Many introductory books on mathematical finance also outline some com-
puter algorithms. My goal is to contribute a closer look at algorithmic
issues that arise from complex forms of the underlying pricing
models-issues many practitioners need to solve sooner or later in their
careers. This book takes such a close look at uncertain volatility
models, an exten- sion of Black-Scholes theory.It discusses applications
to exotic option portfo- lios with barriers and early exercise features.
It describes an object-oriented C++ solution, included in source code on
the accompanying CD. Practitioners and students who need to build
analytic software libraries may benefit from reading this book and
studying the software. The book focuses on a family of mathematical
models, while in the field one encounters greater variation in
instrument properties. In both cases mathematical and financial
knowledge must be complemented by good programming skills to produce the
best system. Analytic software needs design-a central message of the
later chapters of this book. This book has come out of my Ph.D. thesis.
I am very grateful to my academic advisor, Marco Avellaneda of New York
University, who taught me mathematical finance and uncertain volatility.
Computational finance be- came exciting for me because Marco encouraged
an algorithmic approach to uncertain volatility. I thank Afshin
Bayrooti, Vladimir Finkelstein, and Antonio Paras for giving valuable
feedback. Antonio is the co-inventor of the original uncertain
volatility model, A-UVM. Richard Holmes has found a crucial bug in an
early implementation of the software.