Refine Results
Sort By
From
To
Page 14
Page 14
Bio-inspired credit risk analysis : Computational intelligence with support vector machines
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.
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
Big Data in Energy Economics
Combines energy economics and big data modeling analysis in energy conversion and management and comprehensively introduces the relevant theories, key technologies, and application examples of the smart energy economy. With the help of time series big data modeling results, energy economy managers develop reasonable and feasible pricing mechanisms of electricity price and improve the absorption capacity of the power grid. In addition, they also carry out scientific power equipment scheduling and cost–benefit analysis according to the results of data mining, so as to avoid the loss caused by accidental damage of equipment. Energy users adjust their power consumption behavior through the modeling results provided and achieve the effect of energy saving and emission reduction while reasonably reducing the electricity expenditure.
Biased technical change and economic conservation laws
Makes use of Lie groups to shed new light on the analysis of economic conservation laws. Economic conservation laws are not simply abstract concepts; this book shows that they are tools of empirical analysis that can be applied to such topics as analyses of macro performance and corporate efficiency.
Behavioral competencies of digital professionals : Understanding the role of emotional intelligence
Shedding new light on the human side of big data through the lenses of emotional and social intelligence competencies, this book advances the understanding of the requirements of the different professions that deal with big data. It also illustrates the empirical evidence collected through the application of the competency-based methodology to a sample of data scientists and data analysts, the two most in-demand big data jobs in the labor market.
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.
Bargaining Power Effects in Financial Contracting : A Joint Analysis of Contract Type and Placement Mode Choices
The aim of this dissertation is to examine bargaining power effects in financial contracting. In particular power effects on firms' choices of contract type (debt vs. equity) and placement mode (public offering vs. private placement)
ARIS design platform : Advanced process modelling and administration
ARIS is ranked as the leading Business Process Modelling tool in the Gartner Quadrant for Business Process Analysis and Optimization. The ARIS Design Platform is being used as a business process management (BPM) tool for projects in BPM, quality management, business analysis and design, software development, implementation of service-oriented architectures and so forth. Following on from Rob Davis’ successful introductory text, ARIS Design Platform: Getting Started with BPM, this new book covers in detail some of the more advanced concepts of using ARIS Business Architect in the new ARIS 7 Design Platform. Written in a reader-friendly style, it contains detailed explanations of key concepts combined with numerous examples, hints and tips gained from many years of practical experience of using ARIS.
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.
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.
Antecedents of venture firms' internationalization : A conjoint analysis of international entrepreneurship in the net economy
With the continuing dispersion of the global digital network and performance improvements of information and communication technologies, resource-poor start-ups with online business models have emerged in large numbers. These firms are able to deploy their competitive advantages across their country borders early in their life-cycle and engage in international commerce at a fast pace. An increased immediacy between the firms and the globally accessible customer is observed. Julia Christofor’s study aims to analyze the conditions of the initial internationalization decision in the Net Economy. Based on Information Systems, International Entrepreneurship, and Entrepreneurship literature, factors, which constitute the internationalization propensity, are derived. The results of this study suggest that a holistic perspective including the founder, business model and the firm level should be considered when explaining the internationalization propensity of entrepreneurs.
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.
Analysis of microdata
The availability of microdata has increased rapidly over the last decades, and standard statistical and econometric software packages for data analysis include ever more sophisticated modeling options. The goal of this book is to familiarize readers with a wide range of commonly used models, and thereby to enable them to become critical consumers of current empirical research, and to conduct their own empirical analyses.
Analysis and Algorithms for Service Parts Supply Chains
Services requiring parts has become a $1.5 trillion business annually worldwide, creating a tremendous incentive to manage the logistics of these parts efficiently by making planning and operational decisions in a rational and rigorous manner. This book provides a broad overview of modeling approaches and solution methodologies for addressing service parts inventory problems found in high-powered technology and aerospace applications. The focus in this work is on the management of high cost, low demand rate service parts found in multi-echelon settings. This unique book, with its breadth of topics and mathematical treatment, begins by first demonstrating the optimality of an order-up-to policy [or (s-1,s)] in certain environments. This policy is used in the real world and studied throughout the text. The fundamental mathematical building blocks for modeling and solving applications of stochastic process and optimization techniques to service parts management problems are summarized extensively. A wide range of exact and approximate mathematical models of multi-echelon systems is developed and used in practice to estimate future inventory investment and part repair requirements.
An Introduction to Efficiency and Productivity Analysis
It is designed to be a "first port of call" for people wishing to study efficiency and productivity analysis. The book provides an accessible introduction to the four principal methods involved: econometric estimation of average response models; index numbers; data envelopment analysis (DEA); and stochastic firontier analysis (SFA). For each method, we provide a detailed introduction to the basic concepts, give some simple numerical examples, discuss some of the more important extensions to the basic methods, and provide references for further reading. In addition, we provide a number of detailed empirical applications using real-world data.
Ambiguities in Decision-oriented Life Cycle Inventories: The Role of Mental Models and Values
Shows for the first time how mental models and values influence this attribution in the life cycle inventory step of LCA. One of the key findings is that the different management rules for a sustainable use of materials must be taken into account for the attribution of material and energy flows to a product. Otherwise, improvement options recommended by an LCA might turn out to even worsen the environmental situation if reassessed from a meta-perspective. As a consequence of this book, the claim of unambiguitiy (‘objectivity’) of the life cycle inventory must be abandoned. A group-model building process for LCA is developed that allows one to grasp the decision makers' mental models and values in the inventory analysis on a case- and situation-specific basis. Only by this, LCA results will become relevant in a decision-making process. Two case studies on the modelling of recycling and other end-of-life options of aluminium windows and beech wood railway sleepers in LCA complement the methodological part.
Amartya Sens Capability Approach: Theoretical Insights and Empirical Applications
Kuklys examines how Nobel Prize-winning economist Amartya Sen’s approach to welfare measurement can be put in practice for poverty and inequality measurement in affluent societies such as the UK. Sen argues that an individual’s welfare should not be measured in terms of her income, but in terms what she can actually do or be, her capabilities. In Chapters 1 and 2, Kuklys describes the capability approach from a standard welfare economic point of view and provides a comprehensive literature review of the empirical applications in this area of research. In the remaining chapters, novel econometric techniques are employed to operationalise the concepts of functionings and capability to investigate inequality and poverty in terms of capability in the UK. Kuklys finds that capability measurement is always a useful complement to traditional monetary analysis, and particularly so in the case of capability-deprived disabled individuals.
AI in marketing, sales and service : How marketers without a data science degree can use AI, big data and bots
Shows you: how customer and market potential can be automatically identified and profiled; how media planning can be intelligently automated and optimized with AI and Big Data; how (chat)bots and digital assistants can make communication between companies and consumers more efficient and smarter; how you can optimize Customer Journeys based on Algorithmics and AI; and how to conduct market research in more efficient and smarter way.
AI in marketing : Applications, insights, and analysis
AI in marketing equips students with the knowledge to understand the impact of artificial intelligence (AI) on marketing strategies, processes, and activities, empowering them to navigate the AI-driven marketing landscape confidently. divided into four parts, it provides a comprehensive exploration of AI's transformative role in marketing. the first part lays the groundwork, offering foundational insights into the intersection of AI and marketing. Part II explores the various applications of AI in marketing, and the tools marketers use to optimize their processes and deliver enhanced customer experiences. the third part focuses on leveraging AI for consumer insights, enabling marketers to craft data-driven strategies. the final part examines ethical considerations and the pedagogical integration of AI into marketing education.
