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Monte Carlo Methods In Financial Engineering


Monte Carlo Methods In Financial Engineering
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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."



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 : 2014-06-17

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 2014-06-17 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.



Monte Carlo Methods In Financial Engineering


Monte Carlo Methods In Financial Engineering
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Author : Paul Glasserman
language : en
Publisher:
Release Date : 2014-01-15

Monte Carlo Methods In Financial Engineering written by Paul Glasserman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.




Applications Of Monte Carlo Methods To Finance And Insurance


Applications Of Monte Carlo Methods To Finance And Insurance
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Author : Thomas N. Herzog
language : en
Publisher: ACTEX Publications
Release Date : 2002

Applications Of Monte Carlo Methods To Finance And Insurance written by Thomas N. Herzog and has been published by ACTEX Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Business & Economics categories.




Numerical Methods In Finance And Economics


Numerical Methods In Finance And Economics
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Author : Paolo Brandimarte
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-06

Numerical Methods In Finance And Economics 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 2013-06-06 with Mathematics categories.


A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance. Reflecting this development, Numerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition bridges the gap between financial theory and computational practice while showing readers how to utilize MATLAB?--the powerful numerical computing environment--for financial applications. The author provides an essential foundation in finance and numerical analysis in addition to background material for students from both engineering and economics perspectives. A wide range of topics is covered, including standard numerical analysis methods, Monte Carlo methods to simulate systems affected by significant uncertainty, and optimization methods to find an optimal set of decisions. Among this book's most outstanding features is the integration of MATLAB?, which helps students and practitioners solve relevant problems in finance, such as portfolio management and derivatives pricing. This tutorial is useful in connecting theory with practice in the application of classical numerical methods and advanced methods, while illustrating underlying algorithmic concepts in concrete terms. Newly featured in the Second Edition: * In-depth treatment of Monte Carlo methods with due attention paid to variance reduction strategies * New appendix on AMPL in order to better illustrate the optimization models in Chapters 11 and 12 * New chapter on binomial and trinomial lattices * Additional treatment of partial differential equations with two space dimensions * Expanded treatment within the chapter on financial theory to provide a more thorough background for engineers not familiar with finance * New coverage of advanced optimization methods and applications later in the text Numerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition presents basic treatments and more specialized literature, and it also uses algebraic languages, such as AMPL, to connect the pencil-and-paper statement of an optimization model with its solution by a software library. Offering computational practice in both financial engineering and economics fields, this book equips practitioners with the necessary techniques to measure and manage risk.



Finite Difference Methods In Financial Engineering


Finite Difference Methods In Financial Engineering
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Author : Daniel J. Duffy
language : en
Publisher: John Wiley & Sons
Release Date : 2013-10-28

Finite Difference Methods In Financial Engineering written by Daniel J. Duffy 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 2013-10-28 with Business & Economics categories.


The world of quantitative finance (QF) is one of the fastest growing areas of research and its practical applications to derivatives pricing problem. Since the discovery of the famous Black-Scholes equation in the 1970's we have seen a surge in the number of models for a wide range of products such as plain and exotic options, interest rate derivatives, real options and many others. Gone are the days when it was possible to price these derivatives analytically. For most problems we must resort to some kind of approximate method. In this book we employ partial differential equations (PDE) to describe a range of one-factor and multi-factor derivatives products such as plain European and American options, multi-asset options, Asian options, interest rate options and real options. PDE techniques allow us to create a framework for modeling complex and interesting derivatives products. Having defined the PDE problem we then approximate it using the Finite Difference Method (FDM). This method has been used for many application areas such as fluid dynamics, heat transfer, semiconductor simulation and astrophysics, to name just a few. In this book we apply the same techniques to pricing real-life derivative products. We use both traditional (or well-known) methods as well as a number of advanced schemes that are making their way into the QF literature: Crank-Nicolson, exponentially fitted and higher-order schemes for one-factor and multi-factor options Early exercise features and approximation using front-fixing, penalty and variational methods Modelling stochastic volatility models using Splitting methods Critique of ADI and Crank-Nicolson schemes; when they work and when they don't work Modelling jumps using Partial Integro Differential Equations (PIDE) Free and moving boundary value problems in QF Included with the book is a CD containing information on how to set up FDM algorithms, how to map these algorithms to C++ as well as several working programs for one-factor and two-factor models. We also provide source code so that you can customize the applications to suit your own needs.



Handbook Of Computational Finance


Handbook Of Computational Finance
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Author : Jin-Chuan Duan
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-10-25

Handbook Of Computational Finance written by Jin-Chuan Duan 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 2011-10-25 with Business & Economics categories.


