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The challenges of the current financial environment have revealed the need for a new generation of professionals who combine training in traditional finance disciplines with an understanding of sophisticated quantitative and analytical tools. Risk Management and Simulation shows how simulation modeling and analysis can help you solve risk management problems related to market, credit, operational, business, and strategic risk. Simulation models and methodologies offer an effective way to address many of these problems and are easy for finance professionals to understand and use. Drawing on the author’s extensive teaching experience, this accessible book walks you through the concepts, models, and computational techniques.How Simulation Models Can Help You Manage Risk More EffectivelyOrganized into four parts, the book begins with the concepts and framework for risk management. It then introduces the modeling and computational techniques for solving risk management problems, from model development, verification, and validation to designing simulation experiments and conducting appropriate output analysis. The third part of the book delves into specific issues of risk management in a range of risk types. These include market risk, equity risk, interest rate risk, commodity risk, currency risk, credit risk, liquidity risk, and strategic, business, and operational risks. The author also examines insurance as a mechanism for risk management and risk transfer. The final part of the book explores advanced concepts and techniques. The book contains extensive review questions and detailed quantitative or computational exercises in all chapters. Use of MATLAB® mathematical software is encouraged and suggestions for MATLAB functions are provided throughout.Learn Step by Step, from Basic Concepts to More Complex ModelsPacked with applied examples and exercises,

The challenges of the current financial environment have revealed the need for a new generation of professionals who combine training in traditional finance disciplines with an understanding of sophisticated quantitative and analytical tools. Risk Management and Simulation shows how simulation modeling and analysis can help you solve risk management problems related to market, credit, operational, business, and strategic risk. Simulation models and methodologies offer an effective way to address many of these problems and are easy for finance professionals to understand and use. Drawing on the author’s extensive teaching experience, this accessible book walks you through the concepts, models, and computational techniques.How Simulation Models Can Help You Manage Risk More EffectivelyOrganized into four parts, the book begins with the concepts and framework for risk management. It then introduces the modeling and computational techniques for solving risk management problems, from model development, verification, and validation to designing simulation experiments and conducting appropriate output analysis. The third part of the book delves into specific issues of risk management in a range of risk types. These include market risk, equity risk, interest rate risk, commodity risk, currency risk, credit risk, liquidity risk, and strategic, business, and operational risks. The author also examines insurance as a mechanism for risk management and risk transfer. The final part of the book explores advanced concepts and techniques. The book contains extensive review questions and detailed quantitative or computational exercises in all chapters. Use of MATLAB® mathematical software is encouraged and suggestions for MATLAB functions are provided throughout.Learn Step by Step, from Basic Concepts to More Complex ModelsPacked with applied examples and exercises,

Planet Management is a study of, and contribution to, the history of "globality"--the emergence of a complex organization of politics, economics, and culture at a planetary rather than a national level. Drawing on historical archival research as well as recent theoretical work in science studies and critical theory, the book tell the story of the central role of technoscientific discourses and practices in the emergence of globality.

This authoritative, comprehensive, and thoroughly up-to-date guide addresses all the important aspects of a simulation study, including modeling, simulation languages, validation, input probability distribution, and analysis of simulation output data. Full scale treatments of manufacturing systems simulation and simulation software and animation are also included along with useful and instructive case studies.

This authoritative, comprehensive and thoroughly revised text is designed for a one term or two quarter course in simulation taught at the senior or graduate level. It is offered in departments of industrial engineering, business, computer science and operations research. New features include an innovative chapter on simulation of manufacturing systems and an up-to-date treatment of simulation software and animation, with definitive coverage of model validation, input probability distribution and analysis of simulation output data.

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Trading system development, with emphasis on Monte Carlo simulation, position sizing, risk management, and statistics.

This book provides a basic treatment of discrete-event simulation, one of the most widely used operations research and management science tools for dealing with system design in the presence of uncertainty. Proper collection and analysis of data, use of analytic techniques, verification and validation of models and the appropriate design of simulation experiments are treated extensively. Readily understandable to those having a basic familiarity with differential and integral calculus, probability theory and elementary statistics. Includes simulation in C++, the latest versions of the most widely used packages, and features of simulation output analysis software. Covers properties, modeling and random-variate generation from the lognormal distribution. Clarifies the difficult distinctions between terminating and steady-state simulation, and between within- and across-replication statistics. Contains up-to-date treatment of simulation of manufacturing and material handling systems. Emphasizes the hierarchical nature of computing systems, and how simulation techniques vary, depending on the level of abstraction. For readers wanting to learn more about system simulation.

