Results 71 to 80 of about 4,943 (215)
Optimal spectral bandwidth for long memory [PDF]
, 1993 For long range dependent time series with a spectral singularity at frequency zero, a theory for optimal bandwidth choice in non-parametric analysis ofthe singularity was developed by Robinson (1991b).
Delgado, Miguel A., Robinson, Peter M.
core +1 more source
TESTING THE LONG RANGE-DEPENDENCE FOR THE CENTRAL EASTERN EUROPEAN AND THE BALKANS STOCK MARKETS [PDF]
Annals of the University of Oradea: Economic Science, 2013 In this study we tested the existence of long memory in the the return series for major Central Eastern European and Balkans stock markets, using the following statistical methods: Hurst Exponent, GPH method, Andrews and Guggenberger method, Reisen ...
Pece Andreea Maria +3 more
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Lecturas de Economía, 2011 Sesgos en estimación, tamaño y potencia de una prueba sobre el parámetro de memoria larga en modelos ARFIMA Resumen: Castaño et al. (2008) proponen una prueba para investigar la existencia de memoria larga, basada en el parámetro de diferenciación ...
Elkin Castaño Vélez +2 more
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Labor market forecasting in unprecedented times: A machine learning approach
Bulletin of Economic Research, Volume 76, Issue 4, Page 893-915, October 2024.Abstract The COVID‐19 pandemic ushered in unprecedented social and economic conditions, alongside unexpected policy responses, challenging the effectiveness of traditional labor market forecasting approaches. This article presents a novel approach that integrates macroeconomic variables, traditional labor market metrics, and Google search data to ...
Johanna M. Orozco‐Castañeda +2 more
wiley +1 more source
Local Whittle estimation with (quasi‐)analytic wavelets
Journal of Time Series Analysis, Volume 45, Issue 3, Page 421-443, May 2024.In the general setting of long‐memory multivariate time series, the long‐memory characteristics are defined by two components. The long‐memory parameters describe the autocorrelation of each time series. And the long‐run covariance measures the coupling between time series, with general phase parameters.
Sophie Achard, Irène Gannaz
wiley +1 more source
The Use of Weather Variables in the Modeling of Demand for Electricity in One of the Regions in the Southern Poland [PDF]
The main objective of the paper is the verification of usefulness of the ARFIMA-FIGARCH class models in the description of tendencies in the energy consumption in a selected region of the southern Poland taking into consideration weather variables ...
Aneta Wlodarczyk, Marcin Zawada
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International Journal of Finance &Economics, Volume 29, Issue 2, Page 1581-1608, April 2024.Abstract This article contributes to our understanding of the macro‐financial linkages in the high‐frequency domain during the recent health crisis. Building on the extant literature that mainly uses monthly or quarterly macro proxies, we examine the daily economic impact on intra‐daily financial volatility by applying the macro‐augmented HEAVY model ...
Guglielmo Maria Caporale +2 more
wiley +1 more source
IET Intelligent Transport Systems, Volume 18, Issue 4, Page 691-708, April 2024.Based on multi‐source data, this study couples the travel characteristics identifying by introducing a concept of service dependency degree and a Bayesian optimization–long short time memory–convolutional neural network method to conduct the multi‐task online car‐hailing demand prediction. This method is applied to the main scenic spots in Beijing, and
Zile Liu +3 more
wiley +1 more source
Analysing CPI inflation by the fractionally integrated ARFIMA-STVGARCH model [PDF]
The aim of this paper is to study the dynamic evolution of inflation rate. The model is constructed by extending the ARFIMA-GARCH to ARFIMA with a time varying GARCH model where the transition from one regime to another is evolving smoothly over time. We
Imene Mootamri +2 more
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Dynamics of Inflation and Inflation Uncertainty Using ARFIMA- GARCH Model [PDF]
Faslnāmah-i Pizhūhish/Nāmah-i Iqtisādī, 2010 In this paper, we study inflation dynamics and then examine the relation of inflation and inflation uncertainty. At first, for filtering of predictable term of inflation series, we used time series model.
Teymour Mohammadi, Reza Teleblou
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