Calibration and Parameterization Methods for the Libor Market Model [electronic resource] /
Hackl, Christoph.author.
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 necessary 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 tradeoff of speed and correctness where differences in choosing random number generators and the advantages of factor reduction are shown.   Contents   Libor Market Model implementation framework Speed vs. correctness Application examples and possible extensions     Target Groups Researchers and advanced master degree students in a quantitative field (Mathematics, Quant. Finance, Statistics, Physics) Practitioners in the quantitative area of the financial services industry   The Author Christoph Hackl, MA obtained his master’s degree at the UAS bfi Vienna in the programme „Quantitative Asset and Risk Management“.
Description based upon print version of record.
Includes bibliographical references.
Libor Market Model implementation framework -- Speed vs. correctness -- Application examples and possible extensions.
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 necessary 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 tradeoff of speed and correctness where differences in choosing random number generators and the advantages of factor reduction are shown.   Contents   Libor Market Model implementation framework Speed vs. correctness Application examples and possible extensions     Target Groups Researchers and advanced master degree students in a quantitative field (Mathematics, Quant. Finance, Statistics, Physics) Practitioners in the quantitative area of the financial services industry   The Author Christoph Hackl, MA obtained his master’s degree at the UAS bfi Vienna in the programme „Quantitative Asset and Risk Management“.
Finance.
Macroeconomics.
Finance, general.
Macroeconomics/Monetary Economics//Financial Economics.

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