Discrete Event System Simulation is ideal for junior- and senior-level simulation courses in engineering, business, or computer science. It is also a  useful reference for professionals in operations research, management science, industrial engineering, and information science. While most books on simulation focus on particular software tools, Discrete Event System Simulation examines the principles of modeling and analysis that translate to all such tools. This language-independent text explains the basic aspects of the technology, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks. Students and instructors will find a variety of resources at the associated website, www.bcnn.net/, including simulation source code for download, additional exercises and solutions, web links and errata.

Discrete Event System Simulation is ideal for junior- and senior-level simulation courses in engineering, business, or computer science. It is also a  useful reference for professionals in operations research, management science, industrial engineering, and information science. While most books on simulation focus on particular software tools, Discrete Event System Simulation examines the principles of modeling and analysis that translate to all such tools. This language-independent text explains the basic aspects of the technology, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks. Students and instructors will find a variety of resources at the associated website, www.bcnn.net/, including simulation source code for download, additional exercises and solutions, web links and errata.

This book concentrates on the accuracy of risk modelling rather than the management of risk analysis. It provides a comprehensive guide to modelling of uncertainty using spreadsheets and Monte Carlo software on standard PCs. It includes sufficient probability and statistics theory and provides the basic information necessary for a simple risk analysis model.

Most textbooks on business process management focus on either the nuts and bolts of computer simulation or the managerial aspects of business processes. Covering both technical and managerial aspects of business process management, Business Process Modeling, Simulation and Design, Second Edition presents the tools to design effective business processes and the management techniques to operate them efficiently. New to the Second Edition Three completely revised chapters that incorporate ExtendSim 8 An introduction to simulation A chapter on business process analytics Developed from the authors’ many years of teaching process design and simulation courses, the text provides students with a thorough understanding of numerous analytical tools that can be used to model, analyze, design, manage, and improve business processes. It covers a wide range of approaches, including discrete event simulation, graphical flowcharting tools, deterministic models for cycle time analysis and capacity decisions, analytical queuing methods, and data mining. Unlike other operations management books, this one emphasizes user-friendly simulation software as well as business processes, rather than only manufacturing processes or general operations management problems. Taking an analytical modeling approach to process design, this book illustrates the power of simulation modeling as a vehicle for analyzing and designing business processes. It teaches how to apply process simulation and discusses the managerial implications of redesigning processes. The ExtendSim software is available online and ancillaries are available for instructors.

The changes in financial markets and regulatory environment following the financial crisis created many new analytics requirements. These requirements include those for computing CVA. In addition, advanced limit management based on potential future exposure (PFE) has taken an increased role following the crisis. Calculation of PFE-based limits also requires simulation of portfolio to maturity in either risk neutral or real measure. Other important requirements include modelling funding (FVA), collateral needs and cheapest to deliver collateral, and projection of portfolio cashflows for liquidity management. Previously many of these calculations were only performed by the largest sell side firms. Now, most of them are also required by small and medium banks, as well as asset managers and corporates. These new requirements can only be met by performing path consistent Monte Carlo simulation of portfolios involving a large number of risk factors over long time horizon (up to and exceeding 30 years). Written by industry expert Alexander Sokol, this is the first book to focus specifically on model construction and calibration for long-term portfolio simulation. The book offers insider knowledge and techniques for the unique modelling methodologies required in simulating entire portfolios. The book will address the following topics for multiple asset classes, including interest rate, cross currency and hybrid, CDS and credit products, and structured products: - Methodology fundamentals - Risk neutral models - Real world models - Margin period of risk - General wrong way risk - Systemic wrong way risk - Cashflow aggregation - American Monte Carlo - CVA and funding - Collateral optimisation - Liquidity and PFE-based limits - Regulatory capital Long-Term Portfolio Simulation is a comprehensive reference for quants responsible for building models for CVA, PFE, limits, liquidity, or funding, as well as those auditing and reviewing the models.

