK Research Grant Council GRF Grant, ``Research topics for some jump processes in financial engineering'', 2017/01/01 to 2019/12/31.

       Principal Investigator, HK Research Grant Council ECS Grant, ``Time dependency modeling in financial engineering'', 2015/01/01 to 2017/12/31.

       Principal Investigator, CUHK Direct Grant for Research, ``Spectral methods for optimal stopping and first passage problems with applications in financial engineering and corporate investment'', 2013/01/01 to 2014/12/31.


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Prospective Students

I am always looking for self-motivated, hardworking PhD students with solid mathematics training, strong analytical ability and good programming skills. Students with a bachelor/master degree in math, applied math, probability, statistics are preferred, and knowledge in finance is not required. All interested candidates should apply for the Hong Kong PhD fellowship. Master degree is not a requirement for PhD application. Application details can be found in For inquiries about the application, please contact the departments general office.


If you are interested in doing post-doc with me, please send me your previous publications, doctoral thesis and research plan. For post-docs, your PhD field must be financial mathematics, probability, statistics, applied math, math or a field that is closely related to my research.


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Last Updated 11/08/2016