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.
Table des matières
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
A propos de l’auteur
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 Ph D 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.
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