Download or read book Monte Carlo Simulation and Finance written by Don L. McLeish and published by John Wiley & Sons. This book was released on 2011-09-13 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Monte Carlo Methods and Models in Finance and Insurance written by Ralf Korn and published by CRC Press. This book was released on 2010-02-26 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Monte Carlo Methods in Financial Engineering written by Paul Glasserman and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Dimension and Variance Reduction for Monte Carlo Methods for High Dimensional Models in Finance written by Duy-Minh Dang and published by . This book was released on 2015 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: One-way coupling often occurs in multi-dimensional models in finance. In this paper, we present a dimension reduction technique for Monte Carlo (MC) methods, referred to as drMC, that exploits this structure for pricing plain-vanilla European options under a N-dimensional one-way coupled model, where N is arbitrary. The dimension reduction also often produces a significant variance reduction.The drMC method is a dimension reduction technique built upon (i) the conditional MC technique applied to one dimension and (ii) the derivation of a closed-form solution for the conditional Partial Differential Equation (PDE) that arises via Fourier transforms. In the drMC approach, the option price can be computed simply by taking the expectation of this closed-form solution. Hence, the approach results in a powerful dimension reduction from N to one, which often results in a significant variance reduction as well, since the variance associated with the other (N-1) factors in the original model are completely removed from the drMC simulation. Moreover, under the drMC framework, hedging parameters, or Greeks, can be computed in a much more efficient way than in traditional MC techniques.A variance reduction analysis of the method is presented and numerical results illustrating the method's efficiency are provided.

Download or read book Handbook in Monte Carlo Simulation written by Paolo Brandimarte and published by John Wiley & Sons. This book was released on 2014-06-20 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Monte Carlo Simulation with Applications to Finance written by Hui Wang and published by CRC Press. This book was released on 2012-05-22 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Automatic Variance Reduction for Monte Carlo Simulations Via the Local Importance Function Transform written by and published by . This book was released on 1996 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of r̀̀eal ̀̀particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a b̀̀lack box.̀̀ There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases.

Download or read book Theory and Applications of Monte Carlo Simulations written by Victor Chan and published by . This book was released on 2013 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to introduce researchers and practitioners to recent advances and applications of Monte Carlo Simulation (MCS). Random sampling is the key of the MCS technique. The 11 chapters of this book collectively illustrates how such a sampling technique is exploited to solve difficult problems or analyze complex systems in various engineering and science domains. Issues related to the use of MCS including goodness-of-fit, uncertainty evaluation, variance reduction, optimization, and statistical estimation are discussed and examples of solutions are given. Novel applications of MCS are demonstrated in financial systems modeling, estimation of transition behavior of organic molecules, chemical reaction, particle diffusion, kinetic simulation of biophysics and biological data, and healthcare practices. To enlarge the accessibility of this book, both field-specific background materials and field-specific usages of MCS are introduced in most chapters. The aim of this book is to unify knowledge of MCS from different fields to facilitate research and new applications of MCS.

Download or read book Monte Carlo Methods in Finance written by William Johnson and published by HiTeX Press. This book was released on 2024-10-16 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Monte Carlo Methods in Finance: Simulation Techniques for Market Modeling" presents a sophisticated and in-depth exploration of Monte Carlo simulations, a vital tool in modern financial analysis. This book deftly bridges the gap between theoretical constructs and practical implementation, guiding readers through a comprehensive understanding of how these methods unlock insights into the complexities of financial markets. Through capturing the randomness and volatility inherent in financial systems, Monte Carlo techniques provide a structured approach to modeling uncertainty, pricing derivatives, optimizing portfolios, and managing risk with precision and rigor. With a focus on making advanced concepts accessible, this book seamlessly integrates foundational theories with real-world applications. Each chapter meticulously explores critical subjects—ranging from stochastic processes and option pricing to credit risk and machine learning—while providing clear step-by-step Python implementations. As readers progress, they gain robust skills in executing simulations and interpreting results, empowering them to make informed financial decisions. Whether you are a student, a practitioner, or someone with a keen interest in quantitative finance, this text serves as an invaluable resource for mastering the intricacies of Monte Carlo methods and their impactful role in shaping contemporary finance.

Download or read book Rare Event Simulation using Monte Carlo Methods written by Gerardo Rubino and published by John Wiley & Sons. This book was released on 2009-03-18 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. Graduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.

Download or read book Multilevel Dimension Reduction Monte Carlo Simulation for High Dimensional Stochastic Models in Finance written by Duy-Minh Dang and published by . This book was released on 2015 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: One-way coupling often occurs in multi-dimensional stochastic models in finance. In this paper, we develop a highly efficient Monte Carlo (MC) method for pricing European options under a N-dimensional one-way coupled model, where N is arbitrary. The method is based on a combination of (i) the powerful dimension and variance reduction technique, referred to as drMC, developed in Dang et. al (2014), that exploits this structure, and (ii) the highly effective multilevel MC (mlMC) approach developed by Giles (2008). By first applying Step (i), the dimension of the problem is reduced from N to 1, and as a result, Step (ii) is essentially an application of mlMC on a 1-dimensional problem. Numerical results show that, through a careful construction of the ml-dr estimator, improved efficiency expected from the Milstein timestepping with first order strong convergence can be achieved. Moreover, our numerical results show that the proposed ml-drMC method is significantly more efficient than the mlMC methods currently available for multi-dimensional stochastic problems.

