When using daily mutual fund returns to study market timing ability, heavy tails and heteroscedasticity significantly challenge the existing methods. We propose a weighted nonparametric measure and test for market timing. The test finds that the traditional parametric inference misclassifies...

When using daily mutual fund returns to study the market timing, heavy tails and heteroscedasticity significantly challenge the existing methods. We to accommodate them, we propose a new measure and an efficient test for market timing ability and find that the traditional test misclassifies...

Motivated by prediction problems for time series with heavy-tailed marginal distributions, we consider methods based on 'local least absolute deviations' for estimating a regression median from dependent data. Unlike more conventional 'local median' methods, which are in effect based on locally...

We re-examine the methods used in estimating comovements among U.S. regional home prices and find that there are insufficient moments to ensure a normal limit necessary for employing the quasi-maximum likelihood estimator. Hence, we propose applying the self- weighted quasi-maximum exponential...