Computational Financial Mathematics using MATHEMATICA®

This book provides a comprehensive overview of existing and original material, about what mathematics when allied with Mathematica can do for finance. Sophisticated theories are presented systematically in a user-friendly style, and a powerful combination of mathematical rigor and Mathematica programming. The book is designed for the academic community of instructors and students, and most importantly, will meet the everyday trading needs of quantitatively inclined professional and indiviual investors who want to solve various problems encountered when investing and trading in stocks and stock options.

"Stojanovic offers an excellent, user-friendly presentation of advanced mathematical techniques and Mathematica programming for solving problems in finance and trading. He demonstrates the value of probability, mathematical statistics, calculus of variations, and optimal control of stochastic, ordinary and partial differential equations to the study of market analysis. Solutions are computed symbolically, numerically, or by means of Monte-Carlo simulations.... A very useful and valuable book for researchers, students, professionals, and individual investors." Choice

"It is an innovative approach and is very useful for students and practitioners in finance to learn how to use mathematics for investment analysis." Mathematical Reviews

"This book is a state-of-the-art introduction to the mathematics of computational finance. The author reviews and extends several recent breakthroughs and also provides new material, which is highly recommended. The novel use of Mathematica enhances the learning experience by letting the reader focus on the essential ideas. I thoroughly recommend this book to both students and practitioners." Peter Carr, Courant Institute, New York University

Inhalt
0 Introduction.- 0.1 Audience, Highlights, Agenda.- 0.2 Software Installation.- 0.3 Acknowledgments.- Chapter1 Cash Account Evolution.- 1.1 Symbolic Solutions of ODEs.- 1.2 Numerical Solutions of ODEs.- 2 Stock Price Evolution.- 2.1 What are Stocks?.- 2.2 Stock Price Modeling: Stochastic Differential Equations.- 2.3 Itô Calculus.- 2.4 Multivariate and Symbolic Itô Calculus.- 2.5 Relationship Between SDEs and PDEs.- 3 European Style Stock Options.- 3.1 What Are Stock Options?.- 3.2 Black-Scholes PDE and Hedging.- 3.3 Solving Black-Scholes PDE Symbolically.- 3.4 Generalized Black-Scholes Formulas: Time-Dependent Data.- 4 Stock Market Statistics.- 4.1 Remarks.- 4.2 Stock Market Data Import and Manipulation.- 4.3 Volatility Estimates: Scalar Case.- 4.4 Appreciation Rate Estimates: Scalar Case.- 4.5 Statistical Experiments: Bayesian and Non-Bayesian.- 4.6 Vector Basic Price Model Statistics.- 4.7 Dynamic Statistics: Filtering of Conditional Gaussian Processes.- 5 Implied Volatility for European Options.- 5.1 Remarks.- 5.2 Option Market Data.- 5.3 Black-Scholes Theory vs. Market Data: Implied Volatility.- 5.4 Numerical PDEs, Optimal Control, and Implied Volatility.- 6 American Style Stock Options.- 6.1 Remarks.- 6.2 American Options and Obstacle Problems.- 6.3 General Implied Volatility for American Options.- 7 Optimal Portfolio Rules.- 7.1 Remarks.- 7.2 Utility of Wealth.- 7.3 Merton's Optimal Portfolio Rule Derived and Implemented.- 7.4 Portfolio Rules under Appreciation Rate Uncertainty.- 7.5 Portfolio Optimization under Equality Constraints.- 7.6 Portfolio Optimization under Inequality Constraints.- 8 Advanced Trading Strategies.- 8.1 Remarks.- 8.2 Reduced MongeAmpere PDEs of Advanced Portfolio Hedging.- 8.3 Hypoelliptic Obstacle Problems in Optimal MomentumTrading.