Reducing the Bias of the Smoothed Log Periodogram Regression for Financial High-Frequency Data

Bootstrapping the log-periodogram regression

Semiparametric estimation of the memory parameter in economic time series raises the problem of the small sample size and the poor approximation of the asymptotic distribution to the finite sample counterpart. This paper considers the bootstrap to improve the finite sample distribution of the popular log peridogram regression and shows that it can significantly reduce the error in the coverage ...

Log-periodogram regression in asymmetric long memory

Unit Root Log Periodogram Regression By

Log periodogram (LP) regression is shown to be consistent and to have a mixed normal limit distribution when the memory parameter d 1⁄4 1. Gaussian errors are not required. The proof relies on a new result showing that asymptotically infinite collections of discrete Fourier transforms (dft’s) of a short memory process at the fundamental frequencies in the vicinity of the origin can be treated a...

study of cohesive devices in the textbook of english for the students of apsychology by rastegarpour

this study investigates the cohesive devices used in the textbook of english for the students of psychology. the research questions and hypotheses in the present study are based on what frequency and distribution of grammatical and lexical cohesive devices are. then, to answer the questions all grammatical and lexical cohesive devices in reading comprehension passages from 6 units of 21units th...

Nonlinear Log-periodogram Regression for Perturbed Fractional Processes

This paper studies fractional processes that may be perturbed by weakly dependent time series. The model for a perturbed fractional process has a components framework in which there may be components of both long and short memory. All commonly used estimates of the long memory parameter (such as log periodogram (LP) regression) may be used in a components model where the data are affected by we...