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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.
Much recent work has documented evidence for predictability of asset returns. We show how such predictability can affect the portfolio choices of long-lived investors who value wealth not for its own sake but for the consumption their wealth can support. We develop an approximate solution method for the optimal consumption and portfolio choice problem of an infinitely-lived investor with Epstein-Zin utility who faces a set of asset returns described by a vector autoregression in returns and state variables. Empirical estimates in long-run annual and postwar quarterly US data suggest that the predictability of stock returns greatly increases the optimal demand for stock. The role of nominal bonds in long-termport folios depends on the importance of real interest rate risk relative to other sources of risk. We extend the analysis to consider long-term inflation-indexed bonds and find that these bonds greatly increase the utility of conservative investors, who should hold large positions when they are available.
In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of classical Markowitz optimization and traditional objections. The authors demonstrate that in practice the single most important limitation of MV optimization is oversensitivity to estimation error. Portfolio optimization requires a modern statistical perspective. Efficient Asset Management, Second Edition uses Monte Carlo resampling to address information uncertainty and define Resampled Efficiency (RE) technology. RE optimized portfolios represent a new definition of portfolio optimality that is more investment intuitive, robust, and provably investment effective. RE rebalancing provides the first rigorous portfolio trading, monitoring, and asset importance rules, avoiding widespread ad hoc methods in current practice. The Second Edition resolves several open issues and misunderstandings that have emerged since the original edition. The new edition includes new proofs of effectiveness, substantial revisions of statistical estimation, extensive discussion of long-short optimization, and new tools for dealing with estimation error in applications and enhancing computational efficiency. RE optimization is shown to be a Bayesian-based generalization and enhancement of Markowitz's solution. RE technology corrects many current practices that may adversely impact the investment value of trillions of dollars under current asset management. RE optimization technology may also be useful in other financial optimizations and more generally in multivariate estimation contexts of information uncertainty with Bayesian linear constraints. Michaud and Michaud's new book includes numerous additional proposals to enhance investment value including Stein and Bayesian methods for improved input estimation, the use of portfolio priors, and an economic perspective for asset-liability optimization. Applications include investment policy, asset allocation, and equity portfolio optimization. A simple global asset allocation problem illustrates portfolio optimization techniques. A final chapter includes practical advice for avoiding simple portfolio design errors. With its important implications for investment practice, Efficient Asset Management 's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud and Michaud update the practice of optimization for modern investment management.
Handbook of the Economics of Population Aging, Volume 1B provides the economic literature on aging and associated subjects, presenting comprehensive portraits of both social and theoretical issues. As the second of two volumes in this series on the economics of population aging, it continues the discussion, delving deeper into topics such as the labor market and human resource issues, gerontology, history, and the sociological and political ramifications of this fascinating topic whose inception dates back to the late 1970's. This volume includes literature that has appeared in general economics journals, in various field journals in economics, especially, but not exclusively, those covering labor market and human resource issues, information from interdisciplinary social science and life science journals, and data presented in papers by economists published in journals associated with gerontology, history, sociology, political science, and demography, amongst others. - Presents comprehensive portraits of social and theoretical issues that can be used by both policymakers and scholars - Readers receive diverse perspectives on subjects that can be closely associated with national and regional concerns - Chapters offer comprehensive, critical reviews and expositions on the essential aspects of the economics of population aging
This handbook draws on research from a range of academic disciplines to reflect on the implications for provisions of pension and retirement income of demographic ageing. it reviews the latest research, policy related tools, analytical methods and techniques and major theoretical frameworks.
Portfolio risk forecasting has been and continues to be an active research field for both academics and practitioners. Almost all institutional investment management firms use quantitative models for their portfolio forecasting, and researchers have explored models' econometric foundations, relative performance, and implications for capital market behavior and asset pricing equilibrium. Portfolio Risk Analysis provides an insightful and thorough overview of financial risk modeling, with an emphasis on practical applications, empirical reality, and historical perspective. Beginning with mean-variance analysis and the capital asset pricing model, the authors give a comprehensive and detailed account of factor models, which are the key to successful risk analysis in every economic climate. Topics range from the relative merits of fundamental, statistical, and macroeconomic models, to GARCH and other time series models, to the properties of the VIX volatility index. The book covers both mainstream and alternative asset classes, and includes in-depth treatments of model integration and evaluation. Credit and liquidity risk and the uncertainty of extreme events are examined in an intuitive and rigorous way. An extensive literature review accompanies each topic. The authors complement basic modeling techniques with references to applications, empirical studies, and advanced mathematical texts. This book is essential for financial practitioners, researchers, scholars, and students who want to understand the nature of financial markets or work toward improving them.
This paper investigates analytically and numerically intertemporal equilibrium portfolio policies under time dependent returns. The analysis is performed using a new method for obtaining approximate closed form solutions to the optimal portfolio-consumption problem that does not require the imposition of constraints on the conditional moments of consumption and that allows for autoregressive conditional heteroskedasticity in stock returns. The analytical and numerical results show that the elasticity of intertemporal substitution is irrelevant for the determination of the portfolio policy when returns are persistent and follow GARCH processes. In addition, results show that small departures from the i.i.d. assumption produce an important variability in the portfolio holdings that contrasts with the static CAPM constant portfolio policies. However, a conditional version of the static CAPM with the inclusion of a Jensen inequality correction is able to explain the overwhelming majority of the mean and almost all the variability of portfolio.
Innovative approaches to putting asset allocation into practice Building on more than 15 years of asset-allocation research, Paul D. Kaplan, who led the development of the methodologies behind the Morningstar Rating(TM) and the Morningstar Style Box(TM), tackles key challenges investor professionals face when putting asset-allocation theory into practice. This book addresses common issues such as: How should asset classes be defined? Should equities be divided into asset classes based on investment style, geography, or other factors? Should asset classes be represented by market-cap-weighted indexes or should other principles, such as fundamental weights, be used? How do actively managed funds fit into asset-class mixes? Kaplan also interviews industry luminaries who have greatly influenced the evolution of asset allocation, including Harry Markowitz, Roger Ibbotson, and the late Benoit Mandelbrot. Throughout the book, Kaplan explains allocation theory, creates new strategies, and corrects common misconceptions, offering original insights and analysis. He includes three appendices that put theory into action with technical details for new asset-allocation frameworks, including the next generation of portfolio construction tools, which Kaplan dubs "Markowitz 2.0."
Recent years have shown an increase in development and acceptance of quantitative methods for asset and liability management strategies. This book presents state of the art quantitative decision models for three sectors: pension funds, insurance companies and banks, taking into account new regulations and the industries risks.
'Risk-Based Supervision of Pension Funds' provides a review of the design and experience of risk-based pension fund supervision in countries that have been leaders in the development of these methods. The utilization of risk-based methods originates primarily in the supervision of banks. In recent years it has increasingly been extended to other types of financial intermediaries, including pension funds and insurers. The trend toward risk-based supervision of pensions reflects an increasing focus on risk management in both banking and insurance based on three key elements: capital requirements, supervisory review, and market discipline. Although similar in concept to the techniques developed in banking, its application to pension funds has required modifications, particularly for defined contribution funds that transfer investment risk to fund members. The countries examined–Australia, Denmark, Mexico, and the Netherlands–provide a range of experience that illustrates both the diversity of pension systems and the approaches to risk-based supervision, and also presents a commonality of focus on sound risk management and effective supervisory outcomes.