Mathematical Finance Theory Modeling Implementation 1st Edition by Christian Fries – Ebook PDF Instant Download/Delivery: 0470047224 ,9780470047224
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ISBN 10: 0470047224
ISBN 13: 9780470047224
Author: Christian Fries
The ever-growing use of derivative products makes it essential for financial industry practitioners to have a solid understanding of derivative pricing. To cope with the growing complexity, narrowing margins, and shortening life-cycle of the individual derivative product, an efficient, yet modular, implementation of the pricing algorithms is necessary. Mathematical Finance is the first book to harmonize the theory, modeling, and implementation of today’s most prevalent pricing models under one convenient cover. Building a bridge from academia to practice, this self-contained text applies theoretical concepts to real-world examples and introduces state-of-the-art, object-oriented programming techniques that equip the reader with the conceptual and illustrative tools needed to understand and develop successful derivative pricing models.
Utilizing almost twenty years of academic and industry experience, the author discusses the mathematical concepts that are the foundation of commonly used derivative pricing models, and insightful Motivation and Interpretation sections for each concept are presented to further illustrate the relationship between theory and practice. In-depth coverage of the common characteristics found amongst successful pricing models are provided in addition to key techniques and tips for the construction of these models. The opportunity to interactively explore the book’s principal ideas and methodologies is made possible via a related Web site that features interactive Java experiments and exercises.
While a high standard of mathematical precision is retained, Mathematical Finance emphasizes practical motivations, interpretations, and results and is an excellent textbook for students in mathematical finance, computational finance, and derivative pricing courses at the upper undergraduate or beginning graduate level. It also serves as a valuable reference for professionals in the banking, insurance, and asset management industries.
Mathematical Finance Theory Modeling Implementation 1st Edition Table of contents:
Chapter 1: Introduction
- 1.1 The Role of Mathematical Finance
- 1.2 Overview of Financial Markets
- 1.3 Basic Financial Instruments
- 1.4 The Role of Models in Finance
- 1.5 Structure of the Book
Chapter 2: Basic Concepts in Probability and Stochastic Processes
- 2.1 Probability Theory and Random Variables
- 2.2 Stochastic Processes and Filtrations
- 2.3 Markov Processes
- 2.4 Brownian Motion and Wiener Process
- 2.5 The Ito Calculus
Chapter 3: Financial Markets and Instruments
- 3.1 Types of Financial Markets
- 3.2 Pricing of Financial Instruments
- 3.3 The Concept of Arbitrage
- 3.4 Pricing of Bonds, Stocks, and Derivatives
- 3.5 The Black-Scholes Model
Chapter 4: Static Models in Mathematical Finance
- 4.1 The Capital Asset Pricing Model (CAPM)
- 4.2 Portfolio Theory
- 4.3 Utility Theory
- 4.4 Optimal Portfolio Selection
- 4.5 Risk Management
Chapter 5: Stochastic Processes in Financial Models
- 5.1 Modeling Stock Prices with Geometric Brownian Motion
- 5.2 Stochastic Differential Equations (SDEs)
- 5.3 Deriving the Black-Scholes Equation
- 5.4 Pricing Options Using the Black-Scholes Formula
- 5.5 The Greeks and Sensitivity Analysis
Chapter 6: The Black-Scholes Model and Beyond
- 6.1 The Black-Scholes Framework
- 6.2 Extensions to the Black-Scholes Model
- 6.3 Stochastic Volatility Models
- 6.4 Jump-Diffusion Models
- 6.5 Local Volatility Models
Chapter 7: Derivatives Pricing and Hedging
- 7.1 Basic Derivatives and Hedging Strategies
- 7.2 Dynamic Hedging
- 7.3 Pricing American Options
- 7.4 Numerical Methods for Option Pricing (Monte Carlo, Finite Difference)
- 7.5 The Role of Risk-Neutral Pricing
Chapter 8: Interest Rate Models
- 8.1 The Term Structure of Interest Rates
- 8.2 The Vasicek Model
- 8.3 The Cox-Ingersoll-Ross (CIR) Model
- 8.4 The Hull-White Model
- 8.5 Applications in Pricing Bonds and Swaps
Chapter 9: Credit Risk and Credit Derivatives
- 9.1 Credit Risk Models
- 9.2 Credit Default Swaps (CDS)
- 9.3 Collateralized Debt Obligations (CDOs)
- 9.4 Structural Models of Credit Risk
- 9.5 Reduced-Form Models
Chapter 10: Numerical Methods for Financial Modeling
- 10.1 Monte Carlo Simulation
- 10.2 Finite Difference Methods
- 10.3 Binomial Tree Models
- 10.4 Numerical Methods for Stochastic Differential Equations
- 10.5 Risk and Sensitivity Analysis in Numerical Finance
Chapter 11: Empirical Models and Market Data
- 11.1 Analyzing Market Data
- 11.2 Estimation of Volatility and Correlation
- 11.3 High-Frequency Data and Market Microstructure
- 11.4 Empirical Tests of Financial Models
- 11.5 Calibration of Financial Models to Market Data
Chapter 12: Risk Management and Financial Engineering
- 12.1 The Concept of Financial Risk
- 12.2 Value at Risk (VaR)
- 12.3 Stress Testing and Scenario Analysis
- 12.4 Financial Engineering: From Theory to Practice
- 12.5 Applications in Real-World Risk Management
Chapter 13: The Future of Mathematical Finance
- 13.1 Emerging Trends in Financial Modeling
- 13.2 The Role of Technology in Financial Markets
- 13.3 The Intersection of Mathematical Finance and Machine Learning
- 13.4 Challenges and Future Directions
Appendices
- A. Key Mathematical Results
- B. Tables for Option Pricing Calculations
- C. Glossary of Terms
Index
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