Nonparametric Estimation of Multifactor Continuous Time Interest-Rate Models
In this paper we study the finite sample properties of the nonparametric method developed by Stanton and later extended by Boudoukh, et al. for the estimation of the drifts and diffusions of multifactor continuous-time term-structure models. Monte Carlo simulations from a known parametric model are employed to calculate the performance of the estimator. The paper focuses on the issue of optimal bandwidth selection. The results suggest that, for persistent data-generating processes exhibiting stochastic volatility, such as interest rate data, a bandwidth function that varies over the surface of the data is optimal. The paper also presents a computationally intensive bandwidth-selection procedure that uses dynamic graphics, combining the computational power of the machine with the pattern-recognition abilities of the human brain. The Monte Carlo simulations require the numeric solution of a system of stochastic differential equations. The paper also presents a nonparametric test for the validity of the solutions. This test is useful in other estimation algorithms, such as the efficient method of moments, where numeric solutions of stochastic differential equations are required. The test is also useful as a tool for understanding how the length of the time step used in the numeric solution of the stochastic differential solutions affects the accuracy of the solution.
|Date of creation:||01 Mar 1999|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://fmwww.bc.edu/CEF99/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- David A. Chapman & Neil D. Pearson, 1998.
"Is the Short Rate Drift Actually Nonlinear?,"
- Hardle, W., 1992.
"Applied Nonparametric Methods,"
9206, Tilburg - Center for Economic Research.
- Härdle, W.K., 1992. "Applied Nonparametric Methods," Discussion Paper 1992-6, Tilburg University, Center for Economic Research.
- Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.
- HÃ„RDLE, Wolfgang, 1992. "Applied nonparametric methods," CORE Discussion Papers 1992003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9204, Catholique de Louvain - Institut de statistique.
- Yacine Ait-Sahalia, 1995.
"Testing Continuous-Time Models of the Spot Interest Rate,"
NBER Working Papers
5346, National Bureau of Economic Research, Inc.
- Ait-Sahalia, Yacine, 1996. "Testing Continuous-Time Models of the Spot Interest Rate," Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 385-426.
- repec:cup:etheor:v:12:y:1996:i:4:p:657-81 is not listed on IDEAS
- Tauchen, George E. & Gallant, A. Ronald, 1995.
"Which Moments to Match,"
95-20, Duke University, Department of Economics.
- Pritsker, Matt, 1998. "Nonparametric Density Estimation and Tests of Continuous Time Interest Rate Models," Review of Financial Studies, Society for Financial Studies, vol. 11(3), pages 449-87.
- Andersen, Torben G. & Lund, Jesper, 1997. "Estimating continuous-time stochastic volatility models of the short-term interest rate," Journal of Econometrics, Elsevier, vol. 77(2), pages 343-377, April.
- Oliver LINTON, .
"Applied nonparametric methods,"
Statistic und Oekonometrie
9312, Humboldt Universitaet Berlin.
When requesting a correction, please mention this item's handle: RePEc:sce:scecf9:111. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.