This book provides a basic treatment of discrete-event simulation, one of the most widely used operations research and management science tools for dealing with system design in the presence of uncertainty. Proper collection and analysis of data, use of analytic techniques, verification and validation of models and the appropriate design of simulation experiments are treated extensively. Readily understandable to those having a basic familiarity with differential and integral calculus, probability theory and elementary statistics. Includes simulation in C++, the latest versions of the most widely used packages, and features of simulation output analysis software. Covers properties, modeling and random-variate generation from the lognormal distribution. Clarifies the difficult distinctions between terminating and steady-state simulation, and between within- and across-replication statistics. Contains up-to-date treatment of simulation of manufacturing and material handling systems. Emphasizes the hierarchical nature of computing systems, and how simulation techniques vary, depending on the level of abstraction. For readers wanting to learn more about system simulation.

Most textbooks on business process management focus on either the nuts and bolts of computer simulation or the managerial aspects of business processes. Covering both technical and managerial aspects of business process management, Business Process Modeling, Simulation and Design, Second Edition presents the tools to design effective business processes and the management techniques to operate them efficiently. New to the Second Edition Three completely revised chapters that incorporate ExtendSim 8 An introduction to simulation A chapter on business process analytics Developed from the authors’ many years of teaching process design and simulation courses, the text provides students with a thorough understanding of numerous analytical tools that can be used to model, analyze, design, manage, and improve business processes. It covers a wide range of approaches, including discrete event simulation, graphical flowcharting tools, deterministic models for cycle time analysis and capacity decisions, analytical queuing methods, and data mining. Unlike other operations management books, this one emphasizes user-friendly simulation software as well as business processes, rather than only manufacturing processes or general operations management problems. Taking an analytical modeling approach to process design, this book illustrates the power of simulation modeling as a vehicle for analyzing and designing business processes. It teaches how to apply process simulation and discusses the managerial implications of redesigning processes. The ExtendSim software is available online and ancillaries are available for instructors.

This book concentrates on the accuracy of risk modelling rather than the management of risk analysis. It provides a comprehensive guide to modelling of uncertainty using spreadsheets and Monte Carlo software on standard PCs. It includes sufficient probability and statistics theory and provides the basic information necessary for a simple risk analysis model.

Now you can master the core concepts in marketing management that you need as a undergraduate marketing major, first-year MBA or EMBA student with the detailed material in Iacobucci's MARKETING MANAGEMENT, 5E. You are able to immediately apply the key concepts you learn to cases, group work, or simulations that are assigned in your course. MARKETING MANAGEMENT, 5E reflects the dynamic environment facing today's marketers. Engaging explanations, timely cases and memorable examples help you understand how an increasingly competitive global marketplace and current changes in technology affect the marketing decisions that today's managers must make every day.

Get straight to the heart of important strategic management concepts. This brief text offers a concise explanation of the most important concepts and techniques in strategic management. Further, cases and simulations are a perfect supplement to Essentials of Strategic Management, while its brevity also makes it suitable for use in corporate and executive training programs. This edition contains new information to reflect the latest changes in the discipline while remaining brief and to the point.

For the MBA Marketing Management course and/or undergraduate capstone marketing strategy course.     Framework for Marketing Management provides authoritative marketing theory in a concise format to provide flexibility where outside cases, simulations, and projects are brought in.

This book represents a departure from existing textbooks. Rather than covering methodology, the book introduces decision support systems through real world applications, and uses spreadsheets to model and solve problems. It uses management science techniques (statistics, simulation, probabilistic modeling and optimization), but only as tools to facilitate problem solving. The book embraces George Dantzig's dictum as its premise: "The final test of any theory is its capacity to solve the problems which originated it." The book is used in the core MBA program at MIT's Sloan School of Management for the class titled: "Data, Models and Decisions". It is used in over ten universities in both core and elective classes, including Stanford University, Chicago's graduate school of Business, Babson College, among several others. The book contains many real business cases from the authors' consulting experience. Instructor resources are available for faculty who have adopted the book for their course by contacting the authors directly @ dbertsim@mit.edu, rfreund@mit.edu )