Professor Ben Feng

Portfolio Optimisation Advisor

Professor Feng is working with Integral ILS to develop a portfolio optimisation process based on the latest optimisation theory and techniques.

Professor Feng’s research interests include quantitative risk management, financial engineering, Monte Carlo simulation design and analysis, and non-linear optimisation.

Professor Feng is particularly interested in the intersection of these fields such as statistical machine learning, portfolio optimization, efficient simulation algorithms for risk management, etc. His professional background in actuarial science guides his research towards applying advanced theoretical methodologies to solve complex practical problems. His current research topics include:

  • Green simulation: reusing outputs in repeated simulation experiments
  • Quantitative risk management in investment guarantees
    Efficient experiment design for nested simulations
  • Machine learning in actuarial science
  • Quantification of data uncertainty
  • Operations research

Education/biography:

  • 2016 PhD (Industrial Engineering and Management Sciences) Northwestern University, U.S.A.
  • 2011 MMATH (Actuarial Science) University of Waterloo, Canada. Advisor: Ken Seng Tan
  • 2010 BMATH (Actuarial Science and Operations Research) University of Waterloo, Canada
  • Professor Feng joined the Department of Statistics and Actuarial Science at the University of Waterloo in July, 2016 as Assistant Professor.

 

Selected publications:

  • Feng, M. and Staum, J. (2017). Green Simulation: reusing the output of repeated experiments, ACM TACM Transactions on Modeling and Computer Simulation (TOMACS), forthcoming
  • Feng, M., Mitchell, J. E., Pang, J. S., Shen, X., & Waechter, A. Complementarity Formulations of l0-norm Optimization Problems. Pacific Journal of Optimization, forthcoming
  • Staum, J, Feng M., and Liu M. “Systemic risk components in a network model of contagion.” IIE Transactions 48.6 (2016): 501-510.
  • Feng, M and Staum J. “Green simulation with database Monte Carlo.” Proceedings of the 2016 Winter Simulation Conference. IEEE Press, 2016.
  • Feng, M. and Staum J. “Green simulation designs for repeated experiments.” Proceedings of the 2015 Winter Simulation Conference. IEEE Press, 2015.
  • Feng, M, Waechter A, and Staum J. “Practical algorithms for value-at-risk portfolio optimization problems.” Quantitative Finance Letters 3.1 (2015): 1-9.
  • Feng, M, and Tan K.S. “Coherent distortion risk measures in portfolio selection.” Systems Engineering Procedia 4 (2012): 25-34.
 
 

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