Stochastic Processes with Applications to Finance, Second Edition
Features
- Uses discrete processes to clearly explain difficult concepts in stochastic calculus
- Describes the dynamics of credit ratings using Markov chains
- Shows how Monte Carlo simulation is used in financial engineering
- Addresses recent applications in the pricing of discount bonds and credit derivatives
- Contains end-of-chapter exercises and numerous examples throughout
Summary
Financial engineering has been proven to be a useful tool for risk management, but using the theory in practice requires a thorough understanding of the risks and ethical standards involved. Stochastic Processes with Applications to Finance, Second Edition presents the mathematical theory of financial engineering using only basic mathematical tools that are easy to understand even for those with little mathematical expertise. This second edition covers several important developments in the financial industry.
New to the Second Edition
- A chapter on the change of measures and pricing of insurance products
- Many examples of the change of measure technique, including its use in asset pricing theory
- A section on the use of copulas, especially in the pricing of CDOs
- Two chapters that offer more coverage of interest rate derivatives and credit derivatives
Exploring the merge of actuarial science and financial engineering, this edition examines how the pricing of insurance products, such as equity-linked annuities, requires knowledge of asset pricing theory since the equity index can be traded in the market. The book looks at the development of many probability transforms for pricing insurance risks, including the Esscher transform. It also describes how the copula model is used to model the joint distribution of underlying assets.
By presenting significant results in discrete processes and showing how to transfer the results to their continuous counterparts, this text imparts an accessible, practical understanding of the subject. It helps readers not only grasp the theory of financial engineering, but also implement the theory in business.
Table of Contents
Elementary Calculus: Towards Ito’s Formula
Exponential and Logarithmic Functions
Differentiation
Taylor’s Expansion
Ito’s Formula
Integration
Elements in Probability
The Sample Space and Probability
Discrete Random Variables
Continuous Random Variables
Bivariate Random Variables
Expectation
Conditional Expectation
Moment Generating Functions
Copulas
Useful Distributions in Finance
Binomial Distributions
Other Discrete Distributions
Normal and Log-Normal Distributions
Other Continuous Distributions
Multivariate Normal Distributions
Derivative Securities
The Money-Market Account
Various Interest Rates
Forward and Futures Contracts
Options
Interest-Rate Derivatives
Change of Measures and the Pricing of Insurance Products
Change of Measures Based on Positive Random Variables
BlackScholes Formula and Esscher Transform
Premium Principles for Insurance Products
Bühlmann’s Equilibrium Pricing Model
A Discrete-Time Model for Securities Market
Price Processes
Portfolio Value and Stochastic Integral
No-Arbitrage and Replicating Portfolios
Martingales and the Asset Pricing Theorem
American Options
Change of Measures Based on Positive Martingales
Random Walks
The Mathematical Definition
Transition Probabilities
The Reflection Principle
Change of Measures in Random Walks
The Binomial Securities Market Model
The Binomial Model
The Single-Period Model
Multi-Period Models
The Binomial Model for American Options
The Trinomial Model
The Binomial Model for Interest-Rate Claims
A Discrete-Time Model for Defaultable Securities
The Hazard Rate
Discrete Cox Processes
Pricing of Defaultable Securities
Correlated Defaults
Markov Chains
Markov and Strong Markov Properties
Transition Probabilities
Absorbing Markov Chains
Applications to Finance
Monte Carlo Simulation
Mathematical Backgrounds
The Idea of Monte Carlo
Generation of Random Numbers
Some Examples from Financial Engineering
Variance Reduction Methods
From Discrete to Continuous: Towards the BlackScholes
Brownian Motions
The Central Limit Theorem Revisited
The BlackScholes Formula
More on Brownian Motions
Poisson Processes
Basic Stochastic Processes in Continuous Time
Diffusion Processes
Sample Paths of Brownian Motions
Continuous-Time Martingales
Stochastic Integrals
Stochastic Differential Equations
Ito;s Formula Revisited
A Continuous-Time Model for Securities Market
Self-Financing Portfolio and No-Arbitrage
Price Process Models
The BlackScholes Model
The Risk-Neutral Method
The Forward-Neutral Method
Term-Structure Models and Interest-Rate Derivatives
Spot-Rate Models
The Pricing of Discount Bonds
Pricing of Interest-Rate Derivatives
Forward LIBOR and Black’s Formula
A Continuous-Time Model for Defaultable Securities
The Structural Approach
The Reduced-Form Approach
Pricing of Credit Derivatives
References
Index
Exercises appear at the end of each chapter.
