by Fabrice Douglas Rouah, Gregory Vainberg
|
| List Price: | $100.00 |
| Amazon Price: | $63.00 & eligible for FREE Super Saver Shipping on orders over $25. |
| You Save: | $37.00 (37%) |
| Average Rating: |  |
| Lowest New Price: | $53.10 |
| Availablitiy: | Usually ships in 24 hours |
|
 |
|
Product Description
Praise for Option Pricing Models & Volatility Using Excel-VBA
"Excel is already a great pedagogical tool for teaching option valuation and risk management. But the VBA routines in this book elevate Excel to an industrial-strength financial engineering toolbox. I have no doubt that it will become hugely successful as a reference for option traders and risk managers."
--Peter Christoffersen, Associate Professor of Finance, Desautels Faculty of Management, McGill University
"This book is filled with methodology and techniques on how to implement option pricing and volatility models in VBA. The book takes an in-depth look into how to implement the Heston and Heston and Nandi models and includes an entire chapter on parameter estimation, but this is just the tip of the iceberg. Everyone interested in derivatives should have this book in their personal library."
--Espen Gaarder Haug, option trader, philosopher, nd author of Derivatives Models on Models
"I am impressed. This is an important book because it is the first book to cover the modern generation of option models, including stochastic volatility and GARCH."
--Steven L. Heston, Assistant Professor of Finance, R.H. Smith School of Business, University of Maryland
Customers who bought this item also bought
Average Customer Review:
0 of 0 people found the following review helpful:
 A staple in my cubicle, 2008-07-22
This book fills a large gap because it provides a practical way to implement option pricing models. I therefore have to agree with most of these posts: the book is well written, clearly explained, and light on theory. There's a lot of good stuff in there, so I like it a lot and find it very useful. I especially like the Greeks for the Heston and Heston & Nandi models. I had not seen these in closed form before buying this book.
0 of 0 people found the following review helpful:
Good Contents, Good Writing, Bad VBA Codes , 2008-07-21
An Overall good book with contents that are not covered by other books.
I found it very helpful to go though the math concepts and code practices.
However a new edition is seriously needed to correct all the bugs & errors in the book, The VBA codes provided has many bugs and omissions, which can confuse some begining VBA users.
1 of 1 people found the following review helpful:
 code not professional enough, 2008-05-02
I dont know whether the provided VBA code can be
trusted.
Within the very first example (complex numbers)
from the CD of the book, I found an annoying error.
The provided function gives a plain 4 as the square root of -16,
but all mathematicians know, it should be 4i.
They forgot to add the correct angle to the geometric
representation of complex numbers within the code.
Whats the value of a book with basic omissions ?
I'm really sorry.
1 of 1 people found the following review helpful:
Humayun Ali, 2008-02-17
Excel is already a great pedagogical tool for teaching option valuation and risk management. But the VBA routines in this book elevate Excel to an industrial-strength financial engineering toolbox. I have no doubt that it will become hugely successful as a reference for option traders and risk managers.
3 of 3 people found the following review helpful:
Great book for introducing stochastic-volatility models to a novice like me, 2008-01-20
I was a bit panic about choosing an appropriate topic for my master research essay in the area of option pricing. When I read half way through the book, I found what I wanted. The book introduces the continuous-time Heston SV model and the discrete-time Heston-Nandi SV model. The book also includes some codes for implementation and estimation methodologies for different option pricing models. However, as the book emphasises the limitation of vba -- you cannot apply complex estimation methods, e.g. non-linear estimation methods such as non-linear least squares method, to estimate the parameters of those stochastic volatility models. So if you want to apply those models to real market data, you should implement the models via MATLAB or other languages such as C++, JAVA. N.B. MATLAB codes for sv models can be easily obtained online.
Price is accurate as of the date/time indicated. Prices and product availability are subject to change. Any price displayed on the Amazon website at the time of purchase will govern the sale of this product.
|
Store Categories
|