We consider the asymptotic behavior of log-periodogram regression estimators ofthe memory parameter in long-memory stochastic volatility models, under the nullhypothesis of short memory in volatility. We show that in this situation, if theperiodogram is computed from the log squared returns,...

Difficulties with inference in predictive regressions are generally attributed tostrong persistence in the predictor series. We show that the major source of the problem is actually the nuisance intercept parameter and propose basing inference on the Restricted Likelihood,which is free of such...

We study the small sample behaviour of two goodness-of-fit tests for time series models whichhave been proposed recently in the literature. Both tests are generalizations of the popular Box-Ljung-Pierce portmanteau test, one in the time domain and the other in the frequency domain.The tests are...

Difficulties with inference in predictive regressions are generally attributed to strong persistence in the predictor series. We show that the major source of the problem is actually the nuisance intercept parameter and propose basing inference on the Restricted Likelihood,which is free of such...

Abstract: Difficulties with inference in predictive regressions are generally attributed to strong persistence in the predictor series. We show that the major source of the problem is actually the nuisance intercept parameter and propose basing inference on the Restricted Likelihood, which is...