Results 31 to 40 of about 170 (137)
Cumhuriyet Science JournalThe research delved into analysing the stochastic characteristics of Nigeria's Real GDP, the exchange rate of the Naira to US Dollar, and the inflation rate employing Autoregressive fractionally integrated moving average (ARFIMA) and the Autoregressive ...
Ayoade Adewole
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INTERNATIONAL TOURISTS’ EXPENDITURES IN THAILAND: A MODELLING OF THE 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 +5 more
doaj
Structural Breaks and Long Memory Property in Korean Won Exchange Rates: Adaptive FIGARCH Model
East Asian Economic Review, 2011 This paper explores the issue of structural breaks and long memory property in the conditional variance process of the Korean exchange rates. To analyze the above in detail, this paper examines the dynamics of the structural breaks and the long memory in
Young Wook Han
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Frontiers in Applied Mathematics and StatisticsThis study addresses the limitations of the Kalman Filter (KF) by extending the application of the Unscented Kalman Filter (UKF) and the variational Bayes method (VBM) for estimating long-memory (LM) volatility models.
Kisswell Basira +2 more
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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 +5 more
doaj
A Hybrid LSTM Neural Network Approach for Modeling Periodical Long-Memory Characteristics in Financial Energy Index Time Series [PDF]
Mathematics and Modeling in FinanceForecasting financial market volatility has always been a major challenge in economics and financial engineering. In this study, a hybrid approach based on FIGARCH and PLM-GARCH models combined with Long Short-Term Memory (LSTM) neural networks is ...
Minou Yari +2 more
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Australian Economic Papers, Volume 65, Issue 3, Page 222-260, September 2026.ABSTRACT This study examines volatility interconnectedness among selected agricultural commodities and precious/industrial metals, together with oil price uncertainty and global supply chain pressure, over the period January 1998 to June 2024 using a Quantile‐on‐Quantile connectedness framework.
Muhammed Benli, Halil Altıntaş
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Does the Oil Market Volatility have Long Run Memory? [PDF]
Pizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān, 2011 This paper has examined the long memory of oil market volatility. For this purpose, the paper has employed different types of long run ARCH models including FIGARCH-BBM, FIGARCH-chung, FIEGARCH, FIAPARCH-BBM and FIAPARCH-chung and short run ones ...
Seed Rasekhi, Amir Khanalipour
doaj
Argomenti: Rivista di Economia, Cultura e Ricerca Sociale, 2020 We explore the time-varying conditional correlations of the Sovereing CDS spread returns for Germany, France, China and Japan against USA. We employ a cDCC-AR-FIGARCH model in order to capture potential contagion effects between the markets during the ...
Konstantinos Tsiaras, Theodore Simos
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Forecasting Carbon Prices: A Literature Review
Journal of Forecasting, Volume 45, Issue 2, Page 496-529, March 2026.ABSTRACT Carbon emissions trading is utilized by a growing number of states as a significant tool for addressing greenhouse gas emissions (GHG), global warming problem and the climate crisis. Accurate forecasting of carbon prices is essential for effective policy design and investment strategies in climate change mitigation.
Konstantinos Bisiotis +2 more
wiley +1 more source