Monte Carlo Methods in Financial Engineering (Hardcover)

Paul Glasserman

ISBN 10: 0387004513 / ISBN 13: 9780387004518

Editore: Springer-Verlag New York Inc., New York, NY, 2003

Riguardo questo articolo

Hardcover. Monte Carlo Methods are among the most broadly applicable and thus most powerful tools for valuing derivative securities and measuring their risks. As computer speeds continue to increase and new research expands the scope and efficiency of these methods, their use is destined to grow. This book is devoted to the use of Monte Carlo methods in finance. Advances in Monte Carlo methods in financial engineering take place at the interface between academic research and industry practice. This book targets that interface developing theory closely tied to applications. It is roughly divided into three parts: the first three chapters concentrate on the basics of Monte Carlo methods; the next three develop ways to improve Monte Carlo methods; and the final four chapters deal with more specialized problems arising, in particular applications of Monte Carlo to financial engineering. This book will serve as a reference for practitioners and researchers and will also be suitable as a graduate text for courses on computational finance. This book is devoted to the use of Monte Carlo methods in finance and is the first of its kind in this area. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Codice articolo 9780387004518

Dati bibliografici

• Titolo: Monte Carlo Methods in Financial Engineering (Hardcover)
• Editore: Springer-Verlag New York Inc., New York, NY
• Data di pubblicazione: 2003
• Lingua: Inglese
• ISBN 10: 0387004513
• ISBN 13: 9780387004518
• Rilegatura: Hardcover
• Condizione: new

Descrizione articolo

Riassunto

Monte Carlo Methods are among the most broadly applicable and thus most powerful tools for valuing derivative securities and measuring their risks. As computer speeds continue to increase and new research expands the scope and efficiency of these methods, their use is destined to grow. This book is devoted to the use of Monte Carlo methods in finance. Advances in Monte Carlo methods in financial engineering take place at the interface between academic research and industry practice. This book targets that interface developing theory closely tied to applications. It is roughly divided into three parts: the first three chapters concentrate on the basics of Monte Carlo methods; the next three develop ways to improve Monte Carlo methods; and the final four chapters deal with more specialized problems arising, in particular applications of Monte Carlo to financial engineering. This book will serve as a reference for practitioners and researchers and will also be suitable as a graduate text for courses on computational finance.

Dalla quarta di copertina

Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques.

This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios.

The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential.

The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry.