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Financial Modeling, fifth edition
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$125.00
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Product Details
Author:
Simon Benninga, Tal Mofkadi
Format:
Hardcover
Pages:
1048
Publisher:
MIT Press (February 1, 2022)
Imprint:
The MIT Press
Language:
English
Audience:
General/trade
ISBN-13:
9780262046428
ISBN-10:
0262046423
Weight:
56.2oz
Dimensions:
7.31" x 9.31" x 1.44"
File:
RandomHouse-PRH_Book_Company_PRH_PRT_Onix_full_active_D20260705T120602_156890278-20260705.xml
Folder:
RandomHouse
List Price:
$125.00
Country of Origin:
United States
Pub Discount:
65
Case Pack:
8
As low as:
$96.25
Publisher Identifier:
P-RH
Discount Code:
A
QuickShip:
Yes
Overview
A substantially updated new edition of the essential text on financial modeling, with revised material, new data, and implementations shown in Excel, R, and Python.
Financial Modeling has become the gold-standard text in its field, an essential guide for students, researchers, and practitioners that provides the computational tools needed for modeling finance fundamentals. This fifth edition has been substantially updated but maintains the straightforward, hands-on approach, with an optimal mix of explanation and implementation, that made the previous editions so popular. Using detailed Excel spreadsheets, it explains basic and advanced models in the areas of corporate finance, portfolio management, options, and bonds. This new edition offers revised material on valuation, second-order and third-order Greeks for options, value at risk (VaR), Monte Carlo methods, and implementation in R. The examples and implementation use up-to-date and relevant data.
Parts I to V cover corporate finance topics, bond and yield curve models, portfolio theory, options and derivatives, and Monte Carlo methods and their implementation in finance. Parts VI and VII treat technical topics, with part VI covering Excel and R issues and part VII (now on the book’s auxiliary website) covering Excel’s programming language, Visual Basic for Applications (VBA), and Python implementations. Knowledge of technical chapters on VBA and R is not necessary for understanding the material in the first five parts. The book is suitable for use in advanced finance classes that emphasize the need to combine modeling skills with a deeper knowledge of the underlying financial models.
Financial Modeling has become the gold-standard text in its field, an essential guide for students, researchers, and practitioners that provides the computational tools needed for modeling finance fundamentals. This fifth edition has been substantially updated but maintains the straightforward, hands-on approach, with an optimal mix of explanation and implementation, that made the previous editions so popular. Using detailed Excel spreadsheets, it explains basic and advanced models in the areas of corporate finance, portfolio management, options, and bonds. This new edition offers revised material on valuation, second-order and third-order Greeks for options, value at risk (VaR), Monte Carlo methods, and implementation in R. The examples and implementation use up-to-date and relevant data.
Parts I to V cover corporate finance topics, bond and yield curve models, portfolio theory, options and derivatives, and Monte Carlo methods and their implementation in finance. Parts VI and VII treat technical topics, with part VI covering Excel and R issues and part VII (now on the book’s auxiliary website) covering Excel’s programming language, Visual Basic for Applications (VBA), and Python implementations. Knowledge of technical chapters on VBA and R is not necessary for understanding the material in the first five parts. The book is suitable for use in advanced finance classes that emphasize the need to combine modeling skills with a deeper knowledge of the underlying financial models.
