Results 11 to 20 of about 2,269 (199)
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
doaj +2 more sources
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
core +9 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
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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
doaj +2 more sources
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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Direct versus iterated multiperiod Value‐at‐Risk forecasts
Journal of Economic Surveys, Volume 37, Issue 3, Page 915-949, July 2023., 2023 Abstract Since the late nineties, the Basel Accords require financial institutions to measure their financial risk by reporting daily predictions of Value at Risk (VaR) based on 10‐day returns. However, a vast part of the related literature deals with VaR predictions based on one‐period returns.
Esther Ruiz, María Rosa Nieto
wiley +1 more source
Volatility and dynamic dependence modeling: Review, applications, and financial risk management
WIREs Computational Statistics, Volume 14, Issue 5, September/October 2022., 2022 Moving 20‐day window dynamic risks of Alphabet Inc. (GOOGL), the Bank of America Corporation (BAC), and the Coca‐Cola Company (KO) during 26 December 2017 to 31 December 2020. Abstract Since the introduction of ARCH models close to 40 years ago, a wide range of models for volatility estimation and prediction have been developed and integrated into ...
Mike K. P. So +3 more
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