This timely volume addresses three important recent trends in the internationalization of United States equity markets: extensive market integration through foreign investment and links among stock prices around the world; increasing securitization as countries such as Japan come to rely more than ever before on markets in equities and bonds at the expense of banks; and the opening of national financial systems of newly industrializing countries to international financial flows and institutions, as governments remove capital controls and other barriers. Eight essays examine such issues as the current extent of international market integration, gains to U.S. investors through international diversification, home-country bias in investing, the role of time and location around the world in stock trading, and the behavior of country funds. Other, long-standing questions about equity markets are also addressed, including market efficiency and the accuracy of models of expected returns, with a particular focus on variances, covariances, and the price of risk according to the Capital Asset Pricing Model.
This paper studies the cross-border transactions in equity by investors in Canada, Germany, Japan, the U.K. and the U.S. We find that investors from different countries make very different decisions about the allocation of their portfolio across markets. In contradiction to the notion that high variable transactions costs hinder international diversification, we find that the volume of gross equity flows vastly exceeds net equity flows and the turnover rate on foreign equity investments by some investors even exceeds domestic turnover rates. We also reject the hypothesis that U.S. investors follow the standard CAPM in allocating their global equity portfolio.
Recent changes in technology, along with the opening up of many regions previously closed to investment, have led to explosive growth in the international movement of capital. Flows from foreign direct investment and debt and equity financing can bring countries substantial gains by augmenting local savings and by improving technology and incentives. Investing companies acquire market access, lower cost inputs, and opportunities for profitable introductions of production methods in the countries where they invest. But, as was underscored recently by the economic and financial crises in several Asian countries, capital flows can also bring risks. Although there is no simple explanation of the currency crisis in Asia, it is clear that fixed exchange rates and chronic deficits increased the likelihood of a breakdown. Similarly, during the 1970s, the United States and other industrial countries loaned OPEC surpluses to borrowers in Latin America. But when the U.S. Federal Reserve raised interest rates to control soaring inflation, the result was a widespread debt moratorium in Latin America as many countries throughout the region struggled to pay the high interest on their foreign loans. International Capital Flows contains recent work by eminent scholars and practitioners on the experience of capital flows to Latin America, Asia, and eastern Europe. These papers discuss the role of banks, equity markets, and foreign direct investment in international capital flows, and the risks that investors and others face with these transactions. By focusing on capital flows' productivity and determinants, and the policy issues they raise, this collection is a valuable resource for economists, policymakers, and financial market participants.
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.
"Nobel Prize-winning financial economist William Sharpe shows that investment professionals cannot make good portfolio choices unless they understand the determinants of asset prices." -- Provided by publisher.
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.
Choose statistically significant stock selection models using SAS® Portfolio and Investment Analysis with SAS®: Financial Modeling Techniques for Optimization is an introduction to using SAS to choose statistically significant stock selection models, create mean-variance efficient portfolios, and aggressively invest to maximize the geometric mean. Based on the pioneering portfolio selection techniques of Harry Markowitz and others, this book shows that maximizing the geometric mean maximizes the utility of final wealth. The authors draw on decades of experience as teachers and practitioners of financial modeling to bridge the gap between theory and application. Using real-world data, the book illustrates the concept of risk-return analysis and explains why intelligent investors prefer stocks over bonds. The authors first explain how to build expected return models based on expected earnings data, valuation ratios, and past stock price performance using PROC ROBUSTREG. They then show how to construct and manage portfolios by combining the expected return and risk models. Finally, readers learn how to perform hypothesis testing using Bayesian methods to add confidence when data mining from large financial databases.
The primary purpose in this book is to present an integrated and innovative methodological approach for the construction and selection of equity portfolios. The approach takes into account the inherent multidimensional nature of the problem, while allowing the decision makers to incorporate specified preferences in the decision processes. A fundamental principle of modern portfolio theory is that comparisons between portfolios are generally made using two criteria; the expected return and portfolio variance. According to most of the portfolio models derived from the stochastic dominance approach, the group of portfolios open to comparisons is divided into two parts: the efficient portfolios, and the dominated. This work integrates the two approaches providing a unified model for decision making in portfolio management with multiple criteria.
