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Financial Models with Levy Processes and Volatility Clustering.
The financial crisis that began in the summer of 2007 has led to criticisms that the financial models used by risk managers, portfolio managers, and even regulators simply do not reflect the realities of today's markets. While one tool cannot be blamed for the entire global financial crisis, im...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Wiley
2011.
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| Colección: | Frank J. Fabozzi series.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Financial Models with Levy Processes and Volatility Clustering. |
| 264 | 1 | |b Wiley |c 2011. | |
| 300 | |a 1 online resource (400 pages) | ||
| 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 The Frank J. Fabozzi series | |
| 505 | 0 | |a Cover -- Contents -- Preface -- About the Authors -- Chapter 1 Introduction -- 1.1 The Need for Better Financial Modeling of Asset Prices -- 1.2 The Family of Stable Distribution and Its Properties -- 1.2.1 Parameterization of the Stable Distribution -- 1.2.2 Desirable Properties of the Stable Distributions -- 1.2.3 Considerations in the Use of the Stable Distribution -- 1.3 Option Pricing With Volatility Clustering -- 1.3.1 Non-Gaussian Garch Models -- 1.4 Model Dependencies -- 1.5 Monte Carlo -- 1.6 Organization of the Book -- References -- Chapter 2 Probability Distributions -- 2.1 Basic Concepts -- 2.2 Discrete Probability Distributions -- 2.2.1 Bernoulli Distribution -- 2.2.2 Binomial Distribution -- 2.2.3 Poisson Distribution -- 2.3 Continuous Probability Distributions -- 2.3.1 Probability Distribution Function, Probability Density Function, and Cumulative Distribution Function -- 2.3.2 Normal Distribution -- 2.3.3 Exponential Distribution -- 2.3.4 Gamma Distribution -- 2.3.5 Variance Gamma Distribution -- 2.3.6 Inverse Gaussian Distribution -- 2.4 Statistic Moments and Quantiles -- 2.4.1 Location -- 2.4.2 Dispersion -- 2.4.3 Asymmetry -- 2.4.4 Concentration in Tails -- 2.4.5 Statistical Moments -- 2.4.6 Quantiles -- 2.4.7 Sample Moments -- 2.5 Characteristic Function -- 2.6 Joint Probability Distributions -- 2.6.1 Conditional Probability -- 2.6.2 Joint Probability Distribution Defined -- 2.6.3 Marginal Distribution -- 2.6.4 Dependence of Random Variables -- 2.6.5 Covariance and Correlation -- 2.6.6 Multivariate Normal Distribution -- 2.6.7 Elliptical Distributions -- 2.6.8 Copula Functions -- 2.7 Summary -- References -- Chapter 3 Stable and Tempered Stable Distributions -- 3.1 945;-Stable Distribution -- 3.1.1 Definition of An 945;-Stable Random Variable -- 3.1.2 Useful Properties of An 945;-Stable Random Variable -- 3.1.3 Smoothly Truncated Stable Distribution -- 3.2 Tempered Stable Distributions -- 3.2.1 Classical Tempered Stable Distribution -- 3.2.2 Generalized Classical Tempered Stable Distribution -- 3.2.3 Modified Tempered Stable Distribution -- 3.2.4 Normal Tempered Stable Distribution -- 3.2.5 Kim-Rachev Tempered Stable Distribution -- 3.2.6 Rapidly Decreasing Tempered Stable Distribution -- 3.3 Infinitely Divisible Distributions -- 3.3.1 Exponential Moments -- 3.4 Summary -- 3.5 Appendix -- 3.5.1 The Hypergeometric Function -- 3.5.2 The Confluent Hypergeometric Function -- References -- Chapter 4 Stochastic Processes in Continuous Time -- 4.1 Some Preliminaries -- 4.2 Poisson Process -- 4.2.1 Compounded Poisson Process -- 4.3 Pure Jump Process -- 4.3.1 Gamma Process -- 4.3.2 Inverse Gaussian Process -- 4.3.3 Variance Gamma Process -- 4.3.4 945;-Stable Process -- 4.3.5 Tempered Stable Process -- 4.4 Brownian Motion -- 4.4.1 Arithmetic Brownian Motion -- 4.4.2 Geometric Brownian Motion -- 4.5 Time-Changed Brownian Motion -- 4.5.1 Variance Gamma Process -- 4.5.2 Normal Inverse Gaussian Process -- 4.5.3 N. | |
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a The financial crisis that began in the summer of 2007 has led to criticisms that the financial models used by risk managers, portfolio managers, and even regulators simply do not reflect the realities of today's markets. While one tool cannot be blamed for the entire global financial crisis, improving the flexibility and statistical reliability of existing models, in addition to developing better models, is essential for both financial practitioners and academics seeking to explain and prevent extreme events. | ||
| 520 | |a Nobody understands this better than the expert author team of Svetlozar Rachev, Young Shin Kim, Michele Leonardo Bianchi, and Frank Fabozzi, and in Financial Models with Levy Processes and Volatility Clustering, they present a framework for modeling the behavior of stock returns in a univariate and multivariate setting--providing you with practical applications to option pricing and portfolio management. They also explain the reasons for working with non-normal distributions in financial modeling and the best methodologies for employing them. | ||
| 520 | |a This reliable resource includes detailed discussions of the basics of probability distributions and explains the alpha-stable distribution and the tempered stable distribution. The authors also explore discrete-time option pricing models, beginning with the classical normal model with volatility clustering to more recent models that consider both volatility clustering and heavy tails. | ||
| 520 | |a Filled with in-depth insights and expert advice, Financial Models with Levy Processes and Volatility Clustering is a thorough guide to both current probability distribution methods and brand new methodologies for financial modeling. --Book Jacket. | ||
| 546 | |a English. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Capital assets pricing model. | |
| 650 | 0 | |a Lévy processes. | |
| 650 | 0 | |a Finance |x Mathematical models. | |
| 650 | 0 | |a Probabilities. | |
| 650 | 6 | |a Modèle d'évaluation des actifs financiers. | |
| 650 | 6 | |a Lévy, Processus de. | |
| 650 | 6 | |a Finances |x Modèles mathématiques. | |
| 650 | 6 | |a Probabilités. | |
| 650 | 7 | |a probability. |2 aat | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Finance. |2 bisacsh | |
| 650 | 7 | |a Capital assets pricing model |2 fast | |
| 650 | 7 | |a Finance |x Mathematical models |2 fast | |
| 650 | 7 | |a Lévy processes |2 fast | |
| 650 | 7 | |a Probabilities |2 fast | |
| 655 | 4 | |a Electronic resource. | |
| 700 | 1 | |a Kim, Young Shin. |4 aut | |
| 700 | 1 | |a Bianchi, Michele Leonardo. |4 aut | |
| 700 | 1 | |a Fabozzi, Frank J. |4 aut | |
| 720 | |a Rachev, Svetlozar T. | ||
| 776 | 0 | 8 | |i Print version: |t Financial models with Lévy processes and volatility clustering. |d Hoboken, N.J. : John Wiley, ©2011 |z 9780470482353 |w (DLC) 2010033299 |w (OCoLC)656452753 |
| 830 | 0 | |a Frank J. Fabozzi series. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=661566 |z Texto completo |
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