Discrete Dynamics in Nature and Society, Volume 2026, Issue 1, 2026.Today, the astonishing growth of digital currency has attracted many bold investors. This has caused digital currencies to be gradually introduced as a new asset class with its own criteria. However, the relationship between traditional assets and new assets is not yet deeply understood. This study’s objective is to investigate the dynamic relationship
Farzaneh Shams Tarnabi, Fabio Tramontana
wiley +1 more source
PENERAPAN MODEL ARFIMA-FIAPARCH UNTUK PERAMALAN HARGA SAHAM (Studi Kasus Harga Saham PT Bank Rakyat Indonesia Tbk.) [PDF]
, 2021 Berinvestasi saham dihadapkan dengan risiko tinggi karena harga saham yang cenderung fluktuatif menyebabkan adanya ketidakkonsistenan pada volatilitas dan heteroskedastisitas pada data.
Delyana Meilawati Krismonia, -
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PERAMALAN DATA RUNTUN WAKTU DENGAN PEMODELAN ARFIMA-FIGARCH [PDF]
, 2009 Pemodelan Autoregressive Fractional Integrated Moving Average – Fractional Integrated Generalized Autoregressive Conditional Heteroskedastic (ARFIMA-FIGARCH) adalah salah satu model peramalan dimana data time series mempunyai memori jangka panjang dengan
Selvi Affriani, -
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Long memory behavior in the returns of Pakistan stock market: Arfima-Figarch models [PDF]
, 2014 This study examines the weak-form market efficiency of Pakistan Stock Market namely Karachi Stock Exchange for the period 2010-2013. The efficiency of stock market has tested by using ARFIMA-FIGARCH models estimated under different distribution ...
Turkyilmaz, Serpil, Balibey, Mesut
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ARFIMA-FIGARCH, HYGARCH and FIAPARCH models of exchange rates [PDF]
, 2018 In this paper we apply the parametric approach to testing for dual long memory in daily exchange rate returns (first differences of daily log exchange rates) of twelve currencies against USD (4310 observations).
Zhelyazkova, Slaveya; University of Economics-Varna
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Dual long memory property in returns and volatility: Evidence from the CEE countries' stock markets
, 2009 This paper investigates the presence of long memory in the eight Central and Eastern European (CEE) countries' stock market, using the ARFIMA, GPH, FIGARCH and HYGARCH models.
KASMAN, SAADET +2 more
core +1 more source
An Overview of FIGARCH and Related Time Series Models
, 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
core +1 more source
Long memory in UK real GDP, 1851-2013: An ARFIMA-FIGARCH analysis [PDF]
, 2014 This paper analyses the long-memory properties of both the conditional mean and variance of UK real GDP over the period 1851-2013 by estimating a multivariate ARFIMA-FIGARCH model (with the unemployment rate and inflation as explanatory variables).
Marinko Skare +3 more
core +1 more source
Commonality in the LME aluminium and copper volatility processes through a Figarch lens [PDF]
, 2007 We consider dynamic representation of spot and three month aluminium and copper volatilities. These are the two most important metals traded in the London Metal Exchange (LME).
Figuerola-Ferretti, Isabel +1 more
core +1 more source
Commonality in the LME aluminium and copper volatility processes through a Figarch lens [PDF]
We consider dynamic representation of spot and three month aluminium and copper volatilities. These are the two most important metals traded in the London Metal Exchange (LME).
Christopher L. Gilbert +1 more
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