East Asian Economic Review, 2007 This paper investigates the relevance of skewed Student-t distributions in capturing long memory volatility properties in the daily return series of Japanese financial data (Nikkei 225 Index and JPY-USD exchange rate).
Seong¡-Min Yoon , Sang-Hoon Kang
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Estimating Value-at-Risk for the Turkish Stock Index Futures in the Presence of Long Memory Volatility [PDF]
This paper examines the long memory properties for closing prices of the Turkish stock index futures market using the FIGARCH(1,d,1) model with three different distributions : Normal, Student-t, and skewed Student-t.
Adnan Kasman
core
Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach [PDF]
This paper introduces a new long memory volatility process, denoted by Adaptive FIGARCH , or A-FIGARCH , which is designed to account for both long memory and structural change in the conditional variance process. Structural change is modeled by allowing
Claudio Morana, Richard T. Baillie
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Out-of-sample Forecasting Performance of Won/Dollar Exchange Rate Return Volatility Model
East Asian Economic Review, 2009 We compare the out-of-sample forecasting performance of volatility models using daily exchange rate for the KRW/USD during the period from 1992 to 2008.
Hojin Lee
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Long memory of volatility measures in time series [PDF]
The authors analyse relations between the long memory parameter of conditional variance and estimates of the long memory in squared residuals in FIGARCH models. The investigations are performed by means of simulations FIGARCH(0, d, 0) and FIGARCH(1, d, 1)
Henryk Gurgul, Tomasz Wojtowicz
core
On the Predictability of Green Finance Markets: An Assessment Based on Fractal and Shannon Entropy
Fractal and FractionalEconophysics is an interdisciplinary field that applies physics concepts to economic and financial systems. By utilizing tools such as statistical physics, including fractal analysis and entropy measures, econophysics helps model the complex and non ...
Sonia Benghiat, Salim Lahmiri
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Volatilitetsprediktering och beräkning av Value at Risk med hjälp av FIGARCH [PDF]
, 2016 En av typegenskaperna för finansiell data är dess långa minne och för att modellera detta är Fractionally Integrated GARCH (FIGARCH) en möjlighet. Denna rapport låter FIGARCH jämföra sig med GARCH, IGARCH och EGARCH för volatilitetsprediktering på två ...
Mörée, Felix
core
Bivariate FIGARCH and Fractional Cointegration [PDF]
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.
Christopher L. Gilbert, Celso Brunetti
core
A hybrid ExpAR-FIGARCH-ANN model for time series forecasting
Journal of Statistical Sciences and Computational IntelligenceFinancial time series forecast is challenging due to nonlinear mean dynamics, volatility clustering, and long-memory effects. Traditional hybrid models such as Autoregressive Integrated Moving Average – Generalised Autoregressive Conditional Heteroscedasticity (ARIMA–GARCH) and Fractional Generalised Integrated Autoregressive Conditional ...
Abba Bello Muhammad +5 more
openaire +1 more source
New practice for investors in Chinese stock market: From perspective of fractionally integrated realized GARCH model. [PDF]
Heliyon, 2023 Xiao M, Tao Z, Gu Z, Li Z, Chen X.
europepmc +1 more source