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Overlaying Time Scales in Financial Volatility Data

Hillebrand, Eric - EconWPA - 2005

financial time series and use it to improve the short-term forecasts from GARCH models. We study different generalizations of … GARCH that allow for several time scales. On our holding sample, none of the considered models can fully exploit the …

Persistent link: https://www.econbiz.de/10005062571

Do Chinese stock markets share common information arrival processes?

Kostov, Philip; Wu, Ziping; McErlean, Seamus - EconWPA - 2004

long memory. This paper uses fractionally integrated GARCH (FIGARCH) to test and account for long memory. The analysis …

Persistent link: https://www.econbiz.de/10005407887

Flexible Seasonal Long Memory and Economic Time Series

Ooms, M. - Erasmus University Rotterdam, Econometric Institute - 1995

We discuss specification, frequency domain estimation and application of flexible fractionally integrated seasonal long memory time series models, which allow for 'chi-squared' (seasonal) unit root testing. We suggest periodogram regression and approximate ML estimation. We successfully apply a...

Persistent link: https://www.econbiz.de/10004972223

Convergence and Persistence of Left-Right Political Orientations in The Netherlands 1978-1995

Eisinga, R.; Franses, Ph.H.B.F.; Ooms, M. - Erasmus University Rotterdam, Econometric Institute - 1997

-Theory- Two theories about trends in left-right political orientations are juxtaposed: the persistence theory claiming that left-right orientations are highly resistant to change versus the irrelevance theory anticipating a move of mass publics towards the center of the left-right continuum....

Persistent link: https://www.econbiz.de/10004972274

A nonlinear long memory model for US unemployment

Dijk, D.J.C. van; Franses, Ph.H.B.F.; Paap, R. - Erasmus University Rotterdam, Econometric Institute - 2000

Two important empirical features of monthly US unemployment are that shocks to the series seem rather persistent and that unemployment seems to rise faster in recessions than that it falls during expansions. To jointly capture these features of long memory and nonlinearity, respectively, we put...

Persistent link: https://www.econbiz.de/10005505011

The long memory story of ex post real interest rates. Can it be supported?

Venetis, Ioannis A.; Duarte, Agustin; Paya, Ivan - EconWPA - 2004

This papers finds evidence of fractional integration for a number of monthly ex post real interest rate series using the GPH semiparametric estimator on data from fourteen European countries and the US. However, we pose empirical questions on certain time series requirements that emerge from...

Persistent link: https://www.econbiz.de/10005407898

An Alternative Maximum Likelihood Estimator of Long-Memeory Processes Using Compactly Supported Wavelets

Jensen, Mark J. - EconWPA - 1997

In this paper we apply compactly supported wavelets to the ARFIMA(p,d,q) long-memory process to develop an alternative maximum likelihood estimator of the differencing parameter, d, that is invariant to the unknown mean and model specification, and to the level of contamination. We show that...

Persistent link: https://www.econbiz.de/10005407968

Modelling Long Memory Volatility in Agricultural Commodity Futures Returns

Tansuchat, R.; Chang, C-L.; McAleer, M.J. - Erasmus University Rotterdam, Econometric Institute - 2009

, coffee, cotton, orange juice, Kansas City wheat, rubber, and palm oil. The class of fractional GARCH models, namely the … FIGARCH model of Baillie et al. (1996), FIEGACH model of Bollerslev and Mikkelsen (1996), and FIAPARCH model of Tse (1998 …), are modelled and compared with the GARCH model of Bollerslev (1986), EGARCH model of Nelson (1991), and APARCH model of …

Persistent link: https://www.econbiz.de/10008570627

An Approximate Wavelet MLE of Short and Long Memory Parameters

Jensen, Mark J. - EconWPA - 1998

By design a wavelet's strength rests in its ability to simultaneously localize a process in time-scale space. The wavelet's ability to localize a time series in time-scale space directly leads to the computational efficiency of the wavelet representation of a N X N matrix operator by allowing...

Persistent link: https://www.econbiz.de/10005119098

Maximum Likelihood Estimators for ARMA and ARFIMA Models: A Monte Carlo Study

Hauser, Michael A. - EconWPA - 1998

We analyze by simulation the properties of two time domain and two frequency domain estimators for low order autoregressive fractionally integrated moving average Gaussian models, ARFIMA (p,d,q). The estimators considered are the exact maximum likelihood for demeaned data, EML, the associated...

Persistent link: https://www.econbiz.de/10005119109

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