Essentials of Monte Carlo Simulation

Statistical Methods for Building Simulation Models

Author: Nick T. Thomopoulos

Publisher: Springer Science & Business Media

ISBN: 1461460220

Category: Mathematics

Page: 174

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Essentials of Monte Carlo Simulation focuses on the fundamentals of Monte Carlo methods using basic computer simulation techniques. The theories presented in this text deal with systems that are too complex to solve analytically. As a result, readers are given a system of interest and constructs using computer code, as well as algorithmic models to emulate how the system works internally. After the models are run several times, in a random sample way, the data for each output variable(s) of interest is analyzed by ordinary statistical methods. This book features 11 comprehensive chapters, and discusses such key topics as random number generators, multivariate random variates, and continuous random variates. Over 100 numerical examples are presented as part of the appendix to illustrate useful real world applications. The text also contains an easy to read presentation with minimal use of difficult mathematical concepts. Very little has been published in the area of computer Monte Carlo simulation methods, and this book will appeal to students and researchers in the fields of Mathematics and Statistics.

Die Monte-Carlo-Methode

Beispiele unter Excel VBA

Author: Harald Nahrstedt

Publisher: Springer-Verlag

ISBN: 3658101490

Category: Mathematics

Page: 45

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Harald Nahrstedt zeigt hier den pragmatisch technischen und weniger den wissenschaftlichen Ansatz, wie Excel mit seinen Programmiermöglichkeiten sich immer mehr zu einem universellen Arbeitsmittel entwickelt. So ist die Simulation mit Hilfe von Pseudozufallszahlen ein schneller und preiswerter Weg zu fachlichen Aussagen. Den Rahmen dieser Abhandlung bildet der geschichtliche Hintergrund.

Monte Carlo Methods in Financial Engineering

Author: Paul Glasserman

Publisher: Springer Science & Business Media

ISBN: 0387216170

Category: Mathematics

Page: 596

View: 2081

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From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis

Reliability Assessment of Electric Power Systems Using Monte Carlo Methods

Author: Billinton,W. Li

Publisher: Springer Science & Business Media

ISBN: 9780306447815

Category: Technology & Engineering

Page: 352

View: 4506

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The application of quantitative reliability evaluation in electric power sys tems has now evolved to the point at which most utilities use these techniques in one or more areas of their planning, design, and operation. Most of the techniques in use are based on analytical models and resulting analytical evaluation procedures. Improvements in and availability of high-speed digi tal computers have created the opportunity to analyze many of these prob lems using stochastic simulation methods and over the last decade there has been increased interest in and use made of Monte Carlo simulation in quantitative power system reliability assessment. Monte Carlo simulation is not a new concept and recorded applications have existed for at least 50 yr. However, localized high-speed computers with large-capacity storage have made Monte Carlo simulation an available and sometimes preferable option for many power system reliability applications. Monte Carlo simulation is also an integral part of a modern undergrad uate or graduate course on reliability evaluation of general engineering systems or specialized areas such as electric power systems. It is hoped that this textbook will help formalize the many existing applications of Monte Carlo simulation and assist in their integration in teaching programs. This book presents the basic concepts associated with Monte Carlo simulation.

Monte Carlo Simulation and Finance

Author: Don L. McLeish

Publisher: John Wiley & Sons

ISBN: 1118160940

Category: Business & Economics

Page: 387

View: 5035

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Monte Carlo methods have been used for decades in physics, engineering, statistics, and other fields. Monte Carlo Simulation and Finance explains the nuts and bolts of this essential technique used to value derivatives and other securities. Author and educator Don McLeish examines this fundamental process, and discusses important issues, including specialized problems in finance that Monte Carlo and Quasi-Monte Carlo methods can help solve and the different ways Monte Carlo methods can be improved upon. This state-of-the-art book on Monte Carlo simulation methods is ideal for finance professionals and students. Order your copy today.

