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 new edition of this classic title, now in its seventh edition, presents a balanced and
comprehensive introduction to the theory, implementation, and practice of time series …

We examine “realized” daily equity return volatilities and correlations obtained from high-
frequency intraday transaction prices on individual stocks in the Dow Jones Industrial …

Using high-frequency data on deutschemark and yen returns against the dollar, we construct
model-free estimates of daily exchange rate volatility and correlation that cover an entire …

Amongmanyexcitingdevelopmentsinstatistic…, nonlineartimeseriesanddata-
analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths. In …

Econometric modelling of financial data received a broad interest in the last 20 years and
the literature on ARCH and related models is vast. Starting with the path breaking works by …

This paper studies properties of tests for long memory for general fourth order stationary
sequences. We propose a rescaled variance test based on V/S statistic which is shown to …

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric
methods have received extensive attention in the economics and statistics communities over …

This paper studies a broad class of nonnegative ARCH (∞) models. Sufficient conditions for
the existence of a stationary solution are established and an explicit representation of the …