Empirical comparisons in short-term interest rate models using nonparametric methods
AbstractThis study applies the nonparametric estimation procedure to the diffusion process modeling the dynamics of short-term interest rates. This approach allows us to operate in continuous time, estimating the continuous-time model, despite the use of discrete data. Three methods are proposed. We apply these methods to two important financial data. After selecting an appropriate bandwidth for each dataset, empirical comparisons indicate that the specification of the drift has a considerable impact on the pricing of derivatives through its effect on the diffusion function. In addition, a novel nonparametric test has been proposed for specification of linearity in the drift. Our simulation directs us to reject the null hypothesis of linearity at the 5% significance level for the two financial datasets.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 11974.
Date of creation: 23 Sep 2004
Date of revision: 23 Dec 2005
Publication status: Published in Journal of Financial Econometrics 1.4(2006): pp. 310-345
Diffusion process; drift function; kernel density estimation; stochastic volatility;
Other versions of this item:
- Manuel Arapis & Jiti Gao, 2006. "Empirical Comparisons in Short-Term Interest Rate Models Using Nonparametric Methods," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(2), pages 310-345.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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