Intelligent Asset Management

The fundamental motivation of this book is to contribute to the future advancement of Asset Management in the context of industrial plants and infrastructures. The book aims to foster a future perspective that takes advantage of value-based and intelligent asset management in order to make a step forward with respect to the evolution observed nowadays. Indeed, the current understanding of asset management is primarily supported by well-known standards. Nonetheless, asset management is still a young discipline and the knowledge developed by industry and academia is not set in stone yet. Furthermore, current trends in new organizational concepts and technologies lead to an evolutionary path in the field. Therefore, this book aims to discuss this evolutionary path, starting first of all from the consolidated theory, then moving forward to discuss: • The strategic understanding of value-based asset management in a company; • An operational definition of value, as a concept on the background of value-based asset management; • The identification of intelligent asset management, with the aim to frame a set of “tools” recommended to support the asset-related decision-making process over the asset lifecycle; • The emergence of new technologies such as cyber physical systems and digital twins, and the implications of this on asset management.

This book presents a systematic application of recent advances in artificial intelligence (AI) to the problem of asset management. While natural language processing and text mining techniques, such as semantic representation, sentiment analysis, entity extraction, commonsense reasoning, and fact checking have been evolving for decades, finance theories have not yet fully considered and adapted to these ideas. In this unique, readable volume, the authors discuss integrating textual knowledge and market sentiment step-by-step, offering readers new insights into the most popular portfolio optimization theories: the Markowitz model and the Black-Litterman model. The authors also provide valuable visions of how AI technology-based infrastructures could cut the cost of and automate wealth management procedures. This inspiring book is a must-read for researchers and bankers interested in cutting-edge AI applications in finance.

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.

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.

Engineering Asset Management discusses state-of-the-art trends and developments in the emerging field of engineering asset management as presented at the Fourth World Congress on Engineering Asset Management (WCEAM). It is an excellent reference for practitioners, researchers and students in the multidisciplinary field of asset management, covering such topics as asset condition monitoring and intelligent maintenance; asset data warehousing, data mining and fusion; asset performance and level-of-service models; design and life-cycle integrity of physical assets; deterioration and preservation models for assets; education and training in asset management; engineering standards in asset management; fault diagnosis and prognostics; financial analysis methods for physical assets; human dimensions in integrated asset management; information quality management; information systems and knowledge management; intelligent sensors and devices; maintenance strategies in asset management; optimisation decisions in asset management; risk management in asset management; strategic asset management; and sustainability in asset management.

This book introduces readers to essential strategies, practices, and benchmarking for asset maintenance in operations intensive industries. Drawing on a case study from the oil and gas sector, it offers a methodology and practical solutions to help maintenance practitioners select and formulate an asset maintenance strategy, and to establish best maintenance practices at an organizational level using the frameworks developed here. It is intended for industry practitioners, young maintenance professionals, and students of engineering management who aspire to a career in operations intensive industries.

"As with his weekly column, James Montier's Value Investing is a must read for all students of the financial markets. In short order, Montier shreds the 'efficient market hypothesis', elucidates the pertinence of behavioral finance, and explains the crucial difference between investment process and investment outcomes. Montier makes his arguments with clear insight and spirited good humor, and then backs them up with cold hard facts. Buy this book for yourself, and for anyone you know who cares about their capital!" —Seth Klarman, President, The Baupost Group LLC The seductive elegance of classical finance theory is powerful, yet value investing requires that we reject both the precepts of modern portfolio theory (MPT) and pretty much all of its tools and techniques. In this important new book, the highly respected and controversial value investor and behavioural analyst, James Montier explains how value investing is the only tried and tested method of delivering sustainable long-term returns. James shows you why everything you learnt at business school is wrong; how to think properly about valuation and risk; how to avoid the dangers of growth investing; how to be a contrarian; how to short stocks; how to avoid value traps; how to hedge ignorance using cheap insurance. Crucially he also gives real time examples of the principles outlined in the context of the 2008/09 financial crisis. In this book James shares his tried and tested techniques and provides the latest and most cutting edge tools you will need to deploy the value approach successfully. It provides you with the tools to start thinking in a different fashion about the way in which you invest, introducing the ways of over-riding the emotional distractions that will bedevil the pursuit of a value approach and ultimately think and act differently from the herd.

“The Maintenance Management Framework” describes and reviews the concept, process and framework of modern maintenance management of complex systems; concentrating specifically on modern modelling tools (deterministic and empirical) for maintenance planning and scheduling. It will be bought by engineers and professionals involved in maintenance management, maintenance engineering, operations management, quality, etc. as well as graduate students and researchers in this field.