Models and Modeling

Optimal Portfolio Modeling is an easily accessible introduction to portfolio modeling for those who prefer an intuitive approach to this discipline. While early chapters provide engaging insights on the statistical properties of markets, this book quickly moves on to illustrate invaluable trading and risk control models based on popular programs such as Excel and the statistical modeling language R. This reliable resource presents modeling formulas that will allow you to effectively maximize the performance, minimize the drawdown, and manage the risk of your portfolio.

Network Modeling and Simulation is a practical guide to using modeling and simulation to solve real-life problems. The authors give a comprehensive exposition of the core concepts in modeling and simulation, and then systematically address the many practical considerations faced by developers in modeling complex large-scale systems. The authors provide examples from computer and telecommunication networks and use these to illustrate the process of mapping generic simulation concepts to domain-specific problems in different industries and disciplines. Key features: Provides the tools and strategies needed to build simulation models from the ground up rather than providing solutions to specific problems. Includes a new simulation tool, CASiNO built by the authors. Examines the core concepts of systems simulation and modeling. Presents code examples to illustrate the implementation process of commonly encountered simulation tasks. Offers examples of industry-standard modeling methodology that can be applied in steps to tackle any modeling problem in practice.

Illustrates the application of mathematical and computational modeling in a variety of disciplines With an emphasis on the interdisciplinary nature of mathematical and computational modeling, Mathematical and Computational Modeling: With Applications in the Natural and Social Sciences, Engineering, and the Arts features chapters written by well-known, international experts in these fields and presents readers with a host of state-of-the-art achievements in the development of mathematical modeling and computational experiment methodology. The book is a valuable guide to the methods, ideas, and tools of applied and computational mathematics as they apply to other disciplines such as the natural and social sciences, engineering, and technology. Mathematical and Computational Modeling: With Applications in the Natural and Social Sciences, Engineering, and the Arts also features: Rigorous mathematical procedures and applications as the driving force behind mathematical innovation and discovery Numerous examples from a wide range of disciplines to emphasize the multidisciplinary application and universality of applied mathematics and mathematical modeling Original results on both fundamental theoretical and applied developments in diverse areas of human knowledge Discussions that promote interdisciplinary interactions between mathematicians, scientists, and engineers Mathematical and Computational Modeling: With Applications in the Natural and Social Sciences, Engineering, and the Arts is an ideal resource for professionals in various areas of mathematical and statistical sciences, modeling and simulation, physics, computer science, engineering, biology and chemistry, industrial, and computational engineering. The book also serves as an excellent textbook for graduate courses in mathematical modeling, applied mathematics, numerical methods, operations research, and optimization.

A practical how-to guide for more effective planningthrough multi-actor modelling Careful planning is the cornerstone of a successful initiative, and any plan, policy, or business strategy can only be successful if it has the support of different actors. These actors may beactively pursuing their own agendas, so the plan must not only offer an optimal solution to theproblem, but must also fit the needs and abilities of the actors involved. Actor and Strategy Models: Practical Applications and Step-wise Approaches provides a primer on multi-actormodelling, based on the fundamental premise that actor strategies are explained by investigatingwhat actors can do, think, and want to achieve. Covering a variety of models with detailed background and case examples, this book focuses on practical application. Step-by-step instructions for each approach provide immediately actionable insight, while a general framework for actor and strategy modelling allows the reader to tailor any approach as needed to optimize results in terms of situation-specific planning. Oriented toward real-world strategy, this helpful resource: • Provides models that shed light on the multi-actor dimensions of planning, using a variety of analytical approaches • Includes literature, theoretical underpinnings, and applications for each method covered • Clarifies the similarities, differences, and suitable applications between various actor modelling approaches • Provides a step-wise framework for actor and strategy modelling • Offers guidance for the identification, structuring, and measuring of values and perceptions • Examines the challenges involved in analyzing actors and strategies Even before planning begins, an endeavor’s success depends upon a clear understanding of the various actors involved in the planning and implementation stages. From game theory and argumentative analysis, through social network analysis, cognitive mapping, and beyond,Actor and Strategy Models provides valuable insight for more effective planning. Leon M. Hermans is an assistant professor at the Faculty of Technology, Policy, and Management at Delft University of Technology. His research focuses on the use of actor analysis methods to support public policy analysis and evaluation. Scott W. Cunningham is an associate professor at the Faculty of Technology, Policy, and Management at Delft University of Technology. He combines work in actor modelling and game theory with research in data mining, technology forecasting, and innovation.

