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Efficient Asset Management

Efficient Asset Management PDF Author: Richard O. Michaud
Publisher: Oxford University Press
ISBN: 0199887195
Category : Business & Economics
Languages : en
Pages : 144

Book Description
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.

Efficient Asset Management

Efficient Asset Management PDF Author: Richard O. Michaud
Publisher: Oxford University Press
ISBN: 0199887195
Category : Business & Economics
Languages : en
Pages : 144

Book Description
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.

Artificial Intelligence in Asset Management

Artificial Intelligence in Asset Management PDF Author: Söhnke M. Bartram
Publisher: CFA Institute Research Foundation
ISBN: 195292703X
Category : Business & Economics
Languages : en
Pages : 95

Book Description
Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

Fundamentals Of Institutional Asset Management

Fundamentals Of Institutional Asset Management PDF Author: Frank J Fabozzi
Publisher: World Scientific
ISBN: 981122160X
Category : Business & Economics
Languages : en
Pages : 616

Book Description
This book provides the fundamentals of asset management. It takes a practical perspective in describing asset management. Besides the theoretical aspects of investment management, it provides in-depth insights into the actual implementation issues associated with investment strategies. The 19 chapters combine theory and practice based on the experience of the authors in the asset management industry. The book starts off with describing the key activities involved in asset management and the various forms of risk in managing a portfolio. There is then coverage of the different asset classes (common stock, bonds, and alternative assets), collective investment vehicles, financial derivatives, common stock analysis and valuation, bond analytics, equity beta strategies (including smart beta), equity alpha strategies (including quantitative/systematic strategies), bond indexing and active bond portfolio strategies, and multi-asset strategies. The methods of using financial derivatives (equity derivatives, interest rate derivatives, and credit derivatives) in managing the risks of a portfolio are clearly explained and illustrated.

Asset Management Excellence

Asset Management Excellence PDF Author: John D. Campbell
Publisher: CRC Press
ISBN: 9780849303241
Category : Technology & Engineering
Languages : en
Pages : 496

Book Description
During the eight years since the publication of Maintenance Excellence: Optimizing Equipment Life-Cycle Decisions the business environment has changed drastically. Globalization, consolidation, and changes in technology challenge asset management and maintenance professionals to be more efficient. Globalization and consolidation have been particularly instrumental in the changes in maintenance standards, approaches, and the use of technology to become more efficient and cost effective. Reflecting all this and more, the second edition has been renamed: Asset Management Excellence: Optimizing Equipment Life-Cycle Decisions. New in the Second Edition: Two new chapters on Maintenance Management Fundamentals Coverage of leadership issues, the implementation of new processes, and change management Discussion of the design stage and key factors for successful implementation Understanding the dynamic influences and optimization of spares management Updated case studies Introduction to new software packages that optimize a variety of maintenance and replacement decisions Although there have been patterns and trends that have emerged around the world in asset management, the root principles are the same—personnel with tools go out to address the needs of maintaining assets. However, many of the tools, technologies, and thought processes have evolved and matured to allow a rethinking of the deeper maintenance processes. For this edition, a new set of authors and contributors have revisited the content, updated information, and added new content based on the passage of time, changes in thinking, and the introduction and improvement in technologies.

Asset Management

Asset Management PDF Author: Andrew Ang
Publisher: Financial Management Associati
ISBN: 0199959323
Category : Business & Economics
Languages : en
Pages : 717

Book Description
Stocks and bonds? Real estate? Hedge funds? Private equity? If you think those are the things to focus on in building an investment portfolio, Andrew Ang has accumulated a body of research that will prove otherwise. In this book, Ang upends the conventional wisdom about asset allocation by showing that what matters aren't asset class labels but the bundles of overlapping risks they represent.

The Road to AUM

The Road to AUM PDF Author: Sandra Powers Murphy
Publisher:
ISBN: 9780999720417
Category : Business & Economics
Languages : en
Pages : 356

Book Description
The Road to AUM provides investment managers and business owners, marketing and sales professionals with a roadmap to institutional asset growth based on observations and comments directly from the institutions themselves. Whether a firm is launching, emerging, stuck in neutral, or moving in a new direction, a view of the road ahead is paramount.

