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Monte Carlo Simulation With Applications To Finance


Monte Carlo Simulation With Applications To Finance
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Monte Carlo Simulation With Applications To Finance


Monte Carlo Simulation With Applications To Finance
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Author : Hui Wang
language : en
Publisher: CRC Press
Release Date : 2012-05-22

Monte Carlo Simulation With Applications To Finance written by Hui Wang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-22 with Business & Economics categories.


Developed from the author's course on Monte Carlo simulation at Brown University, this text provides a self-contained introduction to Monte Carlo methods in financial engineering. It covers common variance reduction techniques, the cross-entropy method, and the simulation of diffusion process models. Requiring minimal background in mathematics and finance, the book includes numerous examples of option pricing, risk analysis, and sensitivity analysis as well as many hand-and-paper and MATLAB coding exercises at the end of every chapter.



Handbook In Monte Carlo Simulation


Handbook In Monte Carlo Simulation
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Author : Paolo Brandimarte
language : en
Publisher: John Wiley & Sons
Release Date : 2014-06-20

Handbook In Monte Carlo Simulation written by Paolo Brandimarte and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-20 with Business & Economics categories.


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.



Stochastic Simulation And Applications In Finance With Matlab Programs


Stochastic Simulation And Applications In Finance With Matlab Programs
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Author : Huu Tue Huynh
language : en
Publisher: John Wiley & Sons
Release Date : 2011-11-21

Stochastic Simulation And Applications In Finance With Matlab Programs written by Huu Tue Huynh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-21 with Business & Economics categories.


Stochastic Simulation and Applications in Finance with MATLAB Programs explains the fundamentals of Monte Carlo simulation techniques, their use in the numerical resolution of stochastic differential equations and their current applications in finance. Building on an integrated approach, it provides a pedagogical treatment of the need-to-know materials in risk management and financial engineering. The book takes readers through the basic concepts, covering the most recent research and problems in the area, including: the quadratic re-sampling technique, the Least Squared Method, the dynamic programming and Stratified State Aggregation technique to price American options, the extreme value simulation technique to price exotic options and the retrieval of volatility method to estimate Greeks. The authors also present modern term structure of interest rate models and pricing swaptions with the BGM market model, and give a full explanation of corporate securities valuation and credit risk based on the structural approach of Merton. Case studies on financial guarantees illustrate how to implement the simulation techniques in pricing and hedging. NOTE TO READER: The CD has been converted to URL. Go to the following website www.wiley.com/go/huyhnstochastic which provides MATLAB programs for the practical examples and case studies, which will give the reader confidence in using and adapting specific ways to solve problems involving stochastic processes in finance.



Monte Carlo Methods In Financial Engineering


Monte Carlo Methods In Financial Engineering
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Author : Paul Glasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Monte Carlo Methods In Financial Engineering written by Paul Glasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.


Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios. The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential. The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry. Mathematical Reviews, 2004: "... this book is very comprehensive, up-to-date and useful tool for those who are interested in implementing Monte Carlo methods in a financial context."



Monte Carlo Methods And Models In Finance And Insurance


Monte Carlo Methods And Models In Finance And Insurance
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Author : Ralf Korn
language : en
Publisher: CRC Press
Release Date : 2010-02-26

Monte Carlo Methods And Models In Finance And Insurance written by Ralf Korn and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-26 with Business & Economics categories.


Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Rom



Simulation And Monte Carlo


Simulation And Monte Carlo
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Author : J. S. Dagpunar
language : en
Publisher: Wiley
Release Date : 2007-03-12

Simulation And Monte Carlo written by J. S. Dagpunar and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-12 with Mathematics categories.


Simulation and Monte Carlo is aimed at students studying for degrees in Mathematics, Statistics, Financial Mathematics, Operational Research, Computer Science, and allied subjects, who wish an up-to-date account of the theory and practice of Simulation. Its distinguishing features are in-depth accounts of the theory of Simulation, including the important topic of variance reduction techniques, together with illustrative applications in Financial Mathematics, Markov chain Monte Carlo, and Discrete Event Simulation. Each chapter contains a good selection of exercises and solutions with an accompanying appendix comprising a Maple worksheet containing simulation procedures. The worksheets can also be downloaded from the web site supporting the book. This encourages readers to adopt a hands-on approach in the effective design of simulation experiments. Arising from a course taught at Edinburgh University over several years, the book will also appeal to practitioners working in the finance industry, statistics and operations research.



Numerical Probability


Numerical Probability
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Author : Gilles Pagès
language : en
Publisher: Springer
Release Date : 2018-07-31

Numerical Probability written by Gilles Pagès and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with Mathematics categories.


This textbook provides a self-contained introduction to numerical methods in probability with a focus on applications to finance. Topics covered include the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation, and more recent developments such as the multilevel paradigm), stochastic optimization and approximation, discretization schemes of stochastic differential equations, as well as optimal quantization methods. The author further presents detailed applications to numerical aspects of pricing and hedging of financial derivatives, risk measures (such as value-at-risk and conditional value-at-risk), implicitation of parameters, and calibration. Aimed at graduate students and advanced undergraduate students, this book contains useful examples and over 150 exercises, making it suitable for self-study.



Simulation In Computational Finance And Economics Tools And Emerging Applications


Simulation In Computational Finance And Economics Tools And Emerging Applications
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Author : Alexandrova-Kabadjova, Biliana
language : en
Publisher: IGI Global
Release Date : 2012-08-31

Simulation In Computational Finance And Economics Tools And Emerging Applications written by Alexandrova-Kabadjova, Biliana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-31 with Business & Economics categories.


Simulation has become a tool difficult to substitute in many scientific areas like manufacturing, medicine, telecommunications, games, etc. Finance is one of such areas where simulation is a commonly used tool; for example, we can find Monte Carlo simulation in many financial applications like market risk analysis, portfolio optimization, credit risk related applications, etc. Simulation in Computational Finance and Economics: Tools and Emerging Applications presents a thorough collection of works, covering several rich and highly productive areas of research including Risk Management, Agent-Based Simulation, and Payment Methods and Systems, topics that have found new motivations after the strong recession experienced in the last few years. Despite the fact that simulation is widely accepted as a prominent tool, dealing with a simulation-based project requires specific management abilities of the researchers. Economic researchers will find an excellent reference to introduce them to the computational simulation models. The works presented in this book can be used as an inspiration for economic researchers interested in creating their own computational models in their respective fields.



Monte Carlo Simulation And Finance


Monte Carlo Simulation And Finance
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Author : Don L. McLeish
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-13

Monte Carlo Simulation And Finance written by Don L. McLeish and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-13 with Business & Economics categories.


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.



Advanced Simulation Based Methods For Optimal Stopping And Control


Advanced Simulation Based Methods For Optimal Stopping And Control
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Author : Denis Belomestny
language : en
Publisher: Springer
Release Date : 2018-01-31

Advanced Simulation Based Methods For Optimal Stopping And Control written by Denis Belomestny and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-31 with Business & Economics categories.


This is an advanced guide to optimal stopping and control, focusing on advanced Monte Carlo simulation and its application to finance. Written for quantitative finance practitioners and researchers in academia, the book looks at the classical simulation based algorithms before introducing some of the new, cutting edge approaches under development.