Modeling Risk, + DVD

Applying Monte Carlo Risk Simulation, Strategic Real Options, Stochastic Forecasting, and Portfolio Optimization

Author: Johnathan Mun

Publisher: John Wiley & Sons

ISBN: 0470620013

Category: Business & Economics

Page: 976

View: 4131

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An updated guide to risk analysis and modeling Although risk was once seen as something that was both unpredictable and uncontrollable, the evolution of risk analysis tools and theories has changed the way we look at this important business element. In the Second Edition of Analyzing and Modeling Risk, expert Dr. Johnathan Mun provides up-to-date coverage of risk analysis as it is applied within the realms of business risk analysis and offers an intuitive feel of what risk looks like, as well as the different ways of quantifying it. This Second Edition provides professionals in all industries a more comprehensive guide on such key concepts as risk and return, the fundamentals of model building, Monte Carlo simulation, forecasting, time-series and regression analysis, optimization, real options, and more. Includes new examples, questions, and exercises as well as updates using Excel 2007 Book supported by author's proprietary risk analysis software found on the companion CD-ROM Offers both a qualitative and quantitative description of risk Filled with in-depth insights and practical advice, this reliable resource covers all of the essential tools and techniques that risk managers need to successfully conduct risk analysis. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

A Guide to Monte Carlo Simulations in Statistical Physics

Author: David P. Landau,Kurt Binder

Publisher: Cambridge University Press

ISBN: 1316062635

Category: Science

Page: N.A

View: 9801

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Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. This fourth edition contains extensive new material describing numerous powerful algorithms not covered in previous editions, in some cases representing new developments that have only recently appeared. Older methodologies whose impact was previously unclear or unappreciated are also introduced, in addition to many small revisions that bring the text and cited literature up to date. This edition also introduces the use of petascale computing facilities in the Monte Carlo arena. Throughout the book there are many applications, examples, recipes, case studies, and exercises to help the reader understand the material. It is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.

Simulation Modeling and Analysis with ARENA

Author: Tayfur Altiok,Benjamin Melamed

Publisher: Elsevier

ISBN: 9780080548951

Category: Computers

Page: 456

View: 4886

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Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment. It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings. · Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems · Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems · Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling * Ample end-of-chapter problems and full Solutions Manual * Includes CD with sample ARENA modeling programs

Essentials of Electronic Testing for Digital, Memory and Mixed-Signal VLSI Circuits

Author: M. Bushnell,Vishwani Agrawal

Publisher: Springer Science & Business Media

ISBN: 9780792379911

Category: Technology & Engineering

Page: 690

View: 7238

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The modern electronic testing has a forty year history. Test professionals hold some fairly large conferences and numerous workshops, have a journal, and there are over one hundred books on testing. Still, a full course on testing is offered only at a few universities, mostly by professors who have a research interest in this area. Apparently, most professors would not have taken a course on electronic testing when they were students. Other than the computer engineering curriculum being too crowded, the major reason cited for the absence of a course on electronic testing is the lack of a suitable textbook. For VLSI the foundation was provided by semiconductor device techn- ogy, circuit design, and electronic testing. In a computer engineering curriculum, therefore, it is necessary that foundations should be taught before applications. The field of VLSI has expanded to systems-on-a-chip, which include digital, memory, and mixed-signalsubsystems. To our knowledge this is the first textbook to cover all three types of electronic circuits. We have written this textbook for an undergraduate “foundations” course on electronic testing. Obviously, it is too voluminous for a one-semester course and a teacher will have to select from the topics. We did not restrict such freedom because the selection may depend upon the individual expertise and interests. Besides, there is merit in having a larger book that will retain its usefulness for the owner even after the completion of the course. With equal tenacity, we address the needs of three other groups of readers.

