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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Volatility modelling and accurate minimun capital risk requirements : a comparison among several approaches [PDF]
Journal of Futures Markets, 2007 In this paper we estimate, for several investment horizons, minimum capital risk requirements for short and long positions, using the unconditional distribution of three daily indexes futures returns and a set of GARCH-type and stochastic volatility ...
Grané, Aurea, Veiga, Helena
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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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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
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Modelling High-Frequency Volatility with Three-State FIGARCH Models [PDF]
SSRN Electronic Journal, 2013 Abstract Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity (FIGARCH) models have enjoyed considerable popularity over the past decade because of their ability to capture the features of volatility clustering and long-memory persistence.
Shi, Yanlin, Ho, Kin-Yip
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Bivariate FIGARCH and Fractional Cointegration [PDF]
SSRN Electronic Journal, 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, Christopher L. Gilbert
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Analytic Hessian matrices and the computation of FIGARCH estimates [PDF]
Statistical Methods & Applications, 2002 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
LOMBARDI M., GALLO, GIAMPIERO MARIA
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DEVELOPING THE HYBRID ARIMA- FIGARCH MODEL FOR TIME SERIES ANALYSIS
FUDMA JOURNAL OF SCIENCES, 2023 This study takes into account the newly developed hybrid ARIMA-FIGARCH. We use the daily price index of the S&P 500. The data employed for this study was secondary in nature for all the variables and was obtained from the publications of the Central Bank of Nigeria Bulletin, the National Bureau of Statistics, and the World Bank Statistics Database,
Musa Usman Bawa +4 more
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سیستم سبدگردان خودکار با استفاده از ترکیب مدلهای پیشبینی تلاطم و مبانی تحلیل تکنیکال [PDF]
راهبرد مدیریت مالی, 2019 یکی از مواردی که درزمینهی خریدوفروش سهام کمتر موردتوجه قرار گرفتهشده، ارائه مدلی خودکار جهت تشکیل سبد سرمایهگذاری بوده که در طول زمان بهصورت پویا عمل کرده و برحسب شرایط بازار اقدام به تصمیمگیری نماید.
سید حجت وکیلی +2 more
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