This paper focuses on the inference of suitable generally non linear functions in stochastic volatility models. In this context, in order to estimate the variance of the proposed estimators, a moving block bootstrap (MBB) approach is suggested and discussed. Under mild assumptions, we show that the MBB procedure is weakly consistent. Moreover a methodology to choose the optimal length block in the MBB is proposed. Some examples and simulations on the model are also made to show the performance of the proposed procedure
The aim of this paper is to construct bootstrap inference for VaR using a nonparametric bootstrap sc...
The aim of this paper is to construct bootstrap inference for VaR using a nonparametric bootstrap sc...
The aim of this paper is to construct bootstrap inference for VaR using a nonparametric bootstrap sc...
This paper focuses on the inference of suitable generally non linear functions in stochastic volatil...
This paper focuses on the inference of suitable generally non linear functions in stochastic volatil...
This paper focuses on the inference of suitable generally non linear functions in stochastic volatil...
This paper focuses on the inference of suitable generally non linear functions in stochastic volatil...
The present work focuses on the inference in stochastic volatility models. More precisely, estimatio...
The present work focuses on the inference in stochastic volatility models. More precisely, estimatio...
The present work focuses on the inference in stochastic volatility models. More precisely, estimatio...
Many approaches have been proposed for estimating stochastic volatility (SV) models, a number of whi...
In this paper we investigate to what extent the bootstrap can be applied to conditional mean models,...
Stochastic volatility (SV) models provide a means of tracking and forecasting the variance of financ...
First draft: October 2007; This draft: June 2008Using recent advances in the nonparametric estimatio...
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in ...
The aim of this paper is to construct bootstrap inference for VaR using a nonparametric bootstrap sc...
The aim of this paper is to construct bootstrap inference for VaR using a nonparametric bootstrap sc...
The aim of this paper is to construct bootstrap inference for VaR using a nonparametric bootstrap sc...
This paper focuses on the inference of suitable generally non linear functions in stochastic volatil...
This paper focuses on the inference of suitable generally non linear functions in stochastic volatil...
This paper focuses on the inference of suitable generally non linear functions in stochastic volatil...
This paper focuses on the inference of suitable generally non linear functions in stochastic volatil...
The present work focuses on the inference in stochastic volatility models. More precisely, estimatio...
The present work focuses on the inference in stochastic volatility models. More precisely, estimatio...
The present work focuses on the inference in stochastic volatility models. More precisely, estimatio...
Many approaches have been proposed for estimating stochastic volatility (SV) models, a number of whi...
In this paper we investigate to what extent the bootstrap can be applied to conditional mean models,...
Stochastic volatility (SV) models provide a means of tracking and forecasting the variance of financ...
First draft: October 2007; This draft: June 2008Using recent advances in the nonparametric estimatio...
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in ...
The aim of this paper is to construct bootstrap inference for VaR using a nonparametric bootstrap sc...
The aim of this paper is to construct bootstrap inference for VaR using a nonparametric bootstrap sc...
The aim of this paper is to construct bootstrap inference for VaR using a nonparametric bootstrap sc...