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Author: M. Rasmussen
Publisher: Springer
ISBN: 0230512852
Category : Business & Economics
Languages : en
Pages : 453
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Book Description
Targeted towards institutional asset managers in general and chief investment officers, portfolio managers and risk managers in particular, this practical book serves as a comprehensive guide to quantitative portfolio optimization, asset allocation and risk management. Providing an accessible yet rigorous approach to investment management, it gradually introduces ever more advanced quantitative tools for these areas. Using extensive examples, this book guides the reader from basic return and risk analysis, all the way through to portfolio optimization and risk characterization, and finally on to fully fledged quantitative asset allocation and risk management. It employs such tools as enhanced modern portfolio theory using Monte Carlo simulation and advanced return distribution analysis, analysis of marginal contributions to absolute and active portfolio risk, Value-at-Risk and Extreme Value Theory. All this is performed within the same conceptual, theoretical and empirical framework, providing a self-contained, comprehensive reading experience with a strongly practical aim.
Author: M. Rasmussen
Publisher: Springer
ISBN: 0230512852
Category : Business & Economics
Languages : en
Pages : 453
Get Book Here
Book Description
Targeted towards institutional asset managers in general and chief investment officers, portfolio managers and risk managers in particular, this practical book serves as a comprehensive guide to quantitative portfolio optimization, asset allocation and risk management. Providing an accessible yet rigorous approach to investment management, it gradually introduces ever more advanced quantitative tools for these areas. Using extensive examples, this book guides the reader from basic return and risk analysis, all the way through to portfolio optimization and risk characterization, and finally on to fully fledged quantitative asset allocation and risk management. It employs such tools as enhanced modern portfolio theory using Monte Carlo simulation and advanced return distribution analysis, analysis of marginal contributions to absolute and active portfolio risk, Value-at-Risk and Extreme Value Theory. All this is performed within the same conceptual, theoretical and empirical framework, providing a self-contained, comprehensive reading experience with a strongly practical aim.
Author: Attilio Meucci
Publisher: Springer Science & Business Media
ISBN: 3642009646
Category : Business & Economics
Languages : en
Pages : 547
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Book Description
Discusses in the practical and theoretical aspects of one-period asset allocation, i.e. market Modeling, invariants estimation, portfolia evaluation, and portfolio optimization in the prexence of estimation risk The book is software based, many of the exercises simulate in Matlab the solution to practical problems and can be downloaded from the book's web-site
Author: David M. Berns
Publisher: John Wiley & Sons
ISBN: 1119566940
Category : Business & Economics
Languages : en
Pages : 144
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Book Description
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.
Author: Lev Dynkin
Publisher: Princeton University Press
ISBN: 0691210616
Category : Business & Economics
Languages : en
Pages : 999
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Book Description
The practice of institutional bond portfolio management has changed markedly since the late 1980s in response to new financial instruments, investment methodologies, and improved analytics. Investors are looking for a more disciplined, quantitative approach to asset management. Here, five top authorities from a leading Wall Street firm provide practical solutions and feasible methodologies based on investor inquiries. While taking a quantitative approach, they avoid complex mathematical derivations, making the book accessible to a wide audience, including portfolio managers, plan sponsors, research analysts, risk managers, academics, students, and anyone interested in bond portfolio management. The book covers a range of subjects of concern to fixed-income portfolio managers--investment style, benchmark replication and customization, managing credit and mortgage portfolios, managing central bank reserves, risk optimization, and performance attribution. The first part contains empirical studies of security selection versus asset allocation, index replication with derivatives and bonds, optimal portfolio diversification, and long-horizon performance of assets. The second part covers portfolio management tools for risk budgeting, bottom-up risk modeling, performance attribution, innovative measures of risk sensitivities, and hedging risk exposures. A first-of-its-kind publication from a team of practitioners at the front lines of financial thinking, this book presents a winning combination of mathematical models, intuitive examples, and clear language.
Author: Pierre Brugière
Publisher: Springer Nature
ISBN: 3030377407
Category : Mathematics
Languages : en
Pages : 212
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Book Description
This self-contained book presents the main techniques of quantitative portfolio management and associated statistical methods in a very didactic and structured way, in a minimum number of pages. The concepts of investment portfolios, self-financing portfolios and absence of arbitrage opportunities are extensively used and enable the translation of all the mathematical concepts in an easily interpretable way. All the results, tested with Python programs, are demonstrated rigorously, often using geometric approaches for optimization problems and intrinsic approaches for statistical methods, leading to unusually short and elegant proofs. The statistical methods concern both parametric and non-parametric estimators and, to estimate the factors of a model, principal component analysis is explained. The presented Python code and web scraping techniques also make it possible to test the presented concepts on market data. This book will be useful for teaching Masters students and for professionals in asset management, and will be of interest to academics who want to explore a field in which they are not specialists. The ideal pre-requisites consist of undergraduate probability and statistics and a familiarity with linear algebra and matrix manipulation. Those who want to run the code will have to install Python on their pc, or alternatively can use Google Colab on the cloud. Professionals will need to have a quantitative background, being either portfolio managers or risk managers, or potentially quants wanting to double check their understanding of the subject.
Author: Richard O. Michaud
Publisher: Oxford University Press
ISBN: 0199887195
Category : Business & Economics
Languages : en
Pages : 207
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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.
Author: Thierry Roncalli
Publisher: CRC Press
ISBN: 1482207168
Category : Business & Economics
Languages : en
Pages : 430
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Book Description
Although portfolio management didn't change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management. Risk parity then became a popular financial model of investment after the global fina
Author: Christian L. Dunis
Publisher: Springer
ISBN: 1137488808
Category : Business & Economics
Languages : en
Pages : 349
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Book Description
As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
Author: Riccardo Rebonato
Publisher: Cambridge University Press
ISBN: 1107048117
Category : Business & Economics
Languages : en
Pages : 519
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Book Description
A rigorous presentation of a novel methodology for asset allocation in financial portfolios under conditions of market distress.
Author: Emmanuel Jurczenko
Publisher: John Wiley & Sons
ISBN: 1786305445
Category : Business & Economics
Languages : en
Pages : 460
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Book Description
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.