Any financial asset that is openly traded has a market price. Except for extreme market conditions, market price may be more or less than a “fair” value. Fair value is likely to be some complicated function of the current intrinsic value of tangible or intangible assets underlying the claim and our assessment of the characteristics of the underlying assets with respect to the expected rate of growth, future dividends, volatility, and other relevant market factors. Some of these factors that affect the price can be measured at the time of a transaction with reasonably high accuracy. Most factors, however, relate to expectations about the future and to subjective issues, such as current management, corporate policies and market environment, that could affect the future financial performance of the underlying assets. Models are thus needed to describe the stochastic factors and environment, and their implementations inevitably require computational finance tools.



Monte Carlo And Quasi Monte Carlo Methods 2008


Monte Carlo And Quasi Monte Carlo Methods 2008
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Author : Pierre L' Ecuyer
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-01-14

Monte Carlo And Quasi Monte Carlo Methods 2008 written by Pierre L' Ecuyer 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 2010-01-14 with Mathematics categories.


This book represents the refereed proceedings of the Eighth International Conference on Monte Carlo (MC)and Quasi-Monte Carlo (QMC) Methods in Scientific Computing, held in Montreal (Canada) in July 2008. It covers the latest theoretical developments as well as important applications of these methods in different areas. It contains two tutorials, eight invited articles, and 32 carefully selected articles based on the 135 contributed presentations made at the conference. This conference is a major event in Monte Carlo methods and is the premiere event for quasi-Monte Carlo and its combination with Monte Carlo. This series of proceedings volumes is the primary outlet for quasi-Monte Carlo research.



Multilevel Monte Carlo And Debiased Monte Carlo Methods In Financial Engineering


Multilevel Monte Carlo And Debiased Monte Carlo Methods In Financial Engineering
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Author : Arun Kumar Polala
language : en
Publisher:
Release Date : 2020

Multilevel Monte Carlo And Debiased Monte Carlo Methods In Financial Engineering written by Arun Kumar Polala and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Mathematics categories.


This dissertation consists of two parts. In the first part we present a quasi-Monte Carlo implementation of the de-biased Monte Carlo estimator in the context of stochastic differential equations. We combine the quasi-Monte Carlo implementation with path generation techniques, and compare the accuracy of the resulting methods with the original de-biased Monte Carlo estimator when they are applied to option pricing problems under the geometric Brownian motion and Cox-Ingersoll-Ross models. In the second part we consider the application of the multilevel Monte Carlo methods to the LIBOR market model framework. The LIBOR market model is a popular interest rate model used for pricing interest rate derivatives like caplets, caps, and swaptions. Recently, long-dated interest rate derivatives have been popular in the interest rate derivative market, and the practitioners typically price them using the standard Monte Carlo method. To achieve real time pricing, practitioners often use very few Monte Carlo samples, typically in the low hundreds. We use multilevel Monte Carlo, low-discrepancy sequences, and path generation techniques to develop fast and accurate algorithms that achieve significant error reduction for small sample sizes, for pricing long-dated interest rate derivatives in the LIBOR market model framework.



Simulation Techniques In Financial Risk Management


Simulation Techniques In Financial Risk Management
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Author : Ngai Hang Chan
language : en
Publisher: John Wiley & Sons
Release Date : 2015-04-22

Simulation Techniques In Financial Risk Management written by Ngai Hang Chan 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 2015-04-22 with Mathematics categories.


Praise for the First Edition “...a nice, self-contained introduction to simulation and computational techniques in finance...” – Mathematical Reviews Simulation Techniques in Financial Risk Management, Second Edition takes a unique approach to the field of simulations by focusing on techniques necessary in the fields of finance and risk management. Thoroughly updated, the new edition expands on several key topics in these areas and presents many of the recent innovations in simulations and risk management, such as advanced option pricing models beyond the Black–Scholes paradigm, interest rate models, MCMC methods including stochastic volatility models simulations, model assets and model-free properties, jump diffusion, and state space modeling. The Second Edition also features: Updates to primary software used throughout the book, Microsoft Office® Excel® VBA New topical coverage on multiple assets, model-free properties, and related models More than 300 exercises at the end of each chapter, with select answers in the appendix, to help readers apply new concepts and test their understanding Extensive use of examples to illustrate how to use simulation techniques in risk management Practical case studies, such as the pricing of exotic options; simulations of Greeks in hedging; and the use of Bayesian ideas to assess the impact of jumps, so readers can reproduce the results of the studies A related website with additional solutions to problems within the book as well as Excel VBA and S-Plus computer code for many of the examples within the book Simulation Techniques in Financial Risk Management, Second Edition is an invaluable resource for risk managers in the financial and actuarial industries as well as a useful reference for readers interested in learning how to better gauge risk and make more informed decisions. The book is also ideal for upper-undergraduate and graduate-level courses in simulation and risk management.