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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
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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
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An Overview of FIGARCH and Related Time Series Models
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
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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
Investigating Volatility Dynamics of the Portugal Stock Market using FIGARCH Models [PDF]
Annals of Dunarea de Jos University. Fascicle I : Economics and Applied Informatics, 2023 The act of modeling and forecasting stock market volatility has become essential to risk management practice; it has become one of the most prevalent subjects in financial econometrics and has been mainly and continuously used in the valuation of ...
Santosh KUMAR +4 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
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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
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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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Equilibrium bifurcation and extreme risk in the EU carbon futures market [PDF]
HeliyonConsidering the long-term memory and volatility clustering of the European Union (EU) Carbon Emission Allowances (EUA) futures returns, based on the economy–energy–environment system perspective and the assumption of investors' heterogeneity, this study ...
Junlong Mi +3 more
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