Revenue Management and Pricing Analytics, Guillermo Gallego; Huseyin Topaloglu
Автор: Campbell John Y. Название: Financial Decisions and Markets: A Course in Asset Pricing ISBN: 0691160805 ISBN-13(EAN): 9780691160801 Издательство: Wiley Рейтинг: Цена: 12672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
From the field's leading authority, the most authoritative and comprehensive advanced-level textbook on asset pricing
Financial Decisions and Markets is a graduate-level textbook that provides a broad overview of the field of asset pricing. John Campbell, one of the field's most respected authorities, introduces students to leading theories of portfolio choice, their implications for asset prices, and empirical patterns of risk and return in financial markets. Campbell emphasizes the interplay of theory and evidence, as theorists respond to empirical puzzles by developing models with new testable implications. Increasingly these models make predictions not only about asset prices but also about investors' financial positions, and they often draw on insights from behavioral economics.
After a careful introduction to single-period models, Campbell develops multiperiod models with time-varying discount rates, reviews the leading approaches to consumption-based asset pricing, and integrates the study of equities and fixed-income securities. He discusses models with heterogeneous agents who use financial markets to share their risks, but also may speculate against one another on the basis of different beliefs or private information. Campbell takes a broad view of the field, linking asset pricing to related areas, including financial econometrics, household finance, and macroeconomics. The textbook works in discrete time throughout, and does not require stochastic calculus. Problems are provided at the end of each chapter to challenge students to develop their understanding of the main issues in financial economics.
The most comprehensive and balanced textbook on asset pricing available, Financial Decisions and Marketswill be an essential resource for all graduate students in finance and related fields.
Integrated treatment of asset pricing theory and empirical evidence
Emphasis on investors' decisions
Broad view linking the field to areas including financial econometrics, household finance, and macroeconomics
Topics treated in discrete time, with no requirement for stochastic calculus
Solutions manual for problems available to professors
Автор: Bhaduri Название: Advanced Business Analytics ISBN: 9811007268 ISBN-13(EAN): 9789811007262 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The present book provides an enterprise-wide guide for anyone interested in pursuing analytic methods in order to compete effectively. It supplements more general texts on statistics and data mining by providing an introduction from leading practitioners in business analytics and real case studies of firms using advanced analytics to gain a competitive advantage in the marketplace. In the era of “big data” and competing analytics, this book provides practitioners applying business analytics with an overview of the quantitative strategies and techniques used to embed analysis results and advanced algorithms into business processes and create automated insight-driven decisions within the firm. Numerous studies have shown that firms that invest in analytics are more likely to win in the marketplace. Moreover, the Internet of Everything (IoT) for manufacturing and social-local-mobile (SOLOMO) for services have made the use of advanced business analytics even more important for firms. These case studies were all developed by real business analysts, who were assigned the task of solving a business problem using advanced analytics in a way that competitors were not. Readers learn how to develop business algorithms on a practical level, how to embed these within the company and how to take these all the way to implementation and validation.
Presents information to create a trade-off analysis framework for use in government and commercial acquisition environments
This book presents a decision management process based on decision theory and cost analysis best practices aligned with the ISO/IEC 15288, the Systems Engineering Handbook, and the Systems Engineering Body of Knowledge. It provides a sound trade-off analysis framework to generate the tradespace and evaluate value and risk to support system decision-making throughout the life cycle. Trade-off analysis and risk analysis techniques are examined. The authors present an integrated value trade-off and risk analysis framework based on decision theory. These trade-off analysis concepts are illustrated in the different life cycle stages using multiple examples from defense and commercial domains.
Provides techniques to identify and structure stakeholder objectives and creative, doable alternatives
Presents the advantages and disadvantages of tradespace creation and exploration techniques for trade-off analysis of concepts, architectures, design, operations, and retirement
Covers the sources of uncertainty in the system life cycle and examines how to identify, assess, and model uncertainty using probability
Illustrates how to perform a trade-off analysis using the INCOSE Decision Management Process using both deterministic and probabilistic techniques
Trade-off Analytics: Creating and Exploring the System Tradespace is written for upper undergraduate students and graduate students studying systems design, systems engineering, industrial engineering and engineering management. This book also serves as a resource for practicing systems designers, systems engineers, project managers, and engineering managers.
