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CGE models and capital income tax reforms : The case of a dual income tax for Germany
The book suggests a novel way how the effects of tax reforms especially in the field of capital income taxation can be measured by means of dynamic computable general equilibrium (CGE) models.
Cellular Genetic Algorithms
CELLULAR GENETIC ALGORITHMS defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book. This class of genetic algorithms is shown to produce impressive results on a whole range of domains, including complex problems that are epistatic, multi-modal, deceptive, discrete, continuous, multi-objective, and random in nature. The focus of this book is twofold. On the one hand, the authors present new algorithmic models and extensions to the basic class of Cellular GAs in order to tackle complex problems more efficiently. On the other hand, practical real world tasks are successfully faced by applying Cellular GA methodologies to produce workable solutions of real-world applications.
Brand hate : Navigating consumer negativity in the digital world, 2nd
Focuses on the concept of “brand hate” and consumer negativity in today’s digital markets. It explores the emotional detachment consumers generate against valued brands and how negative experiences affect their and other consumers' loyalty. The book defines consumer brand hate and discusses its dimensions, antecedents, and consequences as well as the semiotics and legality of such brand hate activities based on current brand dilution arguments. It describes the situations which lead to anti-branding and how consumers choose to express their dissatisfaction with a company on individual and social levels. This newly updated edition discusses recent research findings from brand hate literature with new cases and extended managerial analysis.
Bond Portfolio Optimization
1 The tools of modern portfolio theory are in general use in the equity markets, either in the form of portfolio optimization software or as an accepted frame- 2 work in which the asset managers think about stock selection. In the ?xed income market on the other hand, these tools seem irrelevant or inapplicable. Bond portfolios are nowadays mainly managed by a comparison of portfolio 3 4 risk measures vis ¶a vis a benchmark. The portfolio manager’s views about the future evolution of the term structure of interest rates translate th- selves directly into a positioning relative to his benchmark, taking the risks of these deviations from the benchmark into account only in a very crude 5 fashion, i.e. without really quantifying them probabilistically. This is quite surprising since sophisticated models for the evolution of interest rates are commonly used for interest rate derivatives pricing and the derivation of ?xed 6 income risk measures.
Be data literate : The data literacy skills everyone needs to succeed
It is not enough for a business to have the best data if those using it don't understand the right questions to ask or how to use the information generated to make decisions. Be Data Literate is the essential guide to developing the curiosity, creativity and critical thinking necessary to make anyone data literate, without retraining as a data scientist or statistician.
Banking on (artificial) intelligence : Navigating the realities of ai in financial services
Provides a tailored overview of what AI specifically means for financial services, a highly regulated yet also disrupted industry. it investigates the current state of AI applications in financial services today along with the state of funding and partnerships between tech and banking industries. it also examines the key pillars of responsible AI and the importance of keeping humans in the loop. the book takes a deep dive into the use cases in the financial services industry, the challenges and opportunities, and the fragmented regulatory landscape. how can we effectively assess risks, and balance innovation and customer centricity with trust in AI in financial services? can smaller organizations reap the benefits of the technology? how can institutions deploy AI responsibly and securely, and promote a fairer and more equitable future for more people?
Banking for Family Business: A New Challenge for Wealth Management
Hints of globalization have actually been around for several decades, even though they made only a modest impact; however, the availability of global capital and advances in communication technology have emp- sized the process of internationalization and the tools available to connect and integrate business activities to answer to more complex needs of c- ents. Moreover, the financial scandals and the review of mutual fund trade activity in the US by the Attorney General Elliot Spitzer have highlighted the importance to focus all efforts on renewing the confidence of prof- sional investors and their clients who have entrusted their capital to asset managers. Therefore, there is a growing need in the market to reinforce the concept of “Shared Positive Values” among the entire industry and among its stakeholders.
