Showing 1 - 10 of 19
This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that, without additional assumptions, it is not possible to estimate the average treatment effect and treatment on the treated. It is, however,...
Persistent link: https://www.econbiz.de/10010321721
This paper considers simultaneous modelling of seasonality, slowly changing un- conditional variance and conditional heteroskedasticity in high-frequency fiancial returns. A new approach, called a seasonal SEMIGARCH model, is proposed to perform this by introducing multiplicative seasonal and...
Persistent link: https://www.econbiz.de/10010323932
In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparametric trend and maximum likelihood estimation of the parameters. For selecting the bandwidth, the proposal of Beran and Feng (1999) based...
Persistent link: https://www.econbiz.de/10010324024
This paper focuses on developing a new data-driven procedure for decomposing seasonal time series based on local regression. Formula of the asymptotic optimal bandwidth hA in the current context is given. Methods for estimating the unknowns in hA are investigated. A data-driven algorithm for...
Persistent link: https://www.econbiz.de/10010324043
Persistent link: https://www.econbiz.de/10010324049
Prediction in time series models with a trend requires reliable estima- tion of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because boundary corrections are included implicitly. However, outliers may lead to unreliable estimates, if...
Persistent link: https://www.econbiz.de/10010324063
Persistent link: https://www.econbiz.de/10010324074
In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparamet- ric trend and maximum likelihood estimation of the parameters. Convergence and asymptotic properties of the proposed algorithms are...
Persistent link: https://www.econbiz.de/10010324077
This paper proposes a semiparametric approach by introducing a smooth scale function into the standard GARCH model so that conditional heteroskedasticity and scale change in a financial time series can be modelled simultaneously. An estimation procedure combining kernel estimation of the scale...
Persistent link: https://www.econbiz.de/10010324081
This paper is written as a supplement to our paper Iterative plug-in algorithms for SEMIFAR models-definition, convergence and asymptotic properties (Beran and Feng, 2001). The purpose of this supplement is to report the detailed simulation results, because it is impossible to include all of...
Persistent link: https://www.econbiz.de/10010324086