A bootstrap test for the comparison of nonlinear time series - with application to interest rate modelling
| dc.contributor.author | Dette, Holger | |
| dc.contributor.author | Weißbach, Rafael | |
| dc.date.accessioned | 2006-08-07T12:12:30Z | |
| dc.date.available | 2006-08-07T12:12:30Z | |
| dc.date.issued | 2006-08-07T12:12:30Z | |
| dc.description.abstract | We study the drift of stationary diffusion processes in a time series analysis of the autoregression function. A marked empirical process measures the difference between the nonparametric regression functions of two time series. We bootstrap the distribution of a Kolmogorov-Smirnov-type test statistic for two hypotheses: Equality of regression functions and shifted regression functions. Neither markovian behavior nor Brownian motion error of the processes are assumed. A detailed simulation study finds the size of the new test near the nominal level and a good power for a variety of parametric models. The two-sample result serves to test for mean reversion of the diffusion drift in several examples. The interest rates Euribor, Libor as well as T-Bond yields do not show that stylized feature often modelled for interest rates. | en |
| dc.format.extent | 243842 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/2003/22692 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-14438 | |
| dc.language.iso | en | |
| dc.subject | Comparision of conditional expectations | en |
| dc.subject | Cox-Ingersoll-Ross | en |
| dc.subject | Interest rate | en |
| dc.subject | Local linear estimation | en |
| dc.subject | Mean reversion | en |
| dc.subject | Nonparametric autoregressive time series | en |
| dc.subject | Ornstein-Uhlenbeck | en |
| dc.subject | Wild bootstrap | en |
| dc.subject.ddc | 004 | |
| dc.title | A bootstrap test for the comparison of nonlinear time series - with application to interest rate modelling | en |
| dc.type | Text | de |
| dc.type.publicationtype | report | en |
| dcterms.accessRights | open access |