Dallas Public Library

Implementing models of financial derivatives, object oriented applications with VBA, Nick Webber

eng

Includes bibliographical references (pages 641-643) and indexes

illustrations

index present

non fiction

Implementing models of financial derivatives

bibliography

636566705

Nick Webber

object oriented applications with VBA

"A practical, step-by-step introduction to the design of pricing engines with VBA This book teaches students and practitioners the numerics and design of a powerful pricing tool in VBA. It leads the reader through the basics of VBA, from simple procedural code to the advanced design of systems and object-style applications. It also covers Monte Carlo and lattice methods and their implementation in VBA. Full implementation methods and code are provided for all methods discussed, making this an invaluable guide for portfolio managers, risk managers, and fund managers. Nick Webber (Warwick, UK) is a lecturer in finance at Warwick Business School. He specializes in interest rate modeling and computational finance"--, Provided by publisher"This book teaches students and non-quant practitioners numerics and the design of a powerful pricing tool in VBA"--, Provided by publisher

Part I A procedural Monte Carlo methods in VBA -- 1 The Monte Carlo method -- 2 Levels of programming sophistication -- 3 Procedural programming: level 1 -- 4 Validation and error handing: level 2 -- Part II Objects and polymorphism -- 5 Introducing objects: level 3 -- 6 Polymorphism and interfaces: level 4 -- 7 A slice-based Monte Carlo -- 8 An embryonic factory: level 5 -- Part III Using files with VBA -- 9 Input and output to file in VBA -- 10 Valuing a book of options -- Part IV Polymorphic factories in VBA -- 11 The VBE object library and a simple polymorphic factory -- 12 A fully polymorphic factory: level 6 -- 13 A semi-polymorphic factory: meta-classes -- Part V Performance issues in VBA -- 14 Performance and cost in VBA -- 15 Level and performance -- 16 Evolution and data structures -- Part VI Variance reduction in the Monte Carlo method -- 17 Wiener sample paths and antithetic variates -- 18 The wierner process and stratified sampling -- 19 Low-discrepancy sampling -- 20 Variance reduction with control variates -- 21 Implementing control variates -- 22 Extreme options and importance sampling -- 23 Combining variance reduction methods -- Part VII The Monte Carlo method: convergence and bias -- 24 The Monte Carlo method: convergence and bias -- 25 Discretization methods -- 26 Applications to models -- 27 Valuation in the Heston model -- Part VIII Valuing American options by simulation -- 28 Valuing American and Bermudan options -- 29 Estimating the early exercise boundary -- 30 The plain LSLS method -- 31 Control variates and the LSLS method -- Appendices -- A VBA and excel -- B Some option formulae -- C The utility code modules -- D Running DLLs from VBA -- E Object-oriented programming -- F A Yukky level 0 monolithic lattice implementation -- G A level 1 crank-Nicolson PDE implementation -- H Root-finding and minimization algorithms