Results 31 to 40 of about 3,114 (262)
Collateralised option pricing in a South African context: A Univariate GARCH approach
Cogent Economics & Finance, 2022 In this paper, the generalised autoregressive heteroskedasticity (GARCH) model is applied to the pricing of collateralised options in the South African equity market. Symmetric GARCH and nonlinear asymmetric GARCH (AGARCH) models are considered.
Pierre J Venter +2 more
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Stochastic Volatility Modeling of Daily Streamflow Time Series
Water Resources Research, 2023 Under the changing climate, the natural characteristics of hydrological processes are assumed to have been intensified, and the volatility of these processes to have increased significantly.
Huimin Wang +4 more
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A note on GARCH model identification
Computers & Mathematics with Applications, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Melody Ghahramani, A. Thavaneswaran
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An algorithm for nonparametric GARCH modelling [PDF]
Computational Statistics & Data Analysis, 2002 A simple iterative algorithm for nonparametric first-order GARCH modelling is proposed. This method offers an alternative to fitting one of the many different parametric GARCH specifications that have been proposed in the literature. A theoretical justification for the algorithm is provided and examples of its application to simulated data from various
Bühlmann, Peter, McNeil, Alexander J.
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The Scientific World Journal, 2014 The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes.
Melike Bildirici, Özgür Ersin
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Enhancing the Efficiency of Time Series Forecasting by Hybrid Univariate Box Jenkins–GARCH Models [PDF]
The Egyptian Statistical JournalDue to the high non-linearity and volatility of the data, financial time series forecasting has been classified as a standard problem. The current study presents a method for modeling stationary, non-stationary, non-linear, and high volatility time ...
Mona Abdel Bary
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Mathematics, 2023 Forecasting stock markets is an important challenge due to leptokurtic distributions with heavy tails due to uncertainties in markets, economies, and political fluctuations.
Özgür Ömer Ersin, Melike Bildirici
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Volatility Modeling of Emerging Foreign Exchange Market: A Case of Bangladesh [PDF]
Journal of International Logistics and Trade, 2013 This paper examined the volatility models for exchange rate return, including Random Walk model, AR model, GARCH model and extensive GARCH model, with Normal and Student-t distribution assumption as well as nonparametric specification test of these ...
Laila Arjuman Ara +1 more
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Forecasting the Volatility of the Cryptocurrency Market by GARCH and Stochastic Volatility
Mathematics, 2021 This study examines the volatility of nine leading cryptocurrencies by market capitalization—Bitcoin, XRP, Ethereum, Bitcoin Cash, Stellar, Litecoin, TRON, Cardano, and IOTA-by using a Bayesian Stochastic Volatility (SV) model and several GARCH models ...
Jong-Min Kim, Chulhee Jun, Junyoup Lee
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Prominent Movement Disorders in RNU2‐2‐Related Spliceosomopathy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Pediatric movement disorders often overlap with neurodevelopmental diseases, suggesting shared molecular mechanisms. Variants in small nuclear RNA (snRNA) genes encoding spliceosome components have recently been associated with neurodevelopmental disorders, termed “RNUopathies.” We analyzed genome sequencing data from 14 patients with ...
Magdalena Krygier +6 more
wiley +1 more source