Advances in Portfolio Construction and Implementation

Advances in Portfolio Construction and Implementation

If the Journal of Finance devoted an entire issue to research papers on portfolio construction, the result might be similar to this book. Satchell and Scowcroft have prepared an edited collection of cutting-edge papers, but the audience is narrow.

The general theme is extensions or alternatives to traditional mean-variance optimization. Do corporations and individual investors have different utility functions? Should we optimize with regard to higher moments: skewness and kurtosis? Should optimization be based on investors' absolute or relative expectations? Can we optimize based on rank orderings as opposed to expected returns?

Articles tend to be dry, serious, and quite technical. There are plenty of citations to the literature. If you are a researcher in portfolio theory, you will find much original thinking to digest. If you are a practitioner, this book will put you to sleep.

Contents

1. A review of portfolio planning: models and systems

2. Generalised mean variance analysis and robust portfolio diversification

3. Portfolio construction from mandate to stock weight: a practitioner’s perspective

4. Enhanced indexation

5. Portfolio management under taxes

6. Using genetic algorithms to construct portfolios

7. Near-uniformly distributed, stochastically generated portfolios

8. Modelling directional hedge funds mean, variance and correlation with tracker funds

9. Integrating market and credit risk in fixed income portfolios

10. Incorporating skewness and kurtosis in portfolio optimization: a multidimensional efficient set

11. Balancing growth and shortfall probability in continuous time active portfolio management

12. Assessing the merits of risk-based optimisation for portfolio concentration

13. The mean-downside risk portfolio frontier: a non-parametric approach

14. Some exact results for portfolio estimators in the two-period capital market model

15. optimal asset allocation for endowments: a large deviations approach

16. Methods of relative portfolio optimization

17. Predicting portfolio returns using exact efficient set distributors


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