Academic literature on the topic 'Time-Varying Multivariate GARCH Models'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Time-Varying Multivariate GARCH Models.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Time-Varying Multivariate GARCH Models"
Klepáč, Václav, and David Hampel. "Assessing Efficiency of D-Vine Copula ARMA-GARCH Method in Value at Risk Forecasting: Evidence from PSE Listed Companies." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 63, no. 4 (2015): 1287–95. http://dx.doi.org/10.11118/actaun201563041287.
Full textTeulon, Frederic, Khaled Guesmi, and Salma Fattoum. "Is There A Difference Between Domestic And Foreign Risk Premium? The Case Of China Stock Market." Journal of Applied Business Research (JABR) 30, no. 5 (August 26, 2014): 1287. http://dx.doi.org/10.19030/jabr.v30i5.8785.
Full textMootamri, Imène. "Long Memory Process in Asset Returns with Multivariate GARCH Innovations." Economics Research International 2011 (September 7, 2011): 1–15. http://dx.doi.org/10.1155/2011/564952.
Full textFengler, Matthias R., and Helmut Herwartz. "Measuring Spot Variance Spillovers when (Co)variances are Time-varying - The Case of Multivariate GARCH Models." Oxford Bulletin of Economics and Statistics 80, no. 1 (May 16, 2017): 135–59. http://dx.doi.org/10.1111/obes.12191.
Full textShiferaw, Yegnanew A