Download or read book Valuing Credit Risk Variance Reduction Techniques for Monte Carlo Methods written by Ralph Karels and published by GRIN Verlag. This book was released on 2003-05-21 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master's Thesis from the year 2003 in the subject Mathematics - Applied Mathematics, grade: 2,0 (B), Frankfurt School of Finance & Management, language: English, abstract: This paper deals with the valuation of credit risk derivatives on the basis of Monte Carlo simulation methods with the main viewpoint on variance reduction techniques. Therefore, first an overview on credit risk derivatives like credit default swaps and first to default baskets is given. It turns out that modelling of the joint distribution of dependent credit default times proves to be the crucial element. Once obtained, any credit derivative can be valued. A convenient way of achieving this is by use of the copula concept, which migrates marginal distributions of credit default times obtained from a credit curve into a joint distribution incorporating any kind of desired dependency structure. A section devoted to this concept provides the necessary background and properties. Next, the general Monte Carlo concept is introduced in detail and carefully adapted to the valuation of credit derivatives, following the path of constructing dependent uniform random variables from dependent normal random variables. At the same time, first insight is gained in the field of variance reduction which is intensified in chapter four, where a series of techniques including antithetic sampling and control variates is presented. The main focus shall lie from there on on importance sampling. In order to increase the efficiency of Monte Carlo methods, sampling is restricted to the region of importance where the function to be evaluated - here: the indicator function of the credit default times - does not vanish. This technique is applied and examined in detail in the final chapter for the one- and multi-credit case. Exponential as well as normal importance sampling densities are derived.

Download or read book Advances in Mathematical Finance written by Michael C. Fu and published by Springer Science & Business Media. This book was released on 2007-06-22 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained volume brings together a collection of chapters by some of the most distinguished researchers and practitioners in the field of mathematical finance and financial engineering. Presenting state-of-the-art developments in theory and practice, the book has real-world applications to fixed income models, credit risk models, CDO pricing, tax rebates, tax arbitrage, and tax equilibrium. It is a valuable resource for graduate students, researchers, and practitioners in mathematical finance and financial engineering.

Download or read book Simulation and Monte Carlo written by John Dagpunar and published by John Wiley & Sons. This book was released on 2007-03-12 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Monte Carlo Methods written by J. Hammersley and published by Springer Science & Business Media. This book was released on 2013-03-07 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph surveys the present state of Monte Carlo methods. we have dallied with certain topics that have interested us Although personally, we hope that our coverage of the subject is reasonably complete; at least we believe that this book and the references in it come near to exhausting the present range of the subject. On the other hand, there are many loose ends; for example we mention various ideas for variance reduction that have never been seriously appli(:d in practice. This is inevitable, and typical of a subject that has remained in its infancy for twenty years or more. We are convinced Qf:ver theless that Monte Carlo methods will one day reach an impressive maturity. The main theoretical content of this book is in Chapter 5; some readers may like to begin with this chapter, referring back to Chapters 2 and 3 when necessary. Chapters 7 to 12 deal with applications of the Monte Carlo method in various fields, and can be read in any order. For the sake of completeness, we cast a very brief glance in Chapter 4 at the direct simulation used in industrial and operational research, where the very simplest Monte Carlo techniques are usually sufficient. We assume that the reader has what might roughly be described as a 'graduate' knowledge of mathematics. The actual mathematical techniques are, with few exceptions, quite elementary, but we have freely used vectors, matrices, and similar mathematical language for the sake of conciseness.

Download or read book Techniques for Efficient Monte Carlo Simulation Volume III Variance Reduction written by E. J. McGrath and published by . This book was released on 1973 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many Monte Carlo simulation problems lend themselves readily to the application of variance reduction techniques. These techniques can result in great improvements in simulation efficiency. The document describes the basic concepts of variance reduction (Part 1), and a methodology for application of variance reduction techniques is presented in Part 2. Appendices include the basic analytical expressions for application of variance reduction schemes as well as an abstracted bibliography. The techniques considered here include importance sampling, Russian roulette and splitting, systematic sampling, stratified sampling, expected values, statistical estimation, correlated sampling, history reanalysis, control variates, antithetic variates, regression, sequantial sampling, adjoint formulation, transformations, orthonormal and conditional Monte Carlo. Emphasis has been placed on presentation of the material for application by the general user. This has been accomplished by presenting a step by step procedure for selection and application of the appropriate technique(s) for a given problem. (Author).

Download or read book Simulation and the Monte Carlo Method written by Reuven Y. Rubinstein and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the first simultaneous coverage of the statistical aspects of simulation and Monte Carlo methods, their commonalities and their differences for the solution of a wide spectrum of engineering and scientific problems. It contains standard material usually considered in Monte Carlo simulation as well as new material such as variance reduction techniques, regenerative simulation, and Monte Carlo optimization.