Financial Modeling with Crystal Ball and Excel

Author: John Charnes

Publisher: John Wiley & Sons

ISBN: 1118240057

Category: Business & Economics

Page: 336

View: 8158

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Updated look at financial modeling and Monte Carlo simulationwith software by Oracle Crystal Ball This revised and updated edition of the bestselling book onfinancial modeling provides the tools and techniques needed toperform spreadsheet simulation. It answers the essential questionof why risk analysis is vital to the decision-making process, forany problem posed in finance and investment. This reliable resourcereviews the basics and covers how to define and refine probabilitydistributions in financial modeling, and explores the conceptsdriving the simulation modeling process. It also discussessimulation controls and analysis of simulation results. The second edition of Financial Modeling with Crystal Balland Excel contains instructions, theory, and practical examplemodels to help apply risk analysis to such areas as derivativepricing, cost estimation, portfolio allocation and optimization,credit risk, and cash flow analysis. It includes the resourcesneeded to develop essential skills in the areas of valuation,pricing, hedging, trading, risk management, project evaluation,credit risk, and portfolio management. Offers an updated edition of the bestselling book covering thenewest version of Oracle Crystal Ball Contains valuable insights on Monte Carlo simulation—anessential skill applied by many corporate finance and investmentprofessionals Written by John Charnes, the former finance department chair atthe University of Kansas and senior vice president of globalportfolio strategies at Bank of America, who is currently Presidentand Chief Data Scientist at Syntelli Solutions, Inc. Risk Analyticsand Predictive Intelligence Division (Syntelli RAPID) Engaging and informative, this book is a vital resource designedto help you become more adept at financial modeling andsimulation.

Monte Carlo Statistical Methods

Author: Christian Robert,George Casella

Publisher: Springer Science & Business Media

ISBN: 1475741456

Category: Mathematics

Page: 649

View: 6214

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We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.

Introducing Monte Carlo Methods with R

Author: Christian Robert,George Casella

Publisher: Springer Science & Business Media

ISBN: 1441915753

Category: Computers

Page: 283

View: 9912

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This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.

Monte Carlo Methods for Particle Transport

Author: Alireza Haghighat

Publisher: CRC Press

ISBN: 1466592540

Category: Mathematics

Page: 272

View: 2792

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The Monte Carlo method has become the de facto standard in radiation transport. Although powerful, if not understood and used appropriately, the method can give misleading results. Monte Carlo Methods for Particle Transport teaches appropriate use of the Monte Carlo method, explaining the method’s fundamental concepts as well as its limitations. Concise yet comprehensive, this well-organized text: Introduces the particle importance equation and its use for variance reduction Describes general and particle-transport-specific variance reduction techniques Presents particle transport eigenvalue issues and methodologies to address these issues Explores advanced formulations based on the author’s research activities Discusses parallel processing concepts and factors affecting parallel performance Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, Monte Carlo Methods for Particle Transport provides nuclear engineers and scientists with a practical guide to the application of the Monte Carlo method.

Explorations in Monte Carlo Methods

Author: Ronald W. Shonkwiler,Franklin Mendivil

Publisher: Springer Science & Business Media

ISBN: 038787836X

Category: Mathematics

Page: 243

View: 2591

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Monte Carlo methods are among the most used and useful computational tools available today, providing efficient and practical algorithims to solve a wide range of scientific and engineering problems. Applications covered in this book include optimization, finance, statistical mechanics, birth and death processes, and gambling systems. Explorations in Monte Carlo Methods provides a hands-on approach to learning this subject. Each new idea is carefully motivated by a realistic problem, thus leading from questions to theory via examples and numerical simulations. Programming exercises are integrated throughout the text as the primary vehicle for learning the material. Each chapter ends with a large collection of problems illustrating and directing the material. This book is suitable as a textbook for students of engineering and the sciences, as well as mathematics.

Reliability Assessment Using Stochastic Finite Element Analysis

Author: Achintya Haldar,Sankaran Mahadevan

Publisher: John Wiley & Sons

ISBN: 9780471369615

Category: Mathematics

Page: 328

View: 2684

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The first complete guide to using the Stochastic Finite Element Method for reliability assessment Unlike other analytical reliability estimation techniques, the Stochastic Finite Element Method (SFEM) can be used for both implicit and explicit performance functions, making it a particularly powerful and robust tool for today's engineer. This book, written by two pioneers in SFEM-based methodologies, shows how to use SFEM for the reliability analysis of a wide range of structures. It begins by reviewing essential risk concepts, currently available risk evaluation procedures, and the use of analytical and sampling methods in estimating risk. Next, it introduces SFEM evaluation procedures, with detailed coverage of displacement-based and stress-based deterministic finite element approaches. Linear, nonlinear, static, and dynamic problems are considered separately to demonstrate the robustness of the methods. The risk or reliability estimation procedure for each case is presented in different chapters, with theory complemented by a useful series of examples. Integrating advanced concepts in risk-based design, finite elements, and mechanics, Reliability Assessment Using Stochastic Finite Element Analysis is vital reading for engineering professionals and students in all areas of the field.

