This note gives a fairly complete statistical description of the Hodrick-Prescott Filter (1997), originally proposed by Leser (1961). It builds on an approach to seasonal adjustment suggested by Leser (1963) and Schlicht (1981, 1984). A moments estimator for the smoothing parameter is proposed...

The estimation of models with time-varying coefficients is usually performed by Kalman-Bucy filtering. The two-sided filter proposed by Schlicht (1988) is statistically and computationally superior to the one-sided Kalman-Bucy filter. This paper describes the estimation procedure and the program...

Given a dictionary of Mn initial estimates of the unknown true regression function, we aim to construct linearly aggregated estimators that target the best performance among all the linear combinations under a sparse q-norm (0 = q = 1) constraint on the linear coefficients. Besides identifying...

In this paper we derive adaptive non-parametric rates of concentration of the posterior distributions for the density model on the class of Sobolev and Besov spaces. For this purpose, we build prior models based on wavelet or Fourier expansions of the logarithm of the density. The prior models...

We consider the model selection problem for ergodic diffusion processes based on sampled data. The adaptive estimators for parameters of drift and diffusion coefficients are used in order to construct Akaike’s information criterion (AIC) type model selection statistics. Asymptotic properties...

There is an increasing demand for models of multivariate time-series with time-varying and non-Gaussian dependencies. The available models suffer from the curse of dimensionality or from restrictive assumptions on the parameters and distributions. A promising class of models is that of...

We propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error score function obtained from the residuals of a preliminary nonparametric regression. We show that our estimator is asymptotically equivalent to the infeasible local maximum...

This paper offers a new approach for estimation and forecasting of the volatility of financial time series. No assumption is made about the parametric form of the processes, on the contrary we only suppose that the volatility can be approximated by a constant over some interval. In such a...

This paper analyzes short term portfolio investment opportunities in a capital market where a currency is defined as a currency basket, i.e. a linear combination of foreign currencies. In line with the mean-variance hedging approach, we determine a self-financed optimal investment strategy which...

The increasing works on parameter instability, structural changes and regime switches lead to the natural research question whether the assumption of stationarity is appropriate to model volatility processes. Early econometric studies have provided testing procedures of covariance stationarity...