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Making Monte Carlo

Making Monte Carlo
Author: Mark Braude
Publisher: Simon and Schuster
Total Pages: 304
Release: 2017-04-25
Genre: Business & Economics
ISBN: 147670970X

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"A rollicking narrative history of Jazz Age Monte Carlo, chronicling the city's rise from WWI's ashes to become one of the world's most storied, infamous playgrounds of the rich, only to be crushed under it's own weight ten years later"--Provided by publisher.


Exploring Monte Carlo Methods

Exploring Monte Carlo Methods
Author: William L. Dunn
Publisher: Elsevier
Total Pages: 594
Release: 2022-06-07
Genre: Science
ISBN: 0128197455

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Exploring Monte Carlo Methods, Second Edition provides a valuable introduction to the numerical methods that have come to be known as "Monte Carlo." This unique and trusted resource for course use, as well as researcher reference, offers accessible coverage, clear explanations and helpful examples throughout. Building from the basics, the text also includes applications in a variety of fields, such as physics, nuclear engineering, finance and investment, medical modeling and prediction, archaeology, geology and transportation planning. Provides a comprehensive yet concise treatment of Monte Carlo methods Uses the famous "Buffon’s needle problem" as a unifying theme to illustrate the many aspects of Monte Carlo methods Includes numerous exercises and useful appendices on: Certain mathematical functions, Bose Einstein functions, Fermi Dirac functions and Watson functions


Monte Carlo Methods in Financial Engineering

Monte Carlo Methods in Financial Engineering
Author: Paul Glasserman
Publisher: Springer Science & Business Media
Total Pages: 603
Release: 2013-03-09
Genre: Mathematics
ISBN: 0387216170

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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


A Guide to Monte Carlo Simulations in Statistical Physics

A Guide to Monte Carlo Simulations in Statistical Physics
Author: David P. Landau
Publisher: Cambridge University Press
Total Pages: 402
Release: 2000-08-17
Genre: Mathematics
ISBN: 9780521653664

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This book describes all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, as well as in related fields, such as polymer science and lattice gauge theory. The authors give a succinct overview of simple sampling methods and develop the importance sampling method. In addition they introduce quantum Monte Carlo methods, aspects of simulations of growth phenomena and other systems far from equilibrium, and the Monte Carlo Renormalization Group approach to critical phenomena. The book includes many applications, examples, and current references, and exercises to help the reader.


Introducing Monte Carlo Methods with R

Introducing Monte Carlo Methods with R
Author: Christian Robert
Publisher: Springer Science & Business Media
Total Pages: 297
Release: 2010
Genre: Computers
ISBN: 1441915753

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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.


Explorations in Monte Carlo Methods

Explorations in Monte Carlo Methods
Author: Ronald W. Shonkwiler
Publisher: Springer Science & Business Media
Total Pages: 249
Release: 2009-08-11
Genre: Mathematics
ISBN: 0387878378

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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.


Monte Carlo Methods in Finance

Monte Carlo Methods in Finance
Author: Peter Jäckel
Publisher: John Wiley & Sons
Total Pages: 245
Release: 2002-04-03
Genre: Business & Economics
ISBN: 047149741X

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An invaluable resource for quantitative analysts who need to run models that assist in option pricing and risk management. This concise, practical hands on guide to Monte Carlo simulation introduces standard and advanced methods to the increasing complexity of derivatives portfolios. Ranging from pricing more complex derivatives, such as American and Asian options, to measuring Value at Risk, or modelling complex market dynamics, simulation is the only method general enough to capture the complexity and Monte Carlo simulation is the best pricing and risk management method available. The book is packed with numerous examples using real world data and is supplied with a CD to aid in the use of the examples.


Forecasting in Mathematics

Forecasting in Mathematics
Author: Abdo Abou Jaoude
Publisher: BoD – Books on Demand
Total Pages: 156
Release: 2021-01-27
Genre: Computers
ISBN: 1838808256

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Mathematical probability and statistics are an attractive, thriving, and respectable part of mathematics. Some mathematicians and philosophers of science say they are the gateway to mathematics’ deepest mysteries. Moreover, mathematical statistics denotes an accumulation of mathematical discussions connected with efforts to most efficiently collect and use numerical data subject to random or deterministic variations. Currently, the concept of probability and mathematical statistics has become one of the fundamental notions of modern science and the philosophy of nature. This book is an illustration of the use of mathematics to solve specific problems in engineering, statistics, and science in general.


Dealmaking

Dealmaking
Author: Richard Razgaitis
Publisher: John Wiley & Sons
Total Pages: 308
Release: 2004-04-16
Genre: Law
ISBN: 0471452017

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Applying practical tools to the volatile process of negotiating Prognosticators apply Monte Carlo Analysis (MCA) to determine the likelihood and significance of a complete range of future outcomes; Real Options Analysis (ROA) can then be employed to develop pricing structures, or options, for such outcomes. Richard Razgaitis' Dealmaking shows readers how to apply these powerful valuation tools to a variety of business processes, such as pricing, negotiating, or living with a "deal," be it a technology license, and R&D partnership, or an outright sales agreement. Dealmaking distinguishes itself from other negotiating guides not only by treating negotiations as an increasingly common situation, but also by presenting a tool-based approach that creates flexible, practical valuation models. This forward-thinking guide includes a variety of checklists, case studies, and a CD-ROM with the appropriate software. Richard Razgaitis (Bloomsbury, NJ) is a Managing Director at InteCap, Inc. He has over twenty-five years of experience working with the development, commercialization, and strategic management of technology, seventeen of which have been spent in the commercialization of intellectual property.


Monte Carlo Simulation and Resampling Methods for Social Science

Monte Carlo Simulation and Resampling Methods for Social Science
Author: Thomas M. Carsey
Publisher: SAGE Publications
Total Pages: 304
Release: 2013-08-05
Genre: Social Science
ISBN: 1483324923

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Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.