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A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model
Kang, Jian; Jakobsen, Johan Stax; Silvennoinen, Annastiina - In: Econometrics : open access journal 10 (2022) 3, pp. 1-41
simulation. An empirical example involving daily returns of 26 stocks included in the Dow Jones stock index is given. …
Persistent link: https://www.econbiz.de/10013459316
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Testing for a serial correlation in VaR failures through the exponential autoregressive conditional duration model
Małecka, Marta - In: Statistics in transition : an international journal of … 22 (2021) 1, pp. 145-162
Although regulatory standards, currently developed by the Basel Committee on Banking Supervision, anticipate a shift from VaR to ES, the evaluation of risk models currently remains based on the VaR measure. Motivated by the Basel regulations, we address the issue of VaR backtesting and...
Persistent link: https://www.econbiz.de/10012487146
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Building multivariate time-varying smooth transition correlation GARCH models, with an application to the four largest Australian banks
Hall, Anthony; Silvennoinen, Annastiina; Teräsvirta, Timo - In: Econometrics : open access journal 11 (2023) 1, pp. 1-37
This paper proposes a methodology for building Multivariate Time-Varying STCC-GARCH models. The novel contributions in this area are the specification tests related to the correlation component, the extension of the general model to allow for additional correlation regimes, and a detailed...
Persistent link: https://www.econbiz.de/10014281494
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Asymptotic and finite sample properties for multivariate rotated GARCH models
Asai, Manabu; Chang, Chia-Lin; McAleer, Michael; … - In: Econometrics : open access journal 9 (2021) 2, pp. 1-21
This paper derives the statistical properties of a two-step approach to estimating multivariate rotated GARCH-BEKK (RBEKK) models. From the definition of RBEKK, the unconditional covariance matrix is estimated in the first step to rotate the observed variables in order to have the identity...
Persistent link: https://www.econbiz.de/10012547429
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L1 regularization for high-dimensional multivariate GARCH models
Yao, Sijie; Zou, Hui; Xing, Haipeng - In: Risks : open access journal 12 (2024) 2, pp. 1-29
carry out simulation studies to show the performance of the proposed inference framework and the procedure for selecting … tuning parameters. In addition, we apply the proposed framework to analyze volatility spillover and portfolio optimization …
Persistent link: https://www.econbiz.de/10014497339
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Oil hedging with a multivariate semiparametric value-at-risk portfolio
Živkov, Dejan; Manić, Slavica; Đurašković, Jasmina; … - In: Borsa Istanbul Review 22 (2022) 6, pp. 1118-1131
This paper minimizes the risk of Brent oil in a multivariate portfolio, with three risk-minimizing goals: variance, parametric value-at-risk (VaR), and semiparametric value-at-risk. Brent oil is combined with five emerging ASEAN (Association of Southeast Asian Nations) stock indexes and five...
Persistent link: https://www.econbiz.de/10014305873
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Volatility modelling and VaR : the case of Bitcoin, Ether and Ripple
Ječmínek, Jakub; Kukalová, Gabriela; Moravec, Lukáš - In: Danube : law and economics review 11 (2020) 3, pp. 253-269
GARCH-type models dominate as VaR estimators the overall objective of this paper is to perform comprehensive volatility and … VaR estimation for three major digital assets and conclude which method gives the best results in terms of risk management …. The methods we used are parametric (GARCH and EWMA model), non-parametric (historical VaR) and Monte Carlo simulation …
Persistent link: https://www.econbiz.de/10012309770
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Cointegrated portfolios and volatility modeling in the cryptocurrency market
Gabriel, Stefan; Kunst, Robert M. - 2024
volatility and the spread used for trading. The results of the trading strategies suggest that cointegrated portfolios based on … part of the econometric analysis explores Granger causality between volatility and the spread. For this analysis, we … implement two types of forecasting models for Bitcoin volatility: the GARCH (generalized autoregressive conditional …
Persistent link: https://www.econbiz.de/10014495264
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Long memory in the volatility of selected cryptocurrencies: Bitcoin, Ethereum and Ripple
Soylu, Pınar Kaya; Okur, Mustafa; Çatıkkaş, Özgür; … - In: Journal of risk and financial management : JRFM 13 (2020) 6/107, pp. 1-20
This paper examines the volatility of cryptocurrencies, with particular attention to their potential long memory …
Persistent link: https://www.econbiz.de/10012305060
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COVID-19 pandemic and Romanian stock market volatility : a GARCH approach
Gherghina, Ștefan Cristian; Armeanu, Daniel Ștefan; … - In: Journal of risk and financial management : JRFM 14 (2021) 8, pp. 1-29
This paper investigates the volatility of daily returns on the Romanian stock market between January 2020 and April … 2021. Volatility is analyzed by means of the representative index for Bucharest Stock Exchange (BSE), namely, the Bucharest … GARCH approach. In the survey, the GARCH model (1,1) was applied to explore the volatility of the BET and BSE traded shares …
Persistent link: https://www.econbiz.de/10012626337