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.
Claudio Morana, Richard T. Baillie
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Volatility Modeling and Spillover: The Turkish and Russian Stock Markets
Istanbul Business ResearchThis study investigates the internal and external (spillover) characteristics of the volatility of the Turkish and Russian stock market indices. To this end, generalized autoregressive conditional heteroskedasticity models that are classified as short ...
Ahmet Galip Gençyürek
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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
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Modeling Sequences of Long Memory Positive Weakly Stationary Random Variables [PDF]
, 2002 In this paper we introduce a new class of covariance stationary long-memory models on the positive half-line. The overall structure of the models is related to that of GARCH processes of Engle (1982) and Bollerslev (1986), whereby sequence of random ...
Dmitri Koulikov
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Estimation and Prediction of Commodity Returns Using Long Memory Volatility Models
RisksModelling the volatility of commodity prices and creating more reliable models for estimating and forecasting commodity price returns are crucial.
Kisswell Basira +4 more
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Long Memory and FIGARCH Models for Daily and High Frequency Commodity Prices [PDF]
Daily futures returns on six important commodities are found to be well described as FIGARCH fractionally integrated volatility processes, with small departures from the martingale in mean property. The paper also analyzes several years of high frequency
Jeongseok Song +3 more
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Bayesian analysis of FIAPARCH model: an application to São Paulo stock market [PDF]
, 2010 In this paper, we develop a Bayesian analysis of a FIAPARCH(p,d,q) model for parameter estimation and conditional variance prediction. In order to study the inference problem we use the Metropolis-Hastings algorithm.This methodology is illustrated in a ...
Pereira, Isabel, Safadi, Thelma
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The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey [PDF]
The purpose of this study is to test predictive performance of Asymmetric Normal Mixture GARCH (NMAGARCH) and other GARCH models based on Kupiec and Christoffersen tests for Turkish equity market.
Alper Özün, Atilla Çifter
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Dynamic linkages and determinants of sovereign CDS and exchange rates: evidence from G7 and BRICS
Humanities & Social Sciences CommunicationsIn the wake of the COVID-19 pandemic, global public debt has escalated, further intensified by ongoing geopolitical tensions. This paper explores the dynamic relationship between sovereign credit risk and exchange rate fluctuations through the innovative
Min Su +3 more
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VOLATILITY AND VAR FORECASTING FOR THE IBEX-35 STOCK-RETURN INDEX USING FIGARCH-TYPE PROCESSES AND DIFFERENT EVALUATION CRITERIA [PDF]
In this paper I analyze the relative performance of Gaussian and Student-t GARCH and FIGARCH type models for volatility and Value-at-Risk forecasting of daily stock-returns using data from the Spanish equity index IBEX-35.
Trino-Manuel Ñíguez
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