Financial Models with Levy Processes and Volatility Clustering

In Financial Models with Levy Processes and Volatility Clustering, the expert author team provides a framework to model the behavior of stock returns in both a univariate and a multivariate setting, providing you with practical applications to option pricing and portfolio management. They also explain the reasons for working with non-normal distribution in financial modeling and the best methodologies for employing it.

The book's framework includes 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.

• Reviews the basics of probability distributions
• Analyzes a continuous time option pricing model (the so-called exponential Levy model)
• Defines a discrete time model with volatility clustering and how to price options using Monte Carlo methods
• Studies two multivariate settings that are suitable to explain joint extreme events

Financial Models with Levy Processes and Volatility Clustering is a thorough guide to classical probability distribution methods and brand new methodologies for financial modeling.Content:
Chapter 1 Introduction (pages 1–17):
Chapter 2 Probability Distributions (pages 19–55):
Chapter 3 Stable and Tempered Stable Distributions (pages 57–85):
Chapter 4 Stochastic Processes in Continuous Time (pages 87–106):
Chapter 5 Conditional Expectation and Change of Measure (pages 107–122):
Chapter 6 Exponential Levy Models (pages 123–140):
Chapter 7 Option Pricing in Exponential Levy Models (pages 141–168):
Chapter 8 Simulation (pages 169–223):
Chapter 9 Multi?Tail t?Distribution (pages 225–246):
Chapter 10 Non?Gaussian Portfolio Allocation (pages 247–269):
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