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Victor DeMiguel

Professor of Management Science and Operations; Chair, Management Science and Operations Faculty

MSc (Madrid), MSc and PhD (Stanford)

Professor Victor DeMiguel’s research focuses on the design, analysis, and application of quantitative models for managerial decision making with applications in financial portfolio selection and competition modelling.

He teaches MBA courses on Financial Modelling and Decision and Risk Analysis and a PhD seminar on Optimisation Theory and Applications. He also teaches the Strategic Decision Making module for the Advanced Development Programme of Executive Education. He is the recipient of the Junior Faculty Teaching Award for 2003/2004 and the Outstanding Core Course Teaching Award for 2008/2009 at London Business School.

Professor DeMiguel’s papers have been published in most of the top journals of his field, including Management Science, Operations Research, and Mathematics of Operations Research. One of his most popular papers received the Best Paper Award from the Institute for Quantitative Investment Research and was published in The Review of Financial Studies.

He has consulted for several companies, including ENDESA, Iberdrola, and McKinsey & Company.


Multiperiod portfolio optimization with multiple risky assets and general transaction costs

Mei X; DeMiguel V; Nogales F

Journal of Banking and Finance 2016 Vol 69:August p 108-120

Supplier capacity and intermediary profits: can less be more?

DeMiguel V; Adida E; Bakshi N

Production and Operations Management 2016 Vol 25:4 p 630-646


Parameter uncertainty in multiperiod portfolio optimization with transaction costs

DeMiguel V; Martin-Utrera A; Nogales F J

Journal of Financial and Quantitative Analysis 2015 Vol 50:6 p 1443-1471


Stock return serial dependence and out-of-sample portfolio

DeMiguel V; Nogales F J; Uppal R

Review of Financial Studies 2014 Vol 27:4 p 1031-1073


Improving portfolio selection using option-implied volatility and skewness

De Miguel V; Plyakha Y; Uppal R; Vilkov G

Journal of Financial and Quantitative Analysis 2013 Vol 48:6 p 1813-1845

Size matters: Optimal calibration of shrinkage estimators for portfolio selection

DeMiguel V; Martin-Utrera A; Nogales F J

Journal of Banking and Finance 2013 Vol 37:8 p 3018-3034


Supply chain competition with multiple manufacturers and retailers

DeMiguel V; Adida E

Operations Research 2011 Vol 59:1 p 156-172


A generalized approach to portfolio optimization: Improving performance by constraining portfolio norms

DeMiguel V; Garlappi L; Nogales F J; Uppal R

Management Science 2009 Vol 55:5 p 798-812

A stochastic multiple leader Stackelberg model: Analysis, computation, and application

DeMiguel V; Xu H

Operations Research 2009 Vol 57:5 p 1220-1235

Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy?

DeMiguel V; Garlappi L; Uppal R

Review of Financial Studies 2009 Vol 22:5 p 1915-1953

Portfolio selection with robust estimation

DeMiguel V; Nogales F J

Operations Research 2009 Vol 57:3 p 560-577


On decomposition methods for a class of partially seperable nonlinear programs

De Miguel V; Nogales F J

Mathematics of Operations Research 2008 Vol 33:1 p 119-139


A local convergence analysis of bilevel decomposition algorithms

DeMiguel V; Murray W

Optimization and Engineering 2006 Vol 7:2 p 99-133

A two-sided relaxation scheme for mathematical programs with equilibrium constraints.

DeMiguel V; et al.

SIAM Journal on Optimization 2006 Vol 16:2 p 587-609

Portfolio investment with the exact tax basis via nonlinear programming

DeMiguel V; Uppal R

Management Science 2006 Vol 51:2 p 277-290


Revenue management with correlated demand forecasting

DeMiguel V; Fridgeirsdottir K; Stefanescu C; et al.

in Proceedings of the American Statistical Association, Business and Economics Statistics Section, Alexandria, VA, 2004


Class of quadratic programming rest problems with global variables

DeMiguel V; Murray W

Technical report SOL 01-2 Dept of MS&E, Stanford University, 2001

Two decomposition algorithms for nonconvex optimization problems with global variables

DeMiguel V; Murray W

Technical report SOL 01-1, Dept of MS&E, Stanford University, 2001


An analysis of collaborative optimization methods

DeMiguel V; Murray W

in Proceedings of the Eighth AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 2000

Research Interests

  • Optimisation
  • Portfolio optimisation
  • Competition