Results 41 to 50 of about 51,403 (193)
Stock price prediction using combined GARCH-AI models
Scientific AfricanThe non-linear and non-stationary nature of financial time series data poses significant challenges for standalone statistical and neural network methods.
John Kamwele Mutinda +1 more
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Energies, 2020 We propose the use of wavelet-based semiparametric models for forecasting the value-at-risk (VaR) and expected shortfall (ES) in the crude oil market. We compared the forecast outcomes across different time scales for three semiparametric models, three ...
Lu Yang, Shigeyuki Hamori
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Contemporaneous-threshold smooth transition GARCH models [PDF]
, 2011 This paper proposes a contemporaneous-threshold smooth transition GARCH (or C-STGARCH)model for dynamic conditional heteroskedasticity. The C-STGARCH model is a generalization tosecond conditional moments of the contemporaneous smooth transition ...
Dueker, M.J. +3 more
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Traffic Volatility Forecasting Using an Omnibus Family GARCH Modeling Framework
Entropy, 2022 Traffic volatility modeling has been highly valued in recent years because of its advantages in describing the uncertainty of traffic flow during the short-term forecasting process.
Jishun Ou +4 more
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Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2015 The article points out the possibilities of using static D-Vine copula ARMA-GARCH model for estimation of 1 day ahead market Value at Risk. For the illustration we use data of the four companies listed on Prague Stock Exchange in range from 2010 to 2014.
Václav Klepáč, David Hampel
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INVESTIGATING VOLATILITY BEHAVIOUR: EMPIRICAL EVIDENCE FROM ISLAMIC STOCK INDICES
Journal of Islamic Monetary Economics and Finance, 2020 The main purpose of this research is to apply five univariate GARCH models to the daily stock returns of four major sharia stock indices. Two symmetric versions of the GARCH model (GARCH and MGARCH) and three asymmetric versions (EGARCH, TGARCH and ...
Burhanuddin Burhanuddin
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Modeling S&P500 returns with GARCH models
Latin American Journal of Central Banking, 2023 This paper provides several estimates of the GARCH models’ parameters for the S&P500 index, based on returns and CBOE VIX. Using a daily sample collected from 2007 to 2022, we can conclude that adding the VIX information improves the estimates of the ...
Rodrigo Alfaro, Alejandra Inzunza
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Closed-form portfolio optimization under GARCH models
Operations Research Perspectives, 2022 This paper develops an approximate closed-form optimal portfolio allocation formula for a spot asset whose variance follows a GARCH(1,1) process. We consider an investor with constant relative risk aversion (CRRA) utility who wants to maximize the ...
Marcos Escobar-Anel +2 more
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Periodic Long-Memory GARCH Models [PDF]
Econometric Reviews, 2008 A distinguishing feature of the intraday time-varying volatility of financial time series is given by the presence of long-range dependence of periodic type, due mainly to time-of-the-day phenomena. In this work, we introduce a model able to describe the empirical evidence given by this periodic long-memory behaviour.
BORDIGNON, SILVANO +2 more
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Heliyon, 2023 In this paper, based on the Realized GARCH model, the fractional integration Realized GARCH model is proposed by combining long memory parameters with conditional variance and replacing the original realized measure with the realized measure obtained ...
Mei Xiao +4 more
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