The golden standard evaluation reference text Now in its second edition, Evaluation Theory, Models, and Applications is the vital text on evaluation models, perfect for classroom use as a textbook, and as a professional evaluation reference. The book begins with an overview of the evaluation field and program evaluation standards, and proceeds to cover the most widely used evaluation approaches. With new evaluation designs and the inclusion of the latest literature from the field, this Second Edition is an essential update for professionals and students who want to stay current. Understanding and choosing evaluation approaches is critical to many professions, and Evaluation Theory, Models, and Applications, Second Edition is the benchmark evaluation guide. Authors Daniel L. Stufflebeam and Chris L. S. Coryn, widely considered experts in the evaluation field, introduce and describe 23 program evaluation approaches, including, new to this edition, transformative evaluation, participatory evaluation, consumer feedback, and meta-analysis. Evaluation Theory, Models, and Applications, Second Edition facilitates the process of planning, conducting, and assessing program evaluations. The highlighted evaluation approaches include: Experimental and quasi-experimental design evaluations Daniel L. Stufflebeam's CIPP Model Michael Scriven's Consumer-Oriented Evaluation Michael Patton's Utilization-Focused Evaluation Robert Stake's Responsive/Stakeholder-Centered Evaluation Case Study Evaluation Key readings listed at the end of each chapter direct readers to the most important references for each topic. Learning objectives, review questions, student exercises, and instructor support materials complete the collection of tools. Choosing from evaluation approaches can be an overwhelming process, but Evaluation Theory, Models, and Applications, Second Edition updates the core evaluation concepts with the latest research, making this complex field accessible in just one book.

The appropriate, defensible way to prepare and present business valuations, with a strong emphasis on applications and models Financial Valuation provides an all-encompassing valuation tome that presents the application of financial valuation theory in an easily understood manner. Delivering valuation theory, the consensus view on application, and the tools to make it happen, James Hitchner?s all-star cast of contributors offer numerous examples, checklists, and models to assist in navigating a valuation project. The book contains hundreds of short, easily understandable «Valuation Tips,» and covers best practices from the view of these twenty-five experts.

The recent financial crisis has highlighted the need for better valuation models and risk management procedures, better understanding of structured products, and has called into question the actions of many financial institutions. It has become commonplace to blame the inadequacy of credit risk models, claiming that the crisis was due to sophisticated and obscure products being traded, but practitioners have for a long time been aware of the dangers and limitations of credit models. It would seem that a lack of understanding of these models is the root cause of their failures but until now little analysis had been published on the subject and, when published, it had gained very limited attention. Credit Models and the Crisis is a succinct but technical analysis of the key aspects of the credit derivatives modeling problems, tracing the development (and flaws) of new quantitative methods for credit derivatives and CDOs up to and through the credit crisis. Responding to the immediate need for clarity in the market and academic research environments, this book follows the development of credit derivatives and CDOs at a technical level, analyzing the impact, strengths and weaknesses of methods ranging from the introduction of the Gaussian Copula model and the related implied correlations to the introduction of arbitrage-free dynamic loss models capable of calibrating all the tranches for all the maturities at the same time. It also illustrates the implied copula, a method that can consistently account for CDOs with different attachment and detachment points but not for different maturities, and explains why the Gaussian Copula model is still used in its base correlation formulation. The book reports both alarming pre-crisis research and market examples, as well as commentary through history, using data up to the end of 2009, making it an important addition to modern derivatives literature. With banks and regulators struggling to fully analyze at a technical level, many of the flaws in modern financial models, it will be indispensable for quantitative practitioners and academics who want to develop stable and functional models in the future.

