Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics

Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics

Author(s): Paolo Brandimarte

Published Online: 20 JUN 2014 08:42PM EST

Print ISBN: 9780470531112

Online ISBN: 9781118593264

DOI: 10.1002/9781118593264

About this Book

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.

Table of contents

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  1. Part I: Overview and Motivation

  2. Part II: Input Analysis: Modeling and Estimation

  3. Part III: Sampling and Path Generation

  4. Part IV: Output Analysis and Efficiency Improvement

  5. Part V: Miscellaneous Applications

    1. You have free access to this content
    1. You have free access to this content

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