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Blockchain, artificial intelligence and financial services : Implications and applications for finance and accounting professionals
Blockchain technology and artificial intelligence (AI) have the potential to transform how the accounting and financial services industries engage with the business, stakeholder and consumer communities. Presenting a blend of technical analysis with current and future applications, this book provides professionals with an action plan to embrace and move forward with these new technologies in financial and accounting organizations.
Big Data Science in Finance
Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides
Asset Sales : Their Role in Restructuring and Financing Firms
Examines the corporate asset market and the mechanisms of asset sale transactions. The book then focuses on the theory of finance in asset sales (the efficiency and financing theory) and the extensive empirical literature now available. In light of recent and rapid technological and digital advances, the last section presents new perspectives on analyzing asset sales transactions. Chiefly intended as a primer for PhD students and academics, the book offers a road map of the empirical research landscape and suggests future research directions.
Arts, Sciences, and Economics : A Historical Safari
This book has a rather long-winding history. It is not like anything else the present author ever wrote, as all the rest is theoretical economics in a d- tinctively mathematical dress. For the emergence of the following pages, there are several people, - cept the author, who are to have the credit, or perhaps the blame.
Artificiality and sustainability in entrepreneurship : Exploring the unforeseen, and paving the way to a sustainable future
Explores the past, present, and future of artificiality and sustainability in entrepreneurship – the unforeseen consequences and ways to advance to a sustainable future. In particular, it connects artificiality, sustainability and entrepreneurship, intertwining artificial with the specific phenomenon of those novel digital technologies that provoke continuous and significant change in our lives and business. Unlike digital entrepreneurship research, which focuses on digital technology development and management, this book covers processes and mechanisms of sustainable adaptability of entrepreneurs, the business logic of start-ups, and the collaborative behaviours under the mass digital transformation, including the prevalence of artificial intelligence. Some of the questions that this book answers are as follows: How has entrepreneurship reacted to such challenges previously? What lessons have been learned and need to be carried forward? How can entrepreneurship and the artefacts of entrepreneurship respond to current challenges? What should be the mindset of the entrepreneur to assure sustainable adaptation? How to embrace and embed the new business logic?
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.
Applied Econometrics with R
This is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of econometric models, from classical linear regression models for cross-section, time series or panel data and the common non-linear models of microeconometrics such as logit, probit and tobit models, to recent semiparametric extensions. In addition, it provides a chapter on programming, including simulations, optimization, and an introduction to R tools enabling reproducible econometric research.
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.
AI Strategy for sales and marketing : Connecting marketing, sales and customer experience
AI Strategy for Sales and Marketing presents a framework for understanding how AI can boost customer-centricity and sales by creating a connected strategy that delivers value today and into the future. Supported by practical tips and advice throughout, it covers topics including personalization, upskilling, customer experience for both on and offline shopping channels and the importance of using AI responsibly to create consumer trust.
Agent-Based Models of Energy Investment Decisions
This book demonstrates how bounded rational decision models can be standardized and parameterized by socio-economic data. Focusing on private energy technology investment decisions, the author shows how different representative agents can be constructed using search rules, analysis tools and decision strategies. Diffusion curves for energy technologies such as solar collectors, boilers and efficiency upgrades for buildings are calculated. Further, the model is extended to study the impact of firms’ competition on technology diffusion. The modeling approach presented in this book may serve as a template for applications in other domain.
Agent-based computational modelling : Applications in demography, social, economic and environmental sciences
The present book describes the methodology to set up agent-based models and to study emerging patterns in complex adaptive systems resulting from multi-agent interaction. It offers the application of agent-based models in demography, social and economic sciences and environmental sciences. It presents and combines different approaches how to implement agent-based computational models and tools in an integrative manner that can be extended to other cases.
Advertising in contemporary consumer culture
This is the first scholarly book dedicated to reading the work of contemporary filmmakers and their impact on modern marketing and advertising. Drawing from consumer culture theory, film and media studies, the author presents an expansive analysis of a range of renowned filmmakers who have successfully applied their aesthetic and narrative vision to commercial advertising. It challenges some traditional advertising tropes and sheds light on the changing nature of advertising in the contemporary media context. Utilising Deleuze and Guattari’s notion of assemblage, This book addresses themes of spatiality and time, narrative and aesthetics and consumer reception within a new frame of reference that re-contextualises classical concepts of genre, platform and aesthetic categories. These diverse elements are embedded into a larger discussion of the resonance of contemporary advertising for consumer culture and the implications of the hybridity characteristic of convergent media platforms for understanding the potential of advertising in the twenty-first century.
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 robust and nonparametric methods in efficiency analysis : Methodology and applications
This readable book makes available an intuitive yet rigorous presentation of advanced nonparametric and robust methods. This flexible toolbox can be used in theories based on the neoclassical theory of production and its alternatives, including evolutionary theories.
Advanced REIT Portfolio Optimization : Innovative Tools for Risk Management
This book provides an investor-friendly presentation of the premises and applications of the quantitative finance models governing investment in one asset class of publicly traded stocks, specifically real estate investment trusts (REITs). The models provide highly advanced analytics for REIT investment, including: portfolio optimization using both historic and predictive return estimation; model backtesting; a complete spectrum of risk assessment and management tools with an emphasis on early warning systems, risk budgeting, estimating tail risk, and factor analysis; derivative valuation; and incorporating ESG ratings into REIT investment.
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.
Advanced Financial Accounting
An up-to-date, comprehensive, and highly illustrated presentation of the accounting and reporting principles and procedures used in a variety of business entities.
Advanced Data Mining Techniques
This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focusses on business applications of data mining. Methods are presented with simple examples, applications are reviewed, and relativ advantages are evaluated.
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.
