Portfolio Construction and Risk Budgeting

I could have used this book in my first (and only) job in investment management. I knew the basics of portfolio theory and lots of math, but whenever I went to the library to read the latest research, I was lost. The concepts, the notation and the terminology were all beyond my basic knowledge. I needed a “bridge” between basic portfolio theory and the cutting-edge of investment management research. With this book, Bernd Scherer offers such a bridge.

The opening chapter is an excellent overview of basic portfolio optimization. Its focus is on traditional approaches, but with a presentation that is mathematically sophisticated and entirely modern. Single-period mean-variance optimization is justified based upon assumptions of quadratic utility and joint-normal returns. Shortcomings of the methodology—due both to the assumptions and its focus on a single period—are discussed, setting the stage for the remainder of the book. Six subsequent chapters cover:

Models for deviations from joint-normality—including the use of lower-partial moments and models based upon mixed-normal distributions. The chapter also assesses the tendency of returns to become increasingly normal over longer horizons due to the central limit theorem.

Estimation error—By its very nature, portfolio optimization tends to maximize the impact of estimation error. This chapter focuses on resampling techniques for assessing that impact. These employ Monte Carlo analyses that integrate with regression analyses to improve portfolio optimization schemes.

Bayesian inference—introduces this increasingly important alternative to “classical” statistics. Bayesian methods are used widely in the academic literature, but have made only modest inroads into actual practice. This chapter does an excellent job of highlighting how they work.

Scenario optimization—entails scenario analysis (and, in a limiting case, Monte Carlo analysis) as a means of conducting sophisticated portfolio optimizations subject to user-specified utility constraints.

Optimizing relative to a benchmark—applies portfolio optimization techniques in a context where absolute risk is replaced by tracking error relative to a benchmark as a quantity of interest.

Allocating assets between multiple managers—applies optimization techniques to allocate assets between passively and actively managed portfolios, taking into account differing active management styles.

This is a tremendous amount of material, so the book is a broad overview. Topics are discussed briefly; examples are presented; the literature is cited; and it is on to the next topic. The book is truly a “bridge” to the vast literature on portfolio optimization. It will appeal to a large audience of practitioners because it is sophisticated without being too technical.

Contents

1. Traditional Portfolio Construction: Selected Issues - Starts with a review of Markowitz based solutions with a particular focus on issues that are of concern to practitioners but rarely treated in conventional textbooks. These involve asset liability management, clustering to redefine the investment universe, treatment of illiquid asset classes, life cycle investing, time varying covariances and implied return analysis.

2. Incorporating Deviations from Normality: Lower Partial Moments - Moves away from the classical model introducing non-normality. It will provide a toolkit to judge when non-normality is a problem and when it is not. Lower partial moment based portfolio construction is carefully discussed introducing all mathematical tools needed to optimally apply this important technique to real world portfolio problems.

3. Portfolio Resampling and Estimation Error - Introduces estimation error and how to heuristically deal with it using either portfolio resampling or constrained optimization. A particular focus is given to the concept of resampled efficiency recently introduced into the literature as an increasing number of investors get interested into this particular form of dealing with estimation error.

4. Bayesian Analysis and Portfolio Choice - Deals with estimation error from a more conventional angle reviewing various Bayesian techniques. A special focus is given on data problems, particularly on how to treat time series of different length as this is one of the main data problems faced by practitioners.

5. Scenario Optimization - This chapter is a natural extension of all four previous chapters. It will describe the most general form of portfolio optimization that can simultaneously deal with data problems (estimation error, time series of different length) as well as with non-linear instruments, non-normal distributions and non-standard preferences.

6. Portfolio Construction with Transaction Costs deals with the most overlooked problem in practical portfolio construction: transaction costs. It shows how various forms of transaction costs can be incorporated into the portfolio construction process.

7. Benchmark-Relative Optimization - Leaves the world of asset allocation and reviews key concepts in making benchmark relative decisions. Again focus is given to problems rarely handled in traditional textbooks such as implicit funding assumptions and risk decomposition, multiple benchmark optimization, tracking error and its forecasting ability or tracking error efficiency versus mean variance efficiency.

8. Core-Satellite Investing: Budgeting Active Manager Risk - Concludes on budgeting active manager risk providing the mathematical tools to address questions like "how much active?" "Where to be active?" or "Is core satellite investing superior to enhanced indexing?"

Who should read the book? First and foremost is consultants who serve institutional investors. Second is those same institutional investors—anyone who is involved in asset allocation or portfolio optimization decisions. The book will also appeal to professionals at investment management firms and researchers who are new to the field. [Review based on the first edition.]

For related books, see sections:

Risk Management - Market Risk

Portfolio Management - General

Portfolio Management - Asset Allocation

Finance - Portfolio Theory

 

 

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