Gregory S. Parnell, PhD, is a Research Professor in the Department of Industrial Engineering at the University of Arkansas. He is also a senior principal with Innovative Decisions, Inc., a decision and risk analysis firm and has served as Chairman of the Board. Dr. Parnell has published more than 100 papers and book chapters and was lead editor of Decision Making for Systems Engineering and Management, Wiley Series in Systems Engineering (2nd Ed, Wiley 2011) and lead author of the Handbook of Decision Analysis (Wiley 2013). He is a fellow of INFORMS, the INCOSE, MORS, and the Society for Decision Professionals.
Описание: Uncover hidden fraud and red flags using efficient data analytics Fraud Data Analytics Methodology addresses the need for clear, reliable fraud detection with a solid framework for a robust data analytic plan.
Описание: Co-edited by acknowledged experts in the quantification of operational risk, Handbook of Operational Risk conveniently and systematically displays all of the financial engineering topics, theories, applications, and current statistical methodologies that are intrinsic to the subject matter.
Автор: Heckmann Название: Towards Supply Chain Risk Analytics ISBN: 3658148691 ISBN-13(EAN): 9783658148690 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this thesis, Iris Heckmann develops a profound conceptual basis of supply chain risk analytics. She transfers the newly defined concepts for the modelling and operationalization of supply chain risk within simulation and optimization approaches, in order to ease unexpected deviations and disruptions, which are subsumed under the notion of supply chain risk, increasingly aggravating the planning and optimization of supply chains.
Автор: Bendoly Elliot Название: Visual Analytics for Management ISBN: 1138190721 ISBN-13(EAN): 9781138190726 Издательство: Taylor&Francis Рейтинг: Цена: 9645.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides students with an in-depth understanding of the concepts, frameworks and processes used to analyze and present visual data for better decision-making. Expert contributors provide guidance in translating complex concepts from large data sets and how this translation drives management practice.
Описание: This handbook focuses on Data Envelopment Analysis (DEA) applications in operations analytics which are fundamental tools and techniques for improving operation functions and attaining long-term competitiveness. In fact, the handbook demonstrates that DEA can be viewed as Data Envelopment Analytics.Chapters include a review of cross-efficiency evaluation; a case study on measuring the environmental performance of OECS countries; how to select a set of performance metrics in DEA with an application to American banks; a relational network model to take the operations of individual periods into account in measuring efficiencies; how the efficient frontier methods DEA and stochastic frontier analysis (SFA) can be used synergistically; and how to integrate DEA and multidimensional scaling.In other chapters, authors construct a dynamic three-stage network DEA model; a bootstrapping based methodology to evaluate returns to scale and convexity assumptions in DEA; hybridizing DEA and cooperative games; using DEA to represent the production technology and directional distance functions to measure band performance; an input-specific Luenberger energy and environmental productivity indicator; and the issue of reference set by differentiating between the uniquely found reference set and the unary and maximal types of the reference set.Finally, additional chapters evaluate and compare the technological advancement observed in different hybrid electric vehicles (HEV) market segments over the past 15 years; radial measurement of efficiency for the production process possessing multi-components under different production technologies; issues around the use of accounting information in DEA; how to use DEA environmental assessment to establish corporate sustainability; a summary of research efforts on DEA environmental assessment applied to energy in the last 30 years; and an overview of DEA and how it can be utilized alone and with other techniques to investigate corporate environmental sustainability questions.
This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies.
Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a “big-data'” era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.
Название: Applied big data analytics in operations management / ISBN: 1522508864 ISBN-13(EAN): 9781522508861 Издательство: Turpin Рейтинг: Цена: 23654.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management.Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.
Автор: Rahul Saxena; Anand Srinivasan Название: Business Analytics ISBN: 1489986723 ISBN-13(EAN): 9781489986726 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a practitioner`s guide to the extensive and comprehensive use of data, data analysis, explanatory and predictive models and methods, and management based on facts, in support of business decisions and actions. Includes real-world case studies.
Автор: Abraham Duarte; Manuel Laguna; Rafael Marti Название: Metaheuristics for Business Analytics ISBN: 3319681176 ISBN-13(EAN): 9783319681177 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This essential metaheuristics tutorial provides descriptions and practical applications in the area of business analytics. It addresses key problems in predictive and prescriptive analysis, while also illustrating how problems that arise in business analytics can be modelled and how metaheuristics can be used to find high-quality solutions.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
