Results 181 to 190 of about 772 (205)

Testing for long memory volatility of Chinese stock markets with FIGARCH model

2014 International Conference on Management Science & Engineering 21th Annual Conference Proceedings, 2014
In this study, the long memory property in the volatility of Chinese stock markets is examined. For this purpose, we applied two semi-parametric tests (GPH and LW) and the FIGARCH model, to four Chinese market indices: Shanghai A, Shanghai B, Shenzhen A and Shenzhen B.
exaly   +2 more sources

An improved FIGARCH model with the fractional differencing operator (1-νL)

Finance Research Letters, 2023
Qunxing Pan, Peng Li, Xiuli Du
exaly   +2 more sources

Integrated ARCH, FIGARCH and AR models: Origins of long memory [PDF]

, 2015
Although the properties of the ARCH(∞) model are well investigated, the existence of long memory FIGARCH and IARCH solution was not established in the literature. These two popular ARCH type models which are widely used in applied literature, were causing theoretical controversy because of the suspicion that other solutions besides the trivial zero one,
Giraitis, Liudas, Surgailis, Donatas, Škarnulis, Andrius   +2 more
openaire   +2 more sources

Modelling long memory and structural breaks in conditional variances: An adaptive FIGARCH approach [PDF]

Journal of Economic Dynamics and Control, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Richard T. Baillie, Claudio Morana
openaire   +4 more sources

Volatility persistence in metal returns: A FIGARCH approach

Journal of Economics and Business, 2012
Abstract This study examines the returns and the long-memory properties of the return volatilities of four metals – copper, gold, platinum, and silver. Daily returns for the January 4, 1999 to March 10, 2009 period are used. Three key issues are addressed: (1) whether the volatility processes exhibit long-run temporal dependence; (2) whether the ...
Steven J. Cochran, Iqbal Mansur, Babatunde Odusami   +2 more
openaire   +1 more source

Accounting for conditional leptokurtosis and closing days effects in FIGARCH models of daily exchange rates [PDF]

Applied Financial Economics, 2002
This paper, estimates FIGARCH models introduced by Baillie et al. (1996a) for the four major daily exchange rates against the USD (DEM, FRF, YEN and the GBP). The former contributions are extended by accounting for the observed kurtosis through a Student-
Christelle Lecourt, Sébastien Laurent, Michel Beine   +2 more
exaly   +2 more sources

Empirical wavelet analysis of tail and memory properties of LARCH and FIGARCH models

Computational Statistics, 2009
The tail index \(\alpha\) and long memory parameter \(d\) are estimated for stationary linear ARCH (LARCH) and fractionally integrated GARCH (FIGARCH) processes with heavy tailed marginal distributions and long memory. The estimates are based on the discrete wavelet transform (DWT). A confidence interval for \(\alpha\) is constructed.
Agnieszka Jach, Piotr Kokoszka
openaire   +2 more sources

Development of out-of-sample forecast formulae for the FIGARCH model

Model Assisted Statistics and Applications
Volatility is a matter of concern for time series modeling. It provides valuable insights into the fluctuation and stability of concerning variables over time. Volatility patterns in historical data can provide valuable information for predicting future behaviour. Nonlinear time series models such as the autoregressive conditional heteroscedastic (ARCH)
Rakshit, Debopam, Paul, Ranjit Kumar
openaire   +1 more source

Volatility in CO2 EUAs returns: a FIGARCH approach

2021
This paper models volatility in CO2 EUA’s emission returns using a FIGARCH approach. Our findings overwhelmingly suggest that conditional variance in CO2 emissions allowance returns is stationary and mean reverting, but with autocorrelations decaying at a hyperbolic rate, thereby a shock to forecast of future conditional variance will be temporary but ...
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Long memory and nonlinearity in conditional variances: A smooth transition FIGARCH model

Journal of Empirical Finance, 2009
Abstract This paper introduces the Smooth Transition version of FIGARCH model which is designed to account for both long memory and nonlinear dynamics in the conditional variance. Nonlinearity is introduced via a logistic transition function. The model can capture smooth changes in the volatility across different regimes as well as asymmetric ...
openaire   +1 more source