Results 61 to 70 of about 367 (185)

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, Lya Paola Sierra‐Suárez, Pavel Vidal   +2 more
wiley   +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, Ludusan (Corovei) Emilia Anuta, Mutu Simona,   +3 more
doaj  

Sesgos en estimación, tamaño y potencia de una prueba sobre el parámetro de memoria larga en modelos ARFIMA

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, Santiago Alejandro Gallón Gómez, Karoll Gómez Portilla   +2 more
doaj   +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

Macro‐financial linkages in the high‐frequency domain: Economic fundamentals and the Covid‐induced uncertainty channel in US and UK financial markets

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, Menelaos Karanasos, Stavroula Yfanti   +2 more
wiley   +1 more source

Coupling travel characteristics identifying and deep learning for demand forecasting on car‐hailing tourists: A case study of Beijing, China

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, Xiaobing Liu, Yun Wang, Xuedong Yan   +3 more
wiley   +1 more source

Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022

WIREs Data Mining and Knowledge Discovery, Volume 14, Issue 1, January/February 2024.
A review of recent research on the application of deep learning models to price forecast of financial time series, with information on model architectures, applications, advantages and disadvantages, and directions for future research. Abstract Accurately predicting the prices of financial time series is essential and challenging for the financial ...
Cheng Zhang, Nilam Nur Amir Sjarif, Roslina Ibrahim   +2 more
wiley   +1 more source

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
doaj  

Uma avaliação da volatilidade dos preços da soja no mercado internacional com dados de alta frequência An evaluation of the volatility of soybeans prices in the international market using high frequency data

Gestão & Produção, 2012
Neste trabalho foram avaliados os ajustes de cinco modelos para previsão da variância, utilizando-se uma série de preços de soja, uma commodity negociada na bolsa de mercadorias de Chicago (CBOT), com dados de alta frequência. Os modelos utilizados foram
Mario Domingues Simões, Marcelo Cabus Klotzle, Antonio Carlos Figueiredo Pinto, Gabriel Levrini   +3 more
doaj   +1 more source

INTERNATIONAL TOURIST ARRIVALS IN THAILAND: FORECASTING WITH ARFIMA-FIGARCH APPROACH [PDF]

Annals of the University of Petrosani: Economics, 2010
Forecasting is an essential analytical tool for tourism policy andplanning. This paper focuses on forecasting methods based on ARFIMA(p,d,q)-FIGARCH(p,d,q).
KANCHANA CHOKETHAWORN, THANES SRIWICHAILAMPHAN,, SONGSAK SRIBOONCHITTA, CHUKIAT CHAIBOONSRI, JITTAPORN SRIBOONJIT, PRASERT CHAITIP   +5 more
doaj