Modelling structural breaks, long memory and stock market volatility: an overview - ScienceDirect
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Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

This is the second edition of Climate Time Series Analysis which was first published in 2010.
In this digital age, a second edition means not that the first edition of a book has been sold …

In this article, we investigate the consequences of applying the sieve bootstrap under
regularity conditions that are sufficiently general to encompass both fractionally integrated …

We investigate the performance of a class of semiparametric estimators of the treatment
effect via asymptotic expansions. We derive approximations to the first two moments of the …

The asymptotic refinements attributable to the block bootstrap for time series are not as large
as those of the nonparametric iid bootstrap or the parametric bootstrap. One reason is that …

This paper analyzes the persistence properties of energy consumption in 107 countries over
the 1971–2011 period. It uses subsampling confidence interval methods that are more …

The block bootstrap has been largely developed for weakly dependent time processes and,
in this context, much research has focused on the large-sample properties of block bootstrap …

This paper is concerned with the estimation and construction of confidence intervals for the
impulse response function (IRF) from strongly persistent time series. A non‐parametric, time …

We consider the nonstationary fractional model Δd} X_ {t}= ε_ {t} with ε_ {t} iid (0, σ²) and d>
1/2. We derive an analytical expression for the main term of the asymptotic bias of the …