1. |
Defense of Markowitz-Usmen
Dr. Michaud and Robert Michaud respond to Harvey et al.'s criticism of the simulation tests used by Markowit and Usmen.
Author: Robert Michaud and Richard Michaud.
Publication: NFA March 2008
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2. |
Robert's Hedgehog
This article presents a slightly whimsical proof of Resampled Efficiency.
Author: Robert Michaud and Richard Michaud.
Publication: June 2007 Newsletter. |
3. |
LETTERS TO THE EDITOR: "Reconstructing Harry"
Dr. Michaud responds to "Optimizing Harry Markowitz" a 2006 article in Institutional Investor.
Author: Richard O. Michaud.
Publication: Institutional Investor . August 2006. |
4. |
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. |
5. |
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. |
6. |
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. |
7. |
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. |
8. |
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.
Authors: Noah Kraut
Publication: September 2004 Newsletter.
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9. |
Forecast Confidence Level and Portfolio Optimization
This report focuses on the role and importance of the uncertainty in forecast information in constructing portfolios with the optimal performance.
Authors: Richard O. Michaud & Robert O. Michaud.
Publication: July 2004 Newsletter.
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10. |
Why Mean-Variance Optimization Isn't Useful for Investment Management
The logic of mean variance optimization is seductive, but the seduction unravels in the investment period.
Author: Richard O. Michaud.
Publication: January 2004 Newsletter.
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11. |
Are Good Inputs Enough? No.
Investment institutions tend to focus the bulk of their human and capital resources on developing reliable forecasts of asset risks and return while ignoring the optimization technology they use to transform their information into investors’ portfolios. These good inputs are no better than bad if the portfolios that represent the information to the investor have no investment value.
Authors: Richard O. Michaud & Robert O. Michaud.
Publication: October 2003 Newsletter. |
12. |
LETTERS TO THE EDITOR: Portfolio Resampling: Review and Critique
The authors responded immediately to Bernd Scherer’s critique of Resampled Efficient Optimization.
Authors: Richard O. Michaud & Robert O. Michaud.
Publication: Financial Analysts Journal. May/June 2003.
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13. |
LETTERS TO THE EDITOR: 'An Examination of Resampled Portfolio Efficiency': A Comment
Dr. Michaud responds to the Fletcher & Hillier article (2001) that compared the performance of mean variance efficient asset allocations to resampled efficient asset allocations by means of a back test.
Author: Richard O. Michaud.
Publication: Financial Analysts Journal. January/February 2003. |
14. |
Resampled Portfolio Rebalancing and Monitoring
An enhancement to the original rebalancing procedure is now available that dramatically increases the uniformity and discrimination power of the original portfolio rebalancing and asset weight range procedures.
Author: Richard O. Michaud.
Publication: Fourth Quarter 2002 Newsletter. |
15. |
An Introduction to Resampled Efficiency
Resampled Efficiency provides the solution to using uncertain information in portfolio optimization.
Author: Richard O. Michaud.
Publication: Third Quarter 2002 Newsletter. |
16. |
A Better Way to Use Information
In the second resampled efficiency article in the European Pension News, Richard Michaud argues for the importance of taking statistical errors into account in asset allocation decisions.
Author: Richard O. Michaud.
Publication: European Pensions & Investment News. July 9, 2001.
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17. |
Out-of-Sample Tests of Resampled Efficiency
Resampled Efficient Optimization improves the average reward-to-risk ratio of classical asset allocation portfolios.
Author: Richard O. Michaud.
Publication: European Pensions & Investment News. June 25, 2001. |
18. |
Aspects: Resampled Efficient Asset Allocation
This article introduces the advantages and functionality of the newly patented Resampled Efficiency.
Author: Richard O. Michaud.
Publication: Frontier News. Second Quarter 2001. |
19. |
A New Design for Portfolios
Given all the problems associated with the inferior investment technology currently being used, it is little wonder that capital markets appear to be efficient. Only when asset management practice has achieved a level of sophistication consistent with the thoughtful use of investment information is it likely to provide statistically significant risk-adjusted performance.
Author: Richard O. Michaud.
Publication: Bloomberg Personal Finance. July/August 2000. |
