Boston Public Library

Optimization Articles

  1. Deconstructing Black-Litterman (available through JOIM)
    Black-Litterman optimization claims to solve the problems of mean-variance optimization in practice, but our analysis demonstrates that it has limited investment value.
    Authors: Richard Michaud, David Esch, and Robert Michaud
    Publication: Journal Of Investment Management 1st quarter 2013
  2. Deconstructing Black-Litterman (draft)
    Black-Litterman optimization claims to solve the problems of mean-variance optimization in practice, but our analysis demonstrates that it has limited investment value.
    Authors: Richard Michaud, David Esch, and Robert Michaud
    Publication: Journal Of Investment Management 1st quarter 2013
  3. Non-Normality Facts and Fallacies (available through JOIM)
    This paper explains why summary rejection of normal distributions is almost always ill-advised.
    Author: David Esch
    Publication: Journal Of Investment Management 1st quarter 2010
  4. Non-Normality Facts and Fallacies (draft)
    This paper explains why summary rejection of normal distributions is almost always ill-advised.
    Author: David Esch
    Publication: September 2009
  5. The Information Ratio of Factor Based Alpha password required
    Misconceptions concerning the proper definition of breadth in Grinold’s Active Law of Management have suggested that the information ratio of optimized portfolios increases with the number of stocks in the portfolio. We show that when active return depends on factor bets, the IR has an upper bound independent of the number of stocks, but depending on the breadth of the strategy and some maximum information ratio of the joint factor bet.
    Authors: Noah Kraut, Robert O. Michaud & Richard O. Michaud
    Publication: October 2005 Newsletter.
  6. Equity Optimization Issues-V: Monte Carlo and Optimization Errors password required
    Improvements in optimization design and resolutions of fallacies in asset management practice are largely due to recent applications of Monte Carlo simulation technology.
    Authors: Richard O. Michaud & Robert O. Michaud
    Publication: August 2005 Newsletter
  7. Equity Optimization Issues-IV: The Fundamental Law of Mismanagement
    The Grinold Law of Active Management is one of the most widely referenced and misused formulas in investment theory and practice.
    Authors: Richard O. Michaud & Robert O. Michaud
    Publication: July 2005 Newsletter
  8. Equity Optimization Issues-III: Insignificant Alphas, Heterogeneous Errors
    Insignificant alphas and heterogeneous estimation error are two issues associated with performance limitations in mean variance equity portfolio optimization.
    Authors: Richard O. Michaud & Robert O. Michaud
    Publication: March 2005 Newsletter
  9. Equity Optimization Issues-II: Large Stock Universes and Scaling Alphas
    In order to obtain the provable benefits of Resampled Efficiency, a number of common ad hoc equity portfolio optimization techniques need to be avoided or corrected. This article focuses on two: the use of large stock universes and incorrect alpha scaling.
    Authors: Richard O. Michaud & Robert O. Michaud
    Publication: February 2005 Newsletter
  10. Equity Optimization Issues-I
    The first equity optimization article is a beginning discussion of difficulties of traditional optimizers and the solutions NFA was starting to explore.
    Authors: Richard O. Michaud & Robert O. Michaud
    Publication: November 2004 Newsletter
  11. Optimization with Non-Normal Resampling
    In order to retain some of the normal distribution relevance for MC optimization, we use a multivariate distribution procedure that allows for exogenous specification of skewness and kurtosis.
    Author: Noah Kraut
    Publication: September 2004 Newsletter
  12. Liquidity and Portfolio Optimization password required
    Liquidity, within the context of defining an optimal portfolio of risky assets, may be viewed as a non-linear return penalty factor that depends on the level of investment and asset size or float.
    Authors: Richard O. Michaud & Robert O. Michaud
    Publication: Second Quarter 2003 Newsletter
  13. Optimal and Investable Portfolios
    Optimal portfolios typically include inconvenient and insignificant asset weights, make for impractical investment. This article introduces some of New Frontier's compute-efficient solutions for finding an investable portfolio from the optimal portfolio.
    Authors: Richard O. Michaud & Robert O. Michaud
    Publication: June 2003 Newsletter
  14. New View of Mean Variance
    This article discusses five methods other than mean variance optimization for defining portfolio optimality: non-variance risk measures, utility function optimization, multi-period objectives, Monte Carlo financial planning, or linear programming.
    Author: Richard O. Michaud
    Publication: Financial Planning Magazine. November 1, 1998
  15. The Markowitz Optimization Enigma: Is Optimized Optimal?
    The major problem with mean variance optimization is its tendency to maximize the effects of errors in the input assumptions.  Unconstrained mean variance optimization can yield results that are inferior to those of simple equal-weighting schemes. Author: Richard O. Michaud
    Publication: Financial Analysts Journal. January/February 1989