Monte Carlo Frameworks PDF Download
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| Author | : Daniel J. Duffy |
| Publisher | : John Wiley & Sons |
| Total Pages | : 775 |
| Release | : 2011-08-02 |
| Genre | : Business & Economics |
| ISBN | : 0470684062 |
Download Monte Carlo Frameworks Book in PDF, ePub and Kindle
This is one of the first books that describe all the steps that are needed in order to analyze, design and implement Monte Carlo applications. It discusses the financial theory as well as the mathematical and numerical background that is needed to write flexible and efficient C++ code using state-of-the art design and system patterns, object-oriented and generic programming models in combination with standard libraries and tools. Includes a CD containing the source code for all examples. It is strongly advised that you experiment with the code by compiling it and extending it to suit your needs. Support is offered via a user forum on www.datasimfinancial.com where you can post queries and communicate with other purchasers of the book. This book is for those professionals who design and develop models in computational finance. This book assumes that you have a working knowledge of C ++.
| Author | : Paul Glasserman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 603 |
| Release | : 2013-03-09 |
| Genre | : Mathematics |
| ISBN | : 0387216170 |
Download Monte Carlo Methods in Financial Engineering Book in PDF, ePub and Kindle
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
| Author | : Christian Robert |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 297 |
| Release | : 2010 |
| Genre | : Computers |
| ISBN | : 1441915753 |
Download Introducing Monte Carlo Methods with R Book in PDF, ePub and Kindle
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.
| Author | : Peter Jäckel |
| Publisher | : John Wiley & Sons |
| Total Pages | : 245 |
| Release | : 2002-04-03 |
| Genre | : Business & Economics |
| ISBN | : 047149741X |
Download Monte Carlo Methods in Finance Book in PDF, ePub and Kindle
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.
| Author | : Bruno Dupire |
| Publisher | : |
| Total Pages | : 341 |
| Release | : 1998 |
| Genre | : Derivative securities |
| ISBN | : 9781899332915 |
Download Monte Carlo Book in PDF, ePub and Kindle
A core reference of classic research and new writing on the methodologies and applications of Monte Carlo simulation.
| Author | : Jun S. Liu |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 350 |
| Release | : 2013-11-11 |
| Genre | : Mathematics |
| ISBN | : 0387763716 |
Download Monte Carlo Strategies in Scientific Computing Book in PDF, ePub and Kindle
This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared. Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians. It can also be used as a textbook for a graduate-level course on Monte Carlo methods.
| Author | : Nicolas Chopin |
| Publisher | : Springer Nature |
| Total Pages | : 378 |
| Release | : 2020-10-01 |
| Genre | : Mathematics |
| ISBN | : 3030478459 |
Download An Introduction to Sequential Monte Carlo Book in PDF, ePub and Kindle
This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics. The coverage is comprehensive, ranging from the underlying theory to computational implementation, methodology, and diverse applications in various areas of science. This is achieved by describing SMC algorithms as particular cases of a general framework, which involves concepts such as Feynman-Kac distributions, and tools such as importance sampling and resampling. This general framework is used consistently throughout the book. Extensive coverage is provided on sequential learning (filtering, smoothing) of state-space (hidden Markov) models, as this remains an important application of SMC methods. More recent applications, such as parameter estimation of these models (through e.g. particle Markov chain Monte Carlo techniques) and the simulation of challenging probability distributions (in e.g. Bayesian inference or rare-event problems), are also discussed. The book may be used either as a graduate text on Sequential Monte Carlo methods and state-space modeling, or as a general reference work on the area. Each chapter includes a set of exercises for self-study, a comprehensive bibliography, and a “Python corner,” which discusses the practical implementation of the methods covered. In addition, the book comes with an open source Python library, which implements all the algorithms described in the book, and contains all the programs that were used to perform the numerical experiments.
| Author | : Adrian Barbu |
| Publisher | : Springer Nature |
| Total Pages | : 433 |
| Release | : 2020-02-24 |
| Genre | : Mathematics |
| ISBN | : 9811329710 |
Download Monte Carlo Methods Book in PDF, ePub and Kindle
This book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nature, the book is suitable for developing and teaching graduate courses on Monte Carlo methods. To facilitate learning, each chapter includes several representative application examples from various fields. The book pursues two main goals: (1) It introduces researchers to applying Monte Carlo methods to broader problems in areas such as Computer Vision, Computer Graphics, Machine Learning, Robotics, Artificial Intelligence, etc.; and (2) it makes it easier for scientists and engineers working in these areas to employ Monte Carlo methods to enhance their research.
| Author | : James E. Gentle |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 252 |
| Release | : 2013-03-14 |
| Genre | : Computers |
| ISBN | : 147572960X |
Download Random Number Generation and Monte Carlo Methods Book in PDF, ePub and Kindle
Monte Carlo simulation has become one of the most important tools in all fields of science. This book surveys the basic techniques and principles of the subject, as well as general techniques useful in more complicated models and in novel settings. The emphasis throughout is on practical methods that work well in current computing environments.
| Author | : A. Dubi |
| Publisher | : John Wiley & Sons |
| Total Pages | : 294 |
| Release | : 2000-01-21 |
| Genre | : Mathematics |
| ISBN | : |
Download Monte Carlo Applications in Systems Engineering Book in PDF, ePub and Kindle
Focusses on the industry and use of mathematical methods, in particular the Monte Carlo method as a tool that can support and improve the engineering of systems. The application of the Monte Carlo method to system engineering is a new concept and the Monte Carlo method allows serious mathematical treatment of real-world industrial systems. This book which includes a large number of worked examples from real industrial problems, will prove a valuable reference source for students, researchers and engineers. It presents a unified approach to time-dependent system behavior in which the Monte Carlo method serves as a tool to obtain solutions to real-world challenges. The author suggest that efficiency can be increased through this integrated approach which combines previously independent considerations such as product reliability, maintenance requirements and the availability of spare parts. Features include: * Comprehensive coverage of the basic theory behind systems engineering and the Monte Carlo method enabling the reader to understand the concepts involved * Description of the method from the basic estimation of simple statistical processes, through the evaluation of multidimensional integrals to the solution of complex transport equations * Extensive examples detailing practical industrial applications for each of the techniques presented * Accompanying software (available via ftp) relating to specific examples which allows the reader to use the methods described to solve practical problems * Discussion of a variety of analytical tools from classical probabilistic methods to the concepts of event distribution, aging and Markovian methods explaining how these fit into the general systems engineering framework.
