A bootstrap test for the comparison of nonlinear time series - with application to interest rate modelling
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Date
2006-08-07T12:12:30Z
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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.
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Comparision of conditional expectations, Cox-Ingersoll-Ross, Interest rate, Local linear estimation, Mean reversion, Nonparametric autoregressive time series, Ornstein-Uhlenbeck, Wild bootstrap