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Real Estate Asset Management

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Institutionelle Investoren (mithin Pensionskassen, Lebensversicherungsunternehmen, Stiftungen und Vorsorge-/Versorgungswerke) verfügen über hohe Investitionen in Immobilienanlagen. Das Management dieser Investitionen und des Bestandes erfolgt auf institutioneller Ebene i.d.R. im Rahmen des Asset Managements bzw. des auf Immobilien spezialisierten Real Estate Asset Managements. Trotz der hohen Investitionen ist der Markt des internen und externen „Asset Managements“ stark fragmentiert und intransparent, d.h. ein Vergleich unterschiedlicher Asset Management-Standards und -Ansätze ist bis heute nicht bzw. nur schwer möglich und führt zu Ineffizienzen auf dem Markt. Gleichwohl ist am Markt eine Professionalisierung der direkten und indirekten Immobilienanlage feststellbar. An dieser Stelle setzt das vorliegende Forschungsvorhaben an mit dem Ziel, den aktuellen Stand zum Real Estate Asset Management in der Schweiz, Deutschland und Österreich im Rahmen einer empirischen Erhebung in Kooperation mit der ASIP Verband der Schweizerischen Pensionskassen aufzuzeigen, untereinander abzugleichen und mit historischen Daten zu vergleichen. Dabei stellt sich insbesondere die Frage, wie die Bereiche Asset Allokation im Immobilienbereich, Asset Management und Organisation strukturiert sind und an welchen Stellen Optimierungspotentiale bestehen. Dabei werden sowohl die Bereiche der direkten Immobilienanlage als auch der indirekten Immobilienanlage anhand der gewonnenen Daten diskutiert. In der wissenschaftlichen Fachliteratur existieren zahlreiche Studien zu dem Bereich „Asset Management“, allerdings sind diese i.d.R. auf ein Land beschränkt, betrachten nicht ausschließlich den Bereich „Immobilie“, orientieren sich am reinen Portfolio-Management bzw. der Portfolio-Optimierung oder spiegeln nicht den aktuellen Stand der Unternehmenspraxis wider. Die empirische Erhebung unter den institutionellen Investoren wurde im Juli und August 2014 durchgeführt und ab September 2014 ausgewertet. Die Forschungsergebnisse sollen im Rahmen einer Buchpublikation veröffentlicht und auf mehreren Konferenzen im I. Quartal 2015 und bei ausgewählten Investoren verteilt werden.

Power and Gas Asset Management

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This book offers meaningful insights into an impending challenge for the energy industry, namely the increasing role of asset management amongst the utilities’ core operations. In the aftermath of energy digitalization, power and gas companies will be able to seize asset productivity—through risk-based operation and maintenance—and better balance capital and operational expenditures. By addressing the asset management of both power and gas infrastructures, and by adopting a comprehensive approach—including regulation and business models, as well as a solid technology background—this book offers a unique perspective on the energy utilities’ transformation journey and the road to optimal decision-making for both asset portfolio expansion and replacement. The asset management end-to-end mission requires appropriate internal governance—depending on the business framework—and the development of decision aid models (for asset replacement and maintenance), supported on probabilistic risk and reliability indexes. This book advocates systematically digitalizing the power and gas assets, addressing both data governance and infrastructure, alongside real-time equipment condition monitoring. It also provides a meaningful methodology for designing data-centric asset management and predictive operation and maintenance, using artificial intelligence and engineering-based approaches. As such, it provides valuable strategy, methods and models—illustrated by case studies and proofs of concept—for a wide range of stakeholders, including utilities and industry professionals, regulators, policy-makers, researchers and students.

Data Intensive Industrial Asset Management

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This book presents a step by step Asset Health Management Optimization Approach Using Internet of Things (IoT). The authors provide a comprehensive study which includes the descriptive, diagnostic, predictive, and prescriptive analysis in detail. The presentation focuses on the challenges of the parameter selection, statistical data analysis, predictive algorithms, big data storage and selection, data pattern recognition, machine learning techniques, asset failure distribution estimation, reliability and availability enhancement, condition based maintenance policy, failure detection, data driven optimization algorithm, and a multi-objective optimization approach, all of which can significantly enhance the reliability and availability of the system.

Definitions, Concepts and Scope of Engineering Asset Management

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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.

Software Engineering Research, Management and Applications 2012

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The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality.  The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.  The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution-this permits a rapid and broad dissemination of research results.   The purpose of the 10th International Conference on Software Engineering Research, Management and Applications(SERA 2012) held on May 3- June 1, 2012 in Shanghai, China was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas and research results about all aspects (theory, applications and tools) of Software Engineering Research, Management and Applications, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.   The conference organizers selected 12 outstanding papers from those papers accepted for presentation at the conference in order to publish them in this volume.  The papers were chosen based on review scores submitted by members of the program committee, and further rigorous rounds of review.

Private Wealth Management Definition

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Private wealth management (PWM) involves the management of the assets of high net worth individuals (HNWI) or accredited investors. Private wealth management firms have established close working relationships with high net worth clients to understand their financial needs and help them build investment portfolios that can meet their clients' financial goals. They offer a range of services, including portfolio management, real estate planning, mortgage planning, asset protection, tax management, and other financial services. Private wealth management services are provided by large corporations, independent financial advisers and portfolio managers who specialize in working with high net worth private clients.

Private Wealth Management Definition

www.discountscat.com/content/32306-private-wealth-management-definition.html

Private wealth management (PWM) involves the management of the assets of high net worth individuals (HNWI) or accredited investors. Private wealth management firms have established close working relationships with high net worth clients to understand their financial needs and help them build investment portfolios that can meet their clients' financial goals.

Top Investors & Wealth Management Companies

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Here is a list of the top investors and wealth management companies: Betterment, Vanguard, Moneyfarm, Robinhood, Advizr, Nutmeg, Wealthfront, Habito, Hydrogen, Sigfig and more. We'll share how these great companies are positioning themselves for success as we move to the new normal.