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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

The Cox-Ingersoll-Ross model


Like the Vasicek model, the Cox-Ingersoll-Ross model (Cox at al., 1985), which is often cited as the CIR model, is a continuous, affine, one-factor stochastic interest rate model. In this model, the instantaneous interest rate dynamics are given by the following stochastic differential equation:

Here, α, β, and σ are positive constants, rt is the interest rate, t is the time, and Wt denotes the standard Wiener process. It is easy to see that the drift component is the same as in the Vasicek model; hence, the interest rate follows a mean-reverting process again, β is the long-run average, and α is the rate of adjustment. The difference is that the volatility term is not constant but is proportional to the square root of the interest rate level. This 'small' difference has dramatic consequences regarding the probability distribution of the future short rates. In the CIR model, the interest rate has non-central chi-squared distribution, with the following density...

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