Results 1 to 10 of about 772 (205)
An Overview of FIGARCH and Related Time Series Models [PDF]
Austrian Journal of Statistics, 2016 This paper reviews the theory and applications related to fractionally integrated generalized autoregressive conditional heteroscedastic (FIGARCH) models, mainly for describing the observed persistence in the volatility of a time series.
Maryam Tayefi, T.V. Ramanathan
doaj +3 more sources
Modelling the High Frequency Exchange Rate in Romania with FIGARCH [PDF]
Procedia Economics and Finance, 2014 AbstractRomanian forex market is an emerging market with periods of high volatility. The Romanian exchange rate was for a long term on a depreciating trend in nominal terms interrupted by short bursts of appreciation. The paper applies a FIGARCH model (Beine at al., 2002) for measuring the volatility of exchange rates in order to see how the forex ...
Pelinescu, Elena, Acatrinei, Marius
exaly +3 more sources
Multivariate FIGARCH and long memory process: evidence of oil price markets [PDF]
Management Science Letters, 2015 Oil price markets can benefit from a better considerate of how shocks can affect volatility through time. This study assesses the impact of structural changes and outliers on volatility persistence of two crude oil markets WTI and Brent oil price between
Nadhem Selmi , Nejib Hachicha
doaj +4 more sources
Bivariate FIGARCH and fractional cointegration [PDF]
Journal of Empirical Finance, 2000 We consider the modelling of volatility on closely related markets. Univariate fractional volatility (FIGARCH) models are now standard, as are multivariate GARCH models. In this paper we adopt a combination of the two methodologies. There is as yet little consensus on the methodology for testing for fractional cointegration.
Celso Brunetti
exaly +5 more sources
Modelling time-varying volatility using GARCH models: evidence from the Indian stock market [version 2; peer review: 2 approved] [PDF]
F1000Research, 2022 Background: In this study, we examined the volatility of the Indian stock market from 2008 to 2021. Owing to the financial crisis, volatility forecasting of the Indian stock market has become crucial for economic and financial analysts.
Tarunpreet Kaur +3 more
doaj +2 more sources
Is Bitcoin’s Carbon Footprint Persistent? Multifractal Evidence and Policy Implications [PDF]
Entropy, 2022 The Bitcoin mining process is energy intensive, which can hamper the much-desired ecological balance. Given that the persistence of high levels of energy consumption of Bitcoin could have permanent policy implications, we examine the presence of long ...
Bikramaditya Ghosh, Elie Bouri
doaj +2 more sources
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 +2 more sources
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 +2 more sources
Block Trading Based Volatility Forecasting: An Application of VACD-FIGARCH Model [PDF]
Journal of Asian Finance, Economics and Business (discontinued), 2020 The purpose of this study is to construct the ACD model for the block trading volume duration. The ACD model based on the block trading volume duration is referred to as Volume ACD (VACD) in this study. By integrating with GARCH-type models, the VACD based GARCH type models, which include VACD-GARCH, VACD-IGARCH and VACD-FIGARCH models, are set up ...
Teng-Tsai TU, Chih-Wei LIAO
exaly +2 more sources
A Study of Nigeria Monthly Stock Price Index Using ARTFIMA-FIGARCH Hybrid Model
UMYU Scientifica Journal, 2023 Long memory is a phenomenon in time series analysis that is exhibited by a slow decay of the autocorrelation function. It has been observed that the presence of long memory in both mean and volatility can complicate model fitting and compromise ...
A G Umar, H G Dikko, J Garba, M Tasi’u
doaj +1 more source