- We will send in 10–14 business days.
/images/books/13225487/9783658046873.jpg)
- Author: Christoph Hackl
- Publisher: Springer Gabler
- Year: 2014
- Pages: 64
- ISBN-10: 3658046872
- ISBN-13: 9783658046873
- Format: 14.8 x 21 x 0.5 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Calibration and Parameterization Methods for the Libor Market Model (e-book) (used book) | bookbook.eu
Reviews
Description
The Libor Market Model (LMM) is a mathematical model for pricing and risk management of interest rate derivatives and has been built on the framework of modelling forward rates. For the conceptual understanding of the model a strong background in the fields of mathematics, statistics, finance and especially for implementation, computer science is necessary. The book provides the ne cessary groundwork to understand the LMM and delivers a framework to implement a working model where possible calibration and parameterization methods for volatility and correlation are explained. Special emphasis lies also on the trade off of speed and correctness where differences in choosing random number generators and the advantages of factor reduction are shown.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 21d.10:34:47
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Christoph Hackl
- Publisher: Springer Gabler
- Year: 2014
- Pages: 64
- ISBN-10: 3658046872
- ISBN-13: 9783658046873
- Format: 14.8 x 21 x 0.5 cm, minkšti viršeliai
- Language: English English
The Libor Market Model (LMM) is a mathematical model for pricing and risk management of interest rate derivatives and has been built on the framework of modelling forward rates. For the conceptual understanding of the model a strong background in the fields of mathematics, statistics, finance and especially for implementation, computer science is necessary. The book provides the ne cessary groundwork to understand the LMM and delivers a framework to implement a working model where possible calibration and parameterization methods for volatility and correlation are explained. Special emphasis lies also on the trade off of speed and correctness where differences in choosing random number generators and the advantages of factor reduction are shown.
Reviews