Results 91 to 100 of about 2,269 (199)
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
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Fractional Integration in Corporate Social Responsibility Indices: A FIGARCH and HYGARCH Approach
Asian Economic and Financial Review, 2019 This research focuses on studying the return and volatility of CSR indices. Four models namely ARFIMA, ARFIMA-GARCH, ARFIMA-FIGARCH and ARFIMA-HYGARCH were applied to investigate the long-memory process in these indices. This paper provides investors with knowledge of CSR indices’ time-series data structure, and identifies the most suitable model for ...
Quynh-Trang Nguyen +3 more
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Symmetric and asymmetric GARCH estimations of the impact of oil price uncertainty on output growth: evidence from the G7. [PDF]
Lett Spat Resour Sci, 2023 Alao RO +5 more
europepmc +1 more source
How Risky Is the Value at Risk? [PDF]
The recent financial crisis has raised numerous questions about the accuracy of value-at-risk (VaR) as a tool to quantify extreme losses. In this paper we present empirical evidence from assessing the out-of-sample performance and robustness of VaR ...
Roxana Chiriac, Winfried Pohlmeier
core
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
core +1 more source
East Asian Economic Review, 2014 This paper examines the effects of financial crises on the long memory volatility dependency of daily exchange returns focusing on the Asian crisis in 97-98 and the Global crisis in 08-09.
Young Wook Han
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The multi-fractal model of asset returns : its estimation via GMM and its use for volatility forecasting [PDF]
Multi-fractal processes have been proposed as a new formalism for modeling the time series of returns in finance. The major attraction of these processes is their ability to generate various degrees of long memory in different powers of returns - a ...
Lux, Thomas
core
FIGARCH Processes: Estimation on volatility in exchange rates of Per´u
Pesquimat, 2019 This research presents a theoretical review of the structure and applica-tion of long memory nature models that combine characteristics of the fractionally integrated processes with the classic GARCH models, thus obtaining the autoregres-sive models with fractionally integrated conditioned heterocedasticity (FIGARCH) which Through the cumulative ...
Briones Zúñiga, José Luis +1 more
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Long Memory Persistence in the Factor of Implied Volatility Dynamics [PDF]
The volatility implied by observed market prices as a function of the strike and time to maturity form an Implied Volatility Surface (IV S). Practical applications require reducing the dimension and characterize its dynamics through a small number of ...
Julius Mungo, Wolfgang Härdle
core
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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