Today’s modern portfolio theory is not your father’s MPT. It has undergone many changes in the past fifty years. Indeed, a new understanding of MPT has emerged, one that has a significant impact on managing asset allocation—especially in today’s turbulent markets. Dynamic Asset Allocation interprets and integrates the developments in modern portfolio theory: from the efficient-market hypothesis and indexing of decades past to strategies for building winning portfolios today. The book is filled with practical, hands-on advice for investors, including guidance on approaching investment as a risk-management task.
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.
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.
This monograph collects in one place the basic definitions, a careful description of the model, and discussion of how convex optimization can be used in multi-period trading, all in a common notation and framework.
The paper developes a VAR macrofinance model of the Czech economy. It shows that yield misalignments from the yields implied by the macrofinance model partially determine subsequent yield changes over three to nine months. These yield misalignments tend to persist for a number of months. This persistence of the misalignments was explained by (a) the fact that the macro-economy influences asset markets only at lower frequencies, (b) the liquidity effect particularly during the times of capital inflows to Czech Republic, and (c) the fact that not all misalignments were greater than their historical one standard deviation.
This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management. The chapters introduce the reader to some of the latest research developments in the area of equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution and transaction costs modeling. This volume will be of great help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.
"Written by two renowned experts in the field, the books under review contain a thorough and insightful treatment of the fundamental underpinnings of various aspects of stochastic processes as well as a wide range of applications. Providing clear exposition, deep mathematical results, and superb technical representation, they are masterpieces of the subject of stochastic analysis and nonlinear filtering....These books...will become classics." --SIAM REVIEW
Asset allocation has long been viewed as a safe bet for reducing risk in a portfolio. Asset allocators strive to buy when prices are low and sell when prices rise. Tactical asset allocation (TAA) practitioners tend to emphasize shorter-term adjustments, reducing exposure when recent market performance has been good, and increasing exposure in a slipping market (in contrast to dynamic asset allocation, or portfolio insurance). As interest in this technique continues to grow, J.P. Morgan's Wai Lee provides comprehensive coverage of the analytical tools needed to successfully implement and monitor tactical asset allocation.
