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We consider nonparametric estimation of the regression function g(*) in a nonlinear regression model Y<sub>t</sub> = g(X<sub>t</sub>) o(X<sub>t</sub>)e<sub>t</sub>, where the regressor X<sub>t</sub> is a nonstationary unit root process and the error e<sub>t</sub> is s sequence of independent and identically distributed (i.i.d.) random variables. With proper...
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We propose a semiparametric measure to estimate systemic interconnectedness across financial institutions based on tail-driven spill-over effects in a ultra-high dimensional framework. Methodologically, we employ a variable selection technique in a time series setting in the context of a...
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Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...
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It is an undisputed fact that weather risk increases over time due to climate change. However, qualification of this statement with regard to the type of weather risk and geographical location is needed. We investigate the application of novel statistical tools for assessing changes in weather...
Persistent link: https://www.econbiz.de/10009379509
We consider theoretical bootstrap "coupling" techniques for nonparametric robust smoothers and quantile regression, and verify the bootstrap improvement. To cope with curse of dimensionality, a variant of "coupling" bootstrap techniques are developed for additive models with both symmetric error...
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