Applied researchers often want to make inference for the difference of a given performance measure for two investment strategies. In this paper, we consider the class of performance measures that are smooth functions of population means of the underlying returns; this class is very rich and...

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...

Conventional tests of present-value models over-reject the null of no predictability. In order to better account for the intrinsic probability of detecting predictive relations by chance alone, we develop a new nonparametric Monte Carlo testing method, which does not rely on distributional...

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

A new resampling procedure, the continuous-path block bootstrap, is proposed in the context of testing for integrated (unit root) time series. The continuous-path block bootstrap (CBB) is a nonparametric procedure that successfully generates unit root integrated pseudo time series retaining the...

We consider a simple random walk process, a special case ofthe Martingale model, which exhibits a deterministic break in its drift term,for instance, from positive to negative. This particular example can be aplausible model for a time series on exchange rates which displays a persistentcurrency...

We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...

Nonparametric unit-root tests are a useful addendum to the tool-box of time-series analysis. They tend to trade off power for enhanced robustness features. We consider combinations of the RURS (seasonal range unit roots) test statistic and a variant of the level-crossings count. This combination...

We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...

This paper considers a general model specification test for nonlinear multivariate cointegrating regressions where the regressor consists of a univariate integrated time series and a vector of stationary time series. The regressors and the errors are generated from the same innovations, so that...