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Persistent link: https://www.econbiz.de/10000168636
Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns Abstract: Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regression (SVR) procedure to forecast nonlinear ARMA model based simulated data...
Persistent link: https://www.econbiz.de/10003770766
asymptotic normality. Simulation evidence strongly corroborates with the asymptotic theory. -- Bandwidths ; B spline ; knots …
Persistent link: https://www.econbiz.de/10008905999
We consider a difference based ridge regression estimator and a Liu type estimator of the regression parameters in the partial linear semiparametric regression model, y = Xβ + f + Both estimators are analysed and compared in the sense of mean-squared error. We consider the case of independent...
Persistent link: https://www.econbiz.de/10008906011
In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions. The method is based on the bootstrap, where resampling is done from a suitably estimated empirical density function (edf) for residuals. It is known that the approximation error...
Persistent link: https://www.econbiz.de/10003952788
Persistent link: https://www.econbiz.de/10003693057
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...
Persistent link: https://www.econbiz.de/10009425497
Classical asset allocation methods have assumed that the distribution of asset returns is smooth, well behaved with stable statistical moments over time. The distribution is assumed to have constant moments with e.g., Gaussian distribution that can be conveniently parameterised by the first two...
Persistent link: https://www.econbiz.de/10011349525
We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression imputation estimator and an empirical likelihood based one for the mean of the response variable are defined. Both the estimators are proved to be asymptotically normal, with...
Persistent link: https://www.econbiz.de/10009620774
Additive modelling has been widely used in nonparametric regression to circumvent the "curse of dimensionality", by reducing the problem of estimating a multivariate regression function to the estimation of its univariate components. Estimation of these univariate functions, however, can suffer...
Persistent link: https://www.econbiz.de/10009626746