This book is devoted to recent developments and applications of multiple criteria decision aid tools in the field of finance, insurance and investment. It illustrates recent methods and procedures designed to solve problems related to finance, insurance and portfolio selection formulated through a mathematical programming framework and for which a large number of conflicting and incommensurable objectives (criteria, attributes) is simultaneously optimized. The book introduces researchers and practitioners to recent theoretical and methodological developments in multi-attributes portfolio selection, multiple criteria analysis in finance, insurance and investment. It is based on selected and invited papers presented and discussed at the 2013 International Conference on Multidimensional Finance, Insurance and Investment (ICMFII’13), held at the College of Business Administration at the University of Bahrain from 25th to 27th November 2013 with the co-sponsorship of the International Society on Multiple Criteria Decision Making and the Institute for Operations Research and the Management Sciences - MCDM section.

This volume highlights recent applications of multiple-criteria decision-making (MCDM) models in the field of finance. Covering a wide range of MCDM approaches, including multiobjective optimization, goal programming, value-based models, outranking techniques, and fuzzy models, it provides researchers and practitioners with a set of MCDM methodologies and empirical results in areas such as portfolio management, investment appraisal, banking, and corporate finance, among others. The book addresses issues related to problem structuring and modeling, solution techniques, comparative analyses, as well as combinations of MCDM models with other analytical methodologies.

This book offers a comprehensive guide to the use of neutrosophic sets in multiple criteria decision making problems. It shows how neutrosophic sets, which have been developed as an extension of fuzzy and paraconsistent logic, can help in dealing with certain types of uncertainty that classical methods could not cope with. The chapters, written by well-known researchers, report on cutting-edge methodologies they have been developing and testing on a variety of engineering problems. The book is unique in its kind as it reports for the first time and in a comprehensive manner on the joint use of neutrosophic sets together with existing decision making methods to solve multi-criteria decision-making problems, as well as other engineering problems that are complex, hard to model and/or include incomplete and vague data. By providing new ideas, suggestions and directions for the solution of complex problems in engineering and decision making, it represents an excellent guide for researchers, lecturers and postgraduate students pursuing research on neutrosophic decision making, and more in general in the area of industrial and management engineering.

When people or computers need to make a decision, typically multiple conflicting criteria need to be evaluated; for example, when we buy a car, we need to consider safety, cost and comfort. Multiple criteria decision making (MCDM) has been researched for decades. Now as the rising trend of big-data analytics in supporting decision making, MCDM can be more powerful when combined with state-of-the-art analytics and machine learning. In this book, the authors introduce a new framework of MCDM, which can lead to more accurate decision making. Several real-world cases will be included to illustrate the new hybrid approaches.

While there are many different models for performing system analysis, the multi-criteria decision making method has proven to be one of the most efficient. By analyzing the key concepts of this theory, the technique can be enhanced and will benefit future organizations and companies in novel ways. Multi-Criteria Decision Making for the Management of Complex Systems provides a comprehensive examination of the latest strategies and methods involved in decision theory. Featuring extensive coverage on relevant topics such as nested scalar convolutions, Pareto optimality, nonlinear schemes, and operator performance, this publication is ideally designed for engineers, students, professionals, academics, and researchers seeking innovative perspectives on the supervision of advanced decision making theories in system analysis.

This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

In the complex world of finance, understanding the relationship between a company's capital structure and its overall performance is crucial. This book offers a comprehensive exploration of the interdependence between capital structure decisions and business performance, with a specific focus on German-listed companies. It provides valuable insights into the intricate dynamics of corporate finance. Through a blend of theoretical frameworks, empirical research, and practical applications, the book presents readers with a thorough understanding of how capital structure decisions impact a company's profitability, risk profile, and long-term sustainability. From traditional theories of capital structure to cutting-edge empirical methodologies, the book outlines the latest developments in the field, offering practical tools and strategies for optimising financial decision-making. Moreover, the book explores how different regions and global trends influence capital structure decisions, providing a comprehensive examination of varying practices and the factors that shape them. It delves into specific aspects influencing global capital structures, including an analytical comparison of capital structures across key global markets such as the United States, the European Union, and China. This comparison highlights how economic, cultural, and market dynamics influence corporate leverage decisions. The impact of technological innovations and their role in reshaping financial strategies are also discussed. Designed for scholars, researchers, and advanced students in finance and economics, this book serves as a definitive reference for understanding the complex dynamics of corporate finance. With its rigorous analysis and practical insights, it equips readers with the knowledge and analytical tools needed to navigate the challenges of capital structure decision-making in today's dynamic business environment.

Covering pertinent areas of sustainable and responsible investment (SRI) this forward-looking book examines SRI in developing markets including its evolution, principles and concepts. It explores the drivers and challenges in developing economies and analyses the theoretical underpinnings to critical issues pertaining to SRI.

Governments must continuously update policies, laws, and legislation as the world continues to rapidly evolve due to technologies and changing cultural perspectives. To streamline policy creation and implementation, governments seek new and efficient methods to ensure their citizens’ and communities’ safety while also encouraging citizen participation. Advanced Methodologies and Technologies in Government and Society provides research on emerging methodologies in effective governing including sections on public sector management and socioeconomic development. While highlighting the challenges facing government officials and law enforcement such as crisis response and natural disaster management, this book shows how technology use can make those areas of government more efficient and improve preventative measures. This book is an ideal resource for law enforcement, government officials and agencies, policymakers, public servants, citizen activists, researchers, and political leaders seeking cutting-edge information to strengthen their government’s relationship with society and their constituents while also strengthening their policy measures through new technology and methods.