Build an agile, responsive portfolio with a new approach to global asset allocation Adaptive Asset Allocation is a no-nonsense how-to guide for dynamic portfolio management. Written by the team behind Gestaltu.com, this book walks you through a uniquely objective and unbiased investment philosophy and provides clear guidelines for execution. From foundational concepts and timing to forecasting and portfolio optimization, this book shares insightful perspective on portfolio adaptation that can improve any investment strategy. Accessible explanations of both classical and contemporary research support the methodologies presented, bolstered by the authors' own capstone case study showing the direct impact of this approach on the individual investor. Financial advisors are competing in an increasingly commoditized environment, with the added burden of two substantial bear markets in the last 15 years. This book presents a framework that addresses the major challenges both advisors and investors face, emphasizing the importance of an agile, globally-diversified portfolio. Drill down to the most important concepts in wealth management Optimize portfolio performance with careful timing of savings and withdrawals Forecast returns 80% more accurately than assuming long-term averages Adopt an investment framework for stability, growth, and maximum income An optimized portfolio must be structured in a way that allows quick response to changes in asset class risks and relationships, and the flexibility to continually adapt to market changes. To execute such an ambitious strategy, it is essential to have a strong grasp of foundational wealth management concepts, a reliable system of forecasting, and a clear understanding of the merits of individual investment methods. Adaptive Asset Allocation provides critical background information alongside a streamlined framework for improving portfolio performance.

Build an agile, responsive portfolio with a new approach to global asset allocation Adaptive Asset Allocation is a no-nonsense how-to guide for dynamic portfolio management. Written by the team behind Gestaltu.com, this book walks you through a uniquely objective and unbiased investment philosophy and provides clear guidelines for execution. From foundational concepts and timing to forecasting and portfolio optimization, this book shares insightful perspective on portfolio adaptation that can improve any investment strategy. Accessible explanations of both classical and contemporary research support the methodologies presented, bolstered by the authors' own capstone case study showing the direct impact of this approach on the individual investor. Financial advisors are competing in an increasingly commoditized environment, with the added burden of two substantial bear markets in the last 15 years. This book presents a framework that addresses the major challenges both advisors and investors face, emphasizing the importance of an agile, globally-diversified portfolio. Drill down to the most important concepts in wealth management Optimize portfolio performance with careful timing of savings and withdrawals Forecast returns 80% more accurately than assuming long-term averages Adopt an investment framework for stability, growth, and maximum income An optimized portfolio must be structured in a way that allows quick response to changes in asset class risks and relationships, and the flexibility to continually adapt to market changes. To execute such an ambitious strategy, it is essential to have a strong grasp of foundational wealth management concepts, a reliable system of forecasting, and a clear understanding of the merits of individual investment methods. Adaptive Asset Allocation provides critical background information alongside a streamlined framework for improving portfolio performance.

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.

A new, evolutionary explanation of markets and investor behavior Half of all Americans have money in the stock market, yet economists can’t agree on whether investors and markets are rational and efficient, as modern financial theory assumes, or irrational and inefficient, as behavioral economists believe. The debate is one of the biggest in economics, and the value or futility of investment management and financial regulation hangs on the answer. In this groundbreaking book, Andrew Lo transforms the debate with a powerful new framework in which rationality and irrationality coexist—the Adaptive Markets Hypothesis. Drawing on psychology, evolutionary biology, neuroscience, artificial intelligence, and other fields, Adaptive Markets shows that the theory of market efficiency is incomplete. When markets are unstable, investors react instinctively, creating inefficiencies for others to exploit. Lo’s new paradigm explains how financial evolution shapes behavior and markets at the speed of thought—a fact revealed by swings between stability and crisis, profit and loss, and innovation and regulation. An ambitious new answer to fundamental questions about economics and investing, Adaptive Markets is essential reading for anyone who wants to understand how markets really work.

