Modern Asset Allocation for Wealth Management

David M. Berns 지음

Wiley 2020년 04월 09일 출간

작품소개

책소개

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 establis

목차

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

작가정보

저자(글) David M. Berns

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.