A powerful, unified approach to mathematical and computational modeling in science and engineering Mathematical and computational modeling makes it possible to predict the behavior of a broad range of systems across a broad range of disciplines. This text guides students and professionals through the axiomatic approach, a powerful method that will enable them to easily master the principle types of mathematical and computational models used in engineering and science. Readers will discover that this axiomatic approach not only enables them to systematically construct effective models, it also enables them to apply these models to any macroscopic physical system. Mathematical Modeling in Science and Engineering focuses on models in which the processes to be modeled are expressed as systems of partial differential equations. It begins with an introductory discussion of the axiomatic formulation of basic models, setting the foundation for further topics such as: Mechanics of classical and non-classical continuous systems Solute transport by a free fluid Flow of a fluid in a porous medium Multiphase systems Enhanced oil recovery Fluid mechanics Throughout the text, diagrams are provided to help readers visualize and better understand complex mathematical concepts. A set of exercises at the end of each chapter enables readers to put their new modeling skills into practice. There is also a bibliography in each chapter to facilitate further investigation of individual topics. Mathematical Modeling in Science and Engineering is ideal for both students and professionals across the many disciplines of science and engineering that depend on mathematical and computational modeling to predict and understand complex systems.

Latent Variable Models and Factor Analysis provides a comprehensive and unified approach to factor analysis and latent variable modeling from a statistical perspective. This book presents a general framework to enable the derivation of the commonly used models, along with updated numerical examples. Nature and interpretation of a latent variable is also introduced along with related techniques for investigating dependency. This book: Provides a unified approach showing how such apparently diverse methods as Latent Class Analysis and Factor Analysis are actually members of the same family. Presents new material on ordered manifest variables, MCMC methods, non-linear models as well as a new chapter on related techniques for investigating dependency. Includes new sections on structural equation models (SEM) and Markov Chain Monte Carlo methods for parameter estimation, along with new illustrative examples. Looks at recent developments on goodness-of-fit test statistics and on non-linear models and models with mixed latent variables, both categorical and continuous. No prior acquaintance with latent variable modelling is pre-supposed but a broad understanding of statistical theory will make it easier to see the approach in its proper perspective. Applied statisticians, psychometricians, medical statisticians, biostatisticians, economists and social science researchers will benefit from this book.

A clear and comprehensive guide to financial modeling and valuation with extensive case studies and practice exercises Corporate and Project Finance Modeling takes a clear, coherent approach to a complex and technical topic. Written by a globally-recognized financial and economic consultant, this book provides a thorough explanation of financial modeling and analysis while describing the practical application of newly-developed techniques. Theoretical discussion, case studies and step-by-step guides allow readers to master many difficult modeling problems and also explain how to build highly structured models from the ground up. The companion website includes downloadable examples, templates, and hundreds of exercises that allow readers to immediately apply the complex ideas discussed. Financial valuation is an in-depth process, involving both objective and subjective parameters. Precise modeling is critical, and thorough, accurate analysis is what bridges the gap from model to value. This book allows readers to gain a true mastery of the principles underlying financial modeling and valuation by helping them to: Develop flexible and accurate valuation analysis incorporating cash flow waterfalls, depreciation and retirements, updates for new historic periods, and dynamic presentation of scenario and sensitivity analysis; Build customized spreadsheet functions that solve circular logic arising in project and corporate valuation without cumbersome copy and paste macros; Derive accurate measures of normalized cash flow and implied valuation multiples that account for asset life, changing growth, taxes, varying returns and cost of capital; Incorporate stochastic analysis with alternative time series equations and Monte Carlo simulation without add-ins; Understand valuation effects of debt sizing, sculpting, project funding, re-financing, holding periods and credit enhancements. Corporate and Project Finance Modeling provides comprehensive guidance and extensive explanation, making it essential reading for anyone in the field.