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...

This paper describes simple econometric methods for the analysis of credit risk and applies them to a data set obtained from credit files taken from six large German universal banks. The paper focuses on (i) binary and ordered probit/logit models which enable the credit analyst to quantify the...

We obtain the global existence and uniqueness result for a one-dimensional back- ward stochastic Riccati equation, whose generator contains a quadratic term of L (the second unknown component). This solves the one-dimensional case of Bismut- Peng's problem which was initially proposed by Bismut...

The choice of a smoothing parameter or bandwidth is crucial when applying non- parametric regression estimators. In nonparametric mean regression various meth- ods for bandwidth selection exists. But in nonparametric quantile regression band- width choice is still an unsolved problem. In this...

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...

SEMIFAR models introduced in Beran (1999) provide a semiparametric modelling framework that enables the data analyst to separate deterministic and stochastic trends as well as short- and long-memory components in an observed time series. A correct distinction between these components, and in...

We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the Gaussian case all kernel M-estimators have the same limiting normal distribution. The motivation behind...

A nonlinear Black-Scholes equation which models transaction costs arising in the hedging of portfolios is discretized semi-implicitly using high order compact finite difference schemes. In particular, the compact schemes of Rigal are generalized. The numerical results are compared to standard...

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...

Nonparametric regression with long-range and antipersistent errors is considered. Local polynomial smoothing is investigated for the estimation of the trend function and its derivatives. It is well known that in the presence of long memory (with a fractional differencing parameter 0 d 1/2),...