Portfolio Management

Portfolio Management PDF Author: Scott D. Stewart
Publisher: John Wiley & Sons
ISBN: 111939743X
Category : Business & Economics
Languages : en
Pages : 785

Book Description
A career’s worth of portfolio management knowledge in one thorough, efficient guide Portfolio Management is an authoritative guide for those who wish to manage money professionally. This invaluable resource presents effective portfolio management practices supported by their underlying theory, providing the tools and instruction required to meet investor objectives and deliver superior performance. Highlighting a practitioner’s view of portfolio management, this guide offers real-world perspective on investment processes, portfolio decision making, and the business of managing money for real clients. Real world examples and detailed test cases—supported by sophisticated Excel templates and true client situations—illustrate real investment scenarios and provide insight into the factors separating success from failure. The book is an ideal textbook for courses in advanced investments, portfolio management or applied capital markets finance. It is also a useful tool for practitioners who seek hands-on learning of advanced portfolio techniques. Managing other people’s money is a challenging and ever-evolving business. Investment professionals must keep pace with the current market environment to effectively manage their client’s assets while students require a foundation built on the most relevant, up-to-date information and techniques. This invaluable resource allows readers to: Learn and apply advanced multi-period portfolio methods to all major asset classes. Design, test, and implement investment processes. Win and keep client mandates. Grasp the theoretical foundations of major investment tools Teaching and learning aids include: Easy-to-use Excel templates with immediately accessible tools. Accessible PowerPoint slides, sample exam and quiz questions and sample syllabi Video lectures Proliferation of mathematics in economics, growing sophistication of investors, and rising competition in the industry requires advanced training of investment professionals. Portfolio Management provides expert guidance to this increasingly complex field, covering the important advancements in theory and intricacies of practice.

Modern Investment Management

Modern Investment Management PDF Author: Bob Litterman
Publisher: John Wiley & Sons
ISBN: 0471480657
Category : Business & Economics
Languages : de
Pages : 648

Book Description
Dieser Band füllt eine echte Marktlücke. "Goldman Sach's Modern Investment" gibt eine Einführung in moderne Investment Management Verfahren, wie sie von Goldman Sachs Asset Management verwendet werden, um erstklassige Investitionsrenditen zu erzielen. Erläutert werden u.a. die moderne Portfoliotheorie (Portfoliodiversifikation zur Risikostreuung), Capital Asset Pricing (Verfahren zur Ermittlung des Risiko-Rendite-Austauschverhältnisses von Finanzanlagen, bei dem der unterschiedliche Risikogehalt von Finanztiteln berücksichtigt wird) sowie eine Reihe aktueller Themen wie z.B. strategische Portfoliostrukturierung, Risikobudgetierung und aktives Portfolio Management. Hier erhalten Sie die Mittel an die Hand, um die Goldman Sachs Asset Management Methode für sich selbst umzusetzen. Das von Fischer Black und Bob Litterman gemeinsam entwickelte Black-Litterman Asset Allocation Model gehört zu den angesehensten und meist verwendeten Modellen zur Portfoliostrukturierung. Litterman und seine Asset Management Group sind oft die treibende Kraft, wenn es um Portfoliostrukturierung und Investmententscheidungen der 100 international größten Pensionsfonds geht.

Asset Management and Institutional Investors

Asset Management and Institutional Investors PDF Author: Ignazio Basile
Publisher: Springer
ISBN: 3319327968
Category : Business & Economics
Languages : en
Pages : 468

Book Description
This book analyses investment management policies for institutional investors. It is composed of four parts. The first one analyses the various types of institutional investors, institutions which, with different objectives, professionally manage portfolios of financial and real assets on behalf of a wide variety of individuals. This part goes on with an in-depth analysis of the economic, technical and regulatory characteristics of the different types of investment funds and of other types of asset management products, which have a high rate of substitutability with investment funds and represent their natural competitors. The second part of the book identifies and investigates the stages of the investment portfolio management. Given the importance of strategic asset allocation in explaining the ex post performance of any type of investment portfolio, this part provides an in-depth analysis of asset allocation methods, illustrating the different theoretical and operational solutions available to institutional investors. The third part describes performance assessment, its breakdown and risk control, with an in-depth examination of performance evaluation techniques, returns-based style analysis approaches, and performance attribution models. Finally, the fourth part deals with the subject of diversification into alternative asset classes, identifying the common characteristics and their possible role within the framework of investment management policies. This part analyses hedge funds, private equity, real estate, commodities, and currency overlay techniques.

Machine Learning for Asset Managers

Machine Learning for Asset Managers PDF Author: Marcos M. López de Prado
Publisher: Cambridge University Press
ISBN: 1108879721
Category : Business & Economics
Languages : en
Pages : 152

Book Description
Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to "learn" complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specification search, robust to multicollinearity and other substitution effects.