Handbook in Monte Carlo simulation : applications in financial engineering, risk management, and economics / Paolo Brandimarte.
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 time...
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| Online Access: |
Full Text (via Wiley) |
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| Main Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Hoboken, New Jersey :
John Wiley & Sons,
[2014]
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| Series: | Wiley handbooks in financial engineering and econometrics.
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| Subjects: |
MARC
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| 100 | 1 | |a Brandimarte, Paolo. |0 http://id.loc.gov/authorities/names/n95065713 |1 http://isni.org/isni/0000000115915893. | |
| 245 | 1 | 0 | |a Handbook in Monte Carlo simulation : |b applications in financial engineering, risk management, and economics / |c Paolo Brandimarte. |
| 264 | 1 | |a Hoboken, New Jersey : |b John Wiley & Sons, |c [2014] | |
| 264 | 4 | |c ©2014. | |
| 300 | |a 1 online resource. | ||
| 336 | |a text |b txt |2 rdacontent. | ||
| 337 | |a computer |b c |2 rdamedia. | ||
| 338 | |a online resource |b cr |2 rdacarrier. | ||
| 490 | 1 | |a Financial engineering and econometrics. | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Half Title page; Title page; Copyright page; Preface; Part One: Overview and Motivation; Chapter One: Introduction to Monte Carlo Methods; 1.1 Historical origin of Monte Carlo simulation; 1.2 Monte Carlo simulation vs. Monte Carlo sampling; 1.3 System dynamics and the mechanics of Monte Carlo simulation; 1.4 Simulation and optimization; 1.5 Pitfalls in Monte Carlo simulation; 1.6 Software tools for Monte Carlo simulation; 1.7 Prerequisites; For further reading; References; Chapter Two: Numerical Integration Methods; 2.1 Classical quadrature formulas; 2.2 Gaussian quadrature. | |
| 505 | 8 | |a 2.3 Extension to higher dimensions: Product rules2.4 Alternative approaches for high-dimensional integration; 2.5 Relationship with moment matching; 2.6 Numerical integration in R; For further reading; References; Part Two: Input Analysis: Modeling and Estimation; Chapter Three: Stochastic Modeling in Finance and Economics; 3.1 Introductory examples; 3.2 Some common probability distributions; 3.3 Multivariate distributions: Covariance and correlation; 3.4 Modeling dependence with copulas; 3.5 Linear regression models: A probabilistic view; 3.6 Time series models. | |
| 505 | 8 | |a 3.7 Stochastic differential equations3.8 Dimensionality reduction; 3.9 Risk-neutral derivative pricing; For further reading; References; Chapter Four: Estimation and Fitting; 4.1 Basic inferential statistics in R; 4.2 Parameter estimation; 4.3 Checking the fit of hypothetical distributions; 4.4 Estimation of linear regression models by ordinary least squares; 4.5 Fitting time series models; 4.6 Subjective probability: The Bayesian view; For further reading; References; Part Three: Sampling and Path Generation; Chapter Five: Random Variate Generation. | |
| 505 | 8 | |a 5.1 The structure of a Monte Carlo simulation5.2 Generating pseudorandom numbers; 5.3 The inverse transform method; 5.4 The acceptance-rejection method; 5.5 Generating normal variates; 5.6 Other ad hoc methods; 5.7 Sampling from copulas; For further reading; References; Chapter Six: Sample Path Generation for Continuous-Time Models; 6.1 Issues in path generation; 6.2 Simulating geometric Brownian motion; 6.3 Sample paths of short-term interest rates; 6.4 Dealing with stochastic volatility; 6.5 Dealing with jumps; For further reading; References. | |
| 505 | 8 | |a Part Four: Output Analysis and Efficiency ImprovementChapter Seven: Output Analysis; 7.1 Pitfalls in output analysis; 7.2 Setting the number of replications; 7.3 A world beyond averages; 7.4 Good and bad news; For further reading; References; Chapter Eight: Variance Reduction Methods; 8.1 Antithetic sampling; 8.2 Common random numbers; 8.3 Control variates; 8.4 Conditional Monte Carlo; 8.5 Stratified sampling; 8.6 Importance sampling; For further reading; References; Chapter Nine: Low-Discrepancy Sequences; 9.1 Low-discrepancy sequences; 9.2 Halton sequences. | |
| 520 | |a 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. | ||
| 546 | |a English. | ||
| 588 | 0 | |a Print version record and CIP data provided by publisher. | |
| 650 | 0 | |a Finance |x Mathematical models. |0 http://id.loc.gov/authorities/subjects/sh85048260. | |
| 650 | 0 | |a Economics |x Mathematical models. |0 http://id.loc.gov/authorities/subjects/sh85040857. | |
| 650 | 0 | |a Monte Carlo method. |0 http://id.loc.gov/authorities/subjects/sh85087032. | |
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| 650 | 7 | |a Finance |x Mathematical models. |2 fast |0 (OCoLC)fst00924398. | |
| 650 | 7 | |a Monte Carlo method. |2 fast |0 (OCoLC)fst01025819. | |
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| 830 | 0 | |a Wiley handbooks in financial engineering and econometrics. |0 http://id.loc.gov/authorities/names/no2012023967. | |
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