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Mastering R for Quantitative Finance

Mastering R for Quantitative Finance

By : Gabler
4 (11)
close
Mastering R for Quantitative Finance

Mastering R for Quantitative Finance

4 (11)
By: Gabler

Overview of this book

This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.
Table of Contents (15 chapters)
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14
Index

Parameter estimation of interest rate models


When using the interest rate models for pricing or simulation purposes, it is important to calibrate their parameters to real data properly. Here, we present a possible method to estimate the parameters. This method was developed by Chan et al, 1992, and is often referred to as the CKLS method. The procedure was elaborated to estimate the parameters of the following interest rate model with the help of the econometric procedure called Generalized Method of Moments (GMM; see Hansen, 1982, for more details):

It is easy to see that this process gives the Vasicek model when γ=0, and the CIR model when γ =0.5. As the first step of the parameter estimation, we discretize this equation with the Euler approximation (see Atkinson, 1989):

Here, δt is the time interval between two observations of the interest rate and et is independent, standard normal random variables. The parameters are estimated with the following null hypothesis:

Let Θ be the vector of...

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