Fund-of-funds (FoF) managers face the task of selecting a (relatively) small number of hedge funds from a large universe of candidate funds. We analyse whether such a selection can be successfully achieved by looking at the track records of the available funds alone, using advanced statistical...

Semiparametric partially linear models are advantageous to use in empirical studies of various economic problems due to a special feature such that both the parametric and nonparametric components can simultaneously exist in the model. However, a systematic estimation procedure and method have...

This paper proposes a simple and improved nonparametric unit-root test. An asymptotic distribution of the proposed test is established. Finite sample comparisons with an existing nonparametric test are discussed. Some issues about possible extensions are outlined

This paper considers a general model specification between a parametric co-integrating model and a nonparametric co-integrating model in a multivariate regression model, which involves a univariate integrated time series regressor and a vector of stationary time series regressors. A new and...

This paper considers model-free hypothesis testing and confidence interval construction for conditional quantiles of time series. A new method, which is based on inversion of the smoothed empirical likelihood of the conditional distribution function around the local polynomial estimator, is...

We propose novel misspecification tests of semiparametric and fully parametric univariate diffusion models based on the estimators developed in Kristensen (Journal of Econometrics, 2010). We first demonstrate that given a preliminary estimator of either the drift or the diffusion term in a...

A novel estimation method for two classes of semiparametric scalar diffusion models is proposed: In the first class, the diffusion term is parameterised and the drift is left unspecified, while in the second class only the drift term is specified. Under the assumption of stationarity, the...

We consider a particular concept of accuracy of predictions, and we develop a class of non-parametric, spectral density tests capable of deciding whether a given random variable can predict a time series. Under standard assumptions, we show that those tests are consistent, robust and admissible....

We consider the fully extended local Whittle estimator of the fractional order of integration d proposed by Abadir, Distaso and Giraitis (2007), and the extended parametric Whittle estimator suggested by Shao (2010). They are valid under stationarity as well as nonstationarity: a priori...