Machine Learning for Asset Managers PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Machine Learning for Asset Managers PDF full book. Access full book title Machine Learning for Asset Managers by Marcos M. López de Prado. Download full books in PDF and EPUB format.
Author: Marcos M. López de Prado
Publisher: Cambridge University Press
ISBN: 1108879721
Category : Business & Economics
Languages : en
Pages : 152
Get Book Here
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.
Author: Marcos M. López de Prado
Publisher: Cambridge University Press
ISBN: 1108879721
Category : Business & Economics
Languages : en
Pages : 152
Get Book Here
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.
Author: Andrew Ang
Publisher: Oxford University Press, USA
ISBN: 0199959323
Category : Business & Economics
Languages : en
Pages : 717
Get Book Here
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.
Author: Robert Zientara
Publisher: Robert Zientara
ISBN: 8394419232
Category : Business & Economics
Languages : en
Pages : 403
Get Book Here
Book Description
This book was written by a Maximo consultant for Maximo functional consultants to help them lead implementation projects better and faster. This is already the second edition of this book, revised and extended. The book covers the topic of how to implement IBM Maximo Asset Management efficiently and bring value to customers. The book begins by describing how to prepare the project and run the workshops. There is an explanation of how to design the system and what deliverables will be. The following chapters focus on the project organization to make it productive. This part of the book can be helpful also for managers of Maximo implementation teams. The second part of the book describes Maximo applications, their interactions, and processes. You will also find here a lot of configuration examples and sample content of the project deliverables. See what my readers have to say… “…I must thank you for your contribution towards the industry and how much it can help young and upcoming business consultants like me in getting things right. Knowledge is invaluable. Thanks for your time in creating a medium to share it globally…” —Hashmeet “…The book has immensely helped me in planning the activities and deploying the project….” —Kushal “…Very well written for a consultant to understand how to approach projects. Utilize many of your talking points with my clients. Great work!...” —John
Author: Paul Dickson (Lawyer)
Publisher:
ISBN: 9781804491065
Category : Asset-liability management
Languages : en
Pages : 0
Get Book Here
Book Description
Author: David M. Berns
Publisher: John Wiley & Sons
ISBN: 1119566940
Category : Business & Economics
Languages : en
Pages : 144
Get Book Here
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: Ellen Carr
Publisher: Columbia University Press
ISBN: 0231551533
Category : Business & Economics
Languages : en
Pages : 392
Get Book Here
Book Description
Diversification is a core principle of investing. Yet money managers have not applied it to their own ranks. Only around 10 percent of portfolio managers—the people most directly responsible for investing your money—are female, and the numbers are even worse at the ownership level. What are the causes of this underrepresentation, and what are its consequences—including for firms’ and clients’ bottom lines? In Undiversified, experienced practitioners Ellen Carr and Katrina Dudley examine the lack of women in investment management and propose solutions to improve the imbalance. They explore the barriers that subtly but effectively discourage women from entering and staying in the industry at each point in the pipeline. At the entry level, the lack of visible role models discourages students from considering the field, and those who do embark on an investment management career face many obstacles to retention and promotion. Carr and Dudley highlight the importance of informal knowledge about how to navigate career tracks, without which women are left at a disadvantage in an industry that lionizes confidence. They showcase a diverse constellation of successful female portfolio managers to demystify the profession. Drawing on wide-ranging research, interviews with prospective, current, and former industry practitioners, and the authors’ own experiences, Undiversified makes a compelling case that increasing the number of women could help transform active investment management at a time when it is under threat from passive strategies and technological innovation.
Author: Joe E. Amadi-Echendu
Publisher: Springer Science & Business Media
ISBN: 1447129245
Category : Technology & Engineering
Languages : en
Pages : 239
Get Book Here
Book Description
Asset Condition, Information Systems and Decision Models, is the second volume of the Engineering Asset Management Review Series. The manuscripts provide examples of implementations of asset information systems as well as some practical applications of condition data for diagnostics and prognostics. The increasing trend is towards prognostics rather than diagnostics, hence the need for assessment and decision models that promote the conversion of condition data into prognostic information to improve life-cycle planning for engineered assets. The research papers included here serve to support the on-going development of Condition Monitoring standards. This volume comprises selected papers from the 1st, 2nd, and 3rd World Congresses on Engineering Asset Management, which were convened under the auspices of ISEAM in collaboration with a number of organisations, including CIEAM Australia, Asset Management Council Australia, BINDT UK, and Chinese Academy of Sciences, Beijing University of Chemical Technology, China. Asset Condition, Information Systems and Decision Models will be of particular interest to finance, maintenance, and operations personnel whose roles directly affect the capability value of engineering asset base, as well as asset managers in both industry and government.
Author: William J. Bernstein
Publisher: McGraw Hill Professional
ISBN: 0071399577
Category : Business & Economics
Languages : en
Pages : 225
Get Book Here
Book Description
Time-Tested Techniques - Safe, Simple, and Proven Effective - for Building Your Own Investment Portfolio. "As its title suggest, Bill Bernstein's fine book honors the sensible principles of Benjamin Graham in the Intelligent Investor Bernstein's concepts are sound, his writing crystal clear, and his exposition orderly. Any reader who takes the time and effort to understand his approach to the crucial subject of asset allocation will surely be rewarded with enhanced long-term returns." - John C. Bogle, Founder and former Chief Executive Officer, The Vanguard Group President, Bogle Financial Markets Research Center Author, common Sense on Mutual Funds. "Bernstein has become a guru to a peculiarly '90s group: well-educated, Internet-powered people intent on investing well - and with minimal 'help' from professional Wall Street." - Robert Barker, Columnist, BusinessWeek. "I go home and tell my wife sometimes, 'I wonder if [Bernstein] doesn't know more than me.' It's humbling." - John Rekenthaler, Research Chief, Morningstar Inc. William Bernstein is an unlikely financial hero. A practicing neurologist, he used his self-taught investment knowledge and research to build one of today's most respected investor's websites. Now, let his plain-spoken The Intelligent Asset Allocator show you how to use the time-honored techniques of asset allocation to build your own pathway to financial security - one that is easy-to-understand, easier-to-apply, and supported by 75 years of solid history and wealth-building results.
Author: Adam Butler
Publisher: John Wiley & Sons
ISBN: 1119220351
Category : Business & Economics
Languages : en
Pages : 244
Get Book Here
Book Description
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.
Author: Joe E. Amadi-Echendu
Publisher: Springer Science & Business Media
ISBN: 1849961786
Category : Technology & Engineering
Languages : en
Pages : 400
Get Book Here
Book Description
Definitions, Concepts and Scope of Engineering Asset Management, the first volume in this new review series, seeks to minimise ambiguities in the subject matter. The ongoing effort to develop guidelines is shaping the future towards the creation of a body of knowledge for the management of engineered physical assets. Increasingly, industry practitioners are looking for strategies and tactics that can be applied to enhance the value-creating capacities of new and installed asset systems. The new knowledge-based economy paradigm provides imperatives to combine various disciplines, knowledge areas and skills for effective engineering asset management. This volume comprises selected papers from the 1st, 2nd, and 3rd World Congresses on Engineering Asset Management, which were convened under the auspices of ISEAM in collaboration with a number of organisations, including CIEAM Australia, Asset Management Council Australia, BINDT UK, and Chinese Academy of Sciences, Beijing University of Chemical Technology, China. Definitions, Concepts and Scope of Engineering Asset Management will be of interest to researchers in engineering, innovation and technology management, as well as to managers, planners and policy-makers in both industry and government.
