An authoritative resource for the wealth management industry that bridges the gap between modern perspectives on asset allocation and practical implementation

An advanced yet practical dive into the world of asset allocation, Modern Asset Allocation for Wealth Management provides the knowledge financial advisors and their robo-advisor counterparts need to reclaim ownership of the asset allocation component of their fiduciary responsibility. Wealth management practitioners are commonly taught the traditional mean-variance approach in CFA and similar curricula, a method with increasingly limited applicability given the evolution of investment products and our understanding of real-world client preferences. Additionally, financial advisors and researchers typically receive little to no training on how to implement a robust asset allocation framework, a conceptually simple yet practically very challenging task. This timely book offers professional wealth managers and researchers an up-to-date and implementable toolset for managing client portfolios. 

The information presented in this book far exceeds the basic models and heuristics most commonly used today, presenting advances in asset allocation that have been isolated to academic and institutional portfolio management settings until now, while simultaneously providing a clear framework that advisors can immediately deploy. This rigorous manuscript covers all aspects of creating client portfolios: setting client risk preferences, deciding which assets to include in the portfolio mix, forecasting future asset performance, and running an optimization to set a final allocation. An important resource for all wealth management fiduciaries, this book enables readers to:

• Implement a rigorous yet streamlined asset allocation framework that they can stand behind with conviction
• Deploy both neo-classical and behavioral elements of client preferences to more accurately establish a client risk profile
• Incorporate client financial goals into the asset allocation process systematically and precisely with a simple balance sheet model
• Create a systematic framework for justifying which assets should be included in client portfolios
• Build capital market assumptions from historical data via a statistically sound and intuitive process
• Run optimization methods that respect complex client preferences and real-world asset characteristics

Modern Asset Allocation for Wealth Management is ideal for practicing financial advisors and researchers in both traditional and robo-advisor settings, as well as advanced undergraduate and graduate courses on asset allocation.

DAVID M. BERNS, PHD, is the Chief Investment Officer and cofounder of Simplify ETFs where he leads the development of novel investment strategies that help advisors produce better outcomes for their clients. David began his finance career at a $5 billion multi-family office where he developed cutting-edge asset allocation, portfolio management, and risk management systems for managing private and institutional wealth across both liquid and illiquid asset classes. David then pivoted to developing short- and intermediate-term investment strategies that, once layered on top of a client's long-term strategic asset allocation, improve both return and risk metrics. David is also the founder and inventor of Portfolio Designer, a cloud-based asset allocation platform empowering advisors to reclaim the asset allocation component of their fiduciary responsibility.

David has a PhD in Physics from the Massachusetts Institute of Technology in the field of Quantum Computation and currently lives in New York City with his wife Carolee and son Henry.

Preface vii

Acknowledgments xiii

Chapter 1 Preliminaries 1

Expected Utility 2

Introduction 2

MPT is an Approximation 5

Higher Moment Motivation 8

Modernized Preference Motivation 13

A Modern Utility Function 15

Returns-Based EU Maximization 21

Estimation Error 23

Introduction 23

Minimizing Estimation Error 24

Reducing Sensitivity to Estimation Error 28

A Modern Definition of Asset Allocation 30

Chapter 2 The Client Risk Profile 33

Introduction 33

Measuring Preferences 34

Risk Aversion 34

Loss Aversion 39

Reflection 41

Lottery Question Sizing 43

Incorporating Goals 43

Preference Moderation via SLR 43

Discretionary Wealth 48

Comparison with Monte Carlo 51

Comparison with Glidepaths 52

Chapter 3 Asset Selection 55

Introduction 55

Moment Contributions 57

Overview 57

Calculation 59

Utility Contribution 62

Mimicking Portfolios 63

A New Asset Class Paradigm 66

Overview 66

A Review of Risk Premia 67

From Assets to Asset Classes 73

Chapter 4 Capital Market Assumptions 79

Introduction 79

Using History as Our Forecast 81

Background 81

Estimation Error and Sample Size 83

Stationarity: Does History Repeat? 89

Adjusting Forecasts 91

Pre-Tax Adjustments 91

Post-Tax Adjustments 93

Chapter 5 Portfolio Optimization 97

Introduction 97

Optimization Results 98

To MPT or Not to MPT? 103

Asset Allocation Sensitivity 105

Final Remarks 109

Bibliography 111

Index 113