Publisher Description

Portfolio Design – choosing the right mix of assets appropriate to a particular investor – is the key to successful investing. It can help you accumulate wealth over time, while cushioning the blow of possible economic downturns. But in order to successfully achieve this goal, you need to be familiar with all of the major asset classes that go into modern portfolios and learn how much they add to portfolio diversification. Thoughtful asset allocation provides discipline to the investment process and gives you the best chance of building and safeguarding wealth. Wharton Professor Richard C. Marston, 2014 recipient of the Investment Management Consultants Association’s prestigious Matthew R. McArthur Award, will guide you through the major decisions that need to be made when designing a portfolio and will put you in the best position to balance the risk-reward relationship that is part of this endeavor. Portfolio Design is to be read by investment advisors. The book is rich in information about individual asset classes, including both traditional assets like stocks and bonds as well as alternative assets such as hedge funds, private equity, real estate, and commodities. So it should appeal to all sophisticated advisors whether or not they are trying to qualify for one of the major investment designations. In fact, the book is designed to be read by any advisor who is as fascinated as Marston by the investment process.

Academic finance has had a remarkable impact on many financial services. Yet long-term investors have received curiously little guidance from academic financial economists. Mean-variance analysis, developed almost fifty years ago, has provided a basic paradigm for portfolio choice. This approach usefully emphasizes the ability of diversification to reduce risk, but it ignores several critically important factors. Most notably, the analysis is static; it assumes that investors care only about risks to wealth one period ahead. However, many investors—-both individuals and institutions such as charitable foundations or universities—-seek to finance a stream of consumption over a long lifetime. In addition, mean-variance analysis treats financial wealth in isolation from income. Long-term investors typically receive a stream of income and use it, along with financial wealth, to support their consumption. At the theoretical level, it is well understood that the solution to a long-term portfolio choice problem can be very different from the solution to a short-term problem. Long-term investors care about intertemporal shocks to investment opportunities and labor income as well as shocks to wealth itself, and they may use financial assets to hedge their intertemporal risks. This should be important in practice because there is a great deal of empirical evidence that investment opportunities—-both interest rates and risk premia on bonds and stocks—-vary through time. Yet this insight has had little influence on investment practice because it is hard to solve for optimal portfolios in intertemporal models. This book seeks to develop the intertemporal approach into an empirical paradigm that can compete with the standard mean-variance analysis. The book shows that long-term inflation-indexed bonds are the riskless asset for long-term investors, it explains the conditions under which stocks are safer assets for long-term than for short-term investors, and it shows how labor income influences portfolio choice. These results shed new light on the rules of thumb used by financial planners. The book explains recent advances in both analytical and numerical methods, and shows how they can be used to understand the portfolio choice problems of long-term investors.

Rational Expectations is a clean sheet of paper in the wonky world of quantitatively based asset allocation aimed at small investors. Continuing the theme of the Investing for Adults series, this full-length finance title is not for beginners, but rather assumes a fair degree of quantitative ability and finance knowledge. If you think you can time the market or pick stocks and mutual fund managers, or even if you think that you can formulate an optimally efficient mean-variance asset allocation with a black box, then learn some basic finance and come back in a few years. On the other hand, if you know your way around risk premiums and standard deviations and know who Irving Fisher and Benjamin Graham were, and if you want to sharpen your asset class skills, you've come to the right place.

Discover a masterful exploration of the fallacies and challenges of asset allocation In Asset Allocation: From Theory to Practice and Beyond—the newly and substantially revised Second Edition of A Practitioner’s Guide to Asset Allocation—accomplished finance professionals William Kinlaw, Mark P. Kritzman, and David Turkington deliver a robust and insightful exploration of the core tenets of asset allocation. Drawing on their experience working with hundreds of the world’s largest and most sophisticated investors, the authors review foundational concepts, debunk fallacies, and address cutting-edge themes like factor investing and scenario analysis. The new edition also includes references to related topics at the end of each chapter and a summary of key takeaways to help readers rapidly locate material of interest. The book also incorporates discussions of: The characteristics that define an asset class, including stability, investability, and similarity The fundamentals of asset allocation, including definitions of expected return, portfolio risk, and diversification Advanced topics like factor investing, asymmetric diversification, fat tails, long-term investing, and enhanced scenario analysis as well as tools to address challenges such as liquidity, rebalancing, constraints, and within-horizon risk. Perfect for client-facing practitioners as well as scholars who seek to understand practical techniques, Asset Allocation: From Theory to Practice and Beyond is a must-read resource from an author team of distinguished finance experts and a forward by Nobel prize winner Harry Markowitz.

With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment. The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that: Introduce OLPS and formulate OLPS as a sequential decision task Present key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learning Detail four innovative OLPS algorithms based on cutting-edge machine learning techniques Provide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the art Investigate possible future directions Complete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment. Readers are encouraged to visit the authors’ website for updates: http://olps.stevenhoi.org.