Engineering Risk Assessment with Subset Simulation

Author: Siu-Kui Au,Yu Wang

Publisher: John Wiley & Sons

ISBN: 1118398076

Category: Technology & Engineering

Page: 336

View: 7896

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This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and stochastic processes for some common distributions encountered in engineering applications. It then introduces a class of powerful simulation techniques called Markov Chain Monte Carlo method (MCMC), an important machinery behind Subset Simulation that allows one to generate samples for investigating rare scenarios in a probabilistically consistent manner. The theory of Subset Simulation is then presented, addressing related practical issues encountered in the actual implementation. The book also introduces the reader to probabilistic failure analysis and reliability-based sensitivity analysis, which are laid out in a context that can be efficiently tackled with Subset Simulation or Monte Carlo simulation in general. The book is supplemented with an Excel VBA code that provides a user-friendly tool for the reader to gain hands-on experience with Monte Carlo simulation. Presents a powerful simulation method called Subset Simulation for efficient engineering risk assessment and failure and sensitivity analysis Illustrates examples with MS Excel spreadsheets, allowing readers to gain hands-on experience with Monte Carlo simulation Covers theoretical fundamentals as well as advanced implementation issues A companion website is available to include the developments of the software ideas This book is essential reading for graduate students, researchers and engineers interested in applying Monte Carlo methods for risk assessment and reliability based design in various fields such as civil engineering, mechanical engineering, aerospace engineering, electrical engineering and nuclear engineering. Project managers, risk managers and financial engineers dealing with uncertainty effects may also find it useful.

Quantum Monte Carlo Methods

Algorithms for Lattice Models

Author: James Gubernatis,Naoki Kawashima,Philipp Werner

Publisher: Cambridge University Press

ISBN: 1316483126

Category: Science

Page: N.A

View: 4178

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Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to provide a pedagogical overview of the field and its applications. The book provides a comprehensive introduction to the Monte Carlo method, its use, and its foundations, and examines algorithms for the simulation of quantum many-body lattice problems at finite and zero temperature. These algorithms include continuous-time loop and cluster algorithms for quantum spins, determinant methods for simulating fermions, power methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuous-time algorithms for quantum impurity models and their use within dynamical mean-field theory, along with algorithms for analytically continuing imaginary-time quantum Monte Carlo data. The parallelization of Monte Carlo simulations is also addressed. This is an essential resource for graduate students, teachers, and researchers interested in quantum Monte Carlo techniques.

Handbook in Monte Carlo Simulation

Applications in Financial Engineering, Risk Management, and Economics

Author: Paolo Brandimarte

Publisher: John Wiley & Sons

ISBN: 1118593642

Category: Business & Economics

Page: 688

View: 7340

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An accessible treatment of Monte Carlo methods, techniques, and applications in the field of finance and economics Providing readers with an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics presents a timely account of the applicationsof Monte Carlo methods in financial engineering and economics. Written by an international leading expert in thefield, the handbook illustrates the challenges confronting present-day financial practitioners and provides various applicationsof Monte Carlo techniques to answer these issues. The book is organized into five parts: introduction andmotivation; input analysis, modeling, and estimation; random variate and sample path generation; output analysisand variance reduction; and applications ranging from option pricing and risk management to optimization. The Handbook in Monte Carlo Simulation features: An introductory section for basic material on stochastic modeling and estimation aimed at readers who may need a summary or review of the essentials Carefully crafted examples in order to spot potential pitfalls and drawbacks of each approach An accessible treatment of advanced topics such as low-discrepancy sequences, stochastic optimization, dynamic programming, risk measures, and Markov chain Monte Carlo methods Numerous pieces of R code used to illustrate fundamental ideas in concrete terms and encourage experimentation The Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics is a complete reference for practitioners in the fields of finance, business, applied statistics, econometrics, and engineering, as well as a supplement for MBA and graduate-level courses on Monte Carlo methods and simulation.