Balancing Exploration and Exploitation by Creating Organizational Think Tanks
Key for successful knowledge management is a balance between exploration and exploitation. Danger arises when exploration is neglected in favour of exploitation since that may result in an organization which lacks innovation capability. In order to prevent this, an idea has been put forward in recent knowledge management research called ambidexterity, which means the simultaneous and balanced pursuing of both exploration and exploitations activities. Tatjana-Xenia Puhan follows up on this idea by concluding that ambidexterity need not necessarily be implemented in one single organization but can also be realised in a network of associated organizations. The interorganizational ambidexterity is based on co-specialisation: one organisation is devoted solely to exploration while associated organizations focus on their competences in exploitation. Furthermore, the author develops the concept of think tanks as organizations that concentrate on radical innovations while their network associates exploit this newly generated knowledge commercially.
Asias debt capital markets : Prospects and strategies for development
The book has three parts. Part I describes the characteristics and historical origins of these markets. Part II examines the contemporary bond markets and shows how they contribute to general welfare, describes the relationship between the banking sector and capital markets, and assesses prospects for reform in Asia's governmental and corporate debt markets. Part III explains the micro-level impediments and obstacles that must be the first targets of any reform efforts, provides an appraisal of attempts at regional cooperation to stimulate structural reform, and lastly contributes proposals to accelerate the growth and reach of bond markets throughout Asia.
Artificial intelligence for asset management and investment : A strategic perspective
The rise of artificial intelligence is nothing short of a technological revolution. AI is poised to completely transform asset management and investment banking, yet its current application within the financial sector is limited and fragmented. Existing AI implementations tend to solve very narrow business issues, rather than serving as a powerful tech framework for next-generation finance. Artificial Intelligence for Asset Management and Investment provides a strategic viewpoint on how AI can be comprehensively integrated within investment finance, leading to evolved performance in compliance, management, customer service, and beyond.
Applied Research in Uncertainty Modeling and Analysis
For a long time uncertainty has been considered synonymous with random, stochastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous. In the past forty years numerous tools that model uncertainty, above and beyond statistics, have been proposed by several engineers and scientists. The tool/method to model uncertainty in a specific context should really be chosen by considering the features of the phenomenon under consideration, not independent of what is known about the system and what causes uncertainty. In this fascinating overview of the field, the authors provide broad coverage of uncertainty analysis/modeling and its application. Applied Research in Uncertainty Modeling and Analysis presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise. Rather than focusing explicitly on theory, the authors use real-world examples to demonstrate the strength of the chosen methodology. Applied Research in Uncertainty Modeling and Analysis concentrates on general aspects of uncertainty, modeling, and methods, and focuses on various applications, included Biomedical Engineering, Chemical Engineering, Structural Engineering, and Transportation Engineering.
Applications of simulation methods in environmental and resource economics
Simulation methods are revolutionizing the practice of applied economic analysis. This volume collects eighteen chapters written by leading researchers from prestigious research institutions the world over. The common denominator of the papers is their relevance for applied research in environmental and resource economics. The topics range from discrete choice modeling with heterogeneity of preferences, to Bayesian estimation, to Monte Carlo experiments, to structural estimation of Kuhn-Tucker demand systems, to evaluation of simulation noise in maximum simulated likelihood estimates, to dynamic natural resource modeling. Empirical cases are used to show the practical use and the results brought forth by the different methods.
Analysis, Control and Optimization of Complex Dynamic Systems
Analysis, Control and Optimization of Complex Dynamic Systems gathers in a single volume a spectrum of complex dynamic systems related papers written by experts in their fields, and strongly representative of current research trends. Complex systems present important challenges, in great part due to their sheer size which makes it difficult to grasp their dynamic behavior, optimize their operations, or study their reliability. Yet, we live in a world where, due to increasing inter-dependencies and networking of systems, complexity has become the norm. With this in mind, the volume comprises two parts. The first part is dedicated to a spectrum of complex problems of decision and control encountered in the area of production and inventory systems. The second part is dedicated to large scale or multi-agent system problems occurring in other areas of engineering such as telecommunication and electric power networks, as well as more generic context.
An annotated timeline of operations research: An informal history
An Annotated Timeline of Operations Research: An Informal History recounts the evolution of Operations Research (OR) as a new science - the science of decision making. Arising from the urgent operational issues of World War II, the philosophy and methodology of OR has permeated the resolution of decision problems in business, industry, and government. The Timeline chronicles the history of OR in the form of self-contained, expository entries. Each entry presents a concise explanation of the events and people under discussion, and provides key sources where further relevant information can be obtained. In addition, books and papers that have influenced the development of OR or helped to educate the first generations of OR academics and practitioners are cited throughout the book.
Agricultural biodiversity and biotechnology in economic development
The topics addressed in this book are of vital importance to the survival of humankind. Agricultural biodiversity, encompassing genetic diversity as well as human knowledge, is the base upon which agricultural production has been built, and protecting this resource is critical to ensuring the capacity of current and future generations to adapt to unforeseen challenges. Agricultural biodiversity underpins the productivity of all agricultural systems and is particularly important for poor and food-insecure farmers, who maintain highly diverse production systems in response to the marginal and risky production conditions they operate under. Understanding the importance of agricultural biodiversity in the livelihoods of the food insecure and enhancing its performance through the use of a variety of tools, including biotechnology, is a critically important issue in the world today
Agent-based modeling : The Santa Fe Institute artificial stock market model revisited
An excellent reference to both the learning, and empirical literature in finance." (Krzysztof Piasecki, Zentralblatt MATH, Vol. 1141, 2008) "Norman Ehrentreich was one of the daring few to take on the model, and he has summarized his work and findings in this excellent book. … It is useful primer for anyone interested in getting started in the area of agent-based finance. … It is essential reading for anyone interested in the dynamics of the SFI market in particular, but I also recommend it for others as a useful resource on agent-based financial market design as well." (Blake LeBaron, Journal of Artificial Societies and Social Simulation, Vol. 12 (2), March, 2009)
Advances in Crowdfunding : Research and Practice
This book presents a comprehensive and up-to-date collection of knowledge on the state of crowdfunding research and practice. It considers crowdfunding models and their different manifestations across a variety of geographies and sectors, and explores the perspectives of fundraisers, backers, platforms, and regulators.
Advanced introduction to marketing strategy
Presents a systematic, next-generation approach to marketing strategy, demonstrating how success is gained and sustained via continuous innovation to create new value for customers. George S. Day develops the outside-in approach to formulating strategy, while providing compelling insights into key market stakeholders to illustrate how to sustain customer value leadership in the face of mounting market turbulence.
Adaptive Scalarization Methods in Multiobjective Optimization
This book presents new adaptive solution methods for multiobjective optimization problems based on parameter dependent scalarizations. With the help of sensitivity results an adaptive parameter control is developed so that high-quality approximations of the efficient set are generated. These examinations are based on a general scalarization approach for arbitrary partial orderings defined by a closed pointed convex cone in the objective space. The application of the results to many other well-known scalarization methods is also presented. Background material of multiobjective optimization and scalarization approaches is concisely summarized at the beginning. The effectiveness of these new methods is demonstrated by test problems and a recent problem in intensity-modulated radiotherapy. The book concludes with a further application: a procedure for solving multiobjective bilevel optimization problems.
Adaptive Information Systems and Modelling in Economics and Management Science
Learning and adaption are key features of "real economies". Studying interesting real phenomena like innovation, industry evolution or the role of expectation formulation in financial markets thus necessitates novel methods of data analysis and modelling. This title covers statistical models of heterogeneity, artificial consumer markets, models of adaptive expectation formulation in financial markets and agent-based models of industry evolution, product diversification and energy markets. The joint findings are presented in a manner that is interesting both for readers with a background in economics/management and mathematics and statistics and also for non-expert readers because it allows them to grasp the ideas of modern management science. This book thus provides a unique integrated toolbox for building realistic agent-based models of learning and adaption in a variety of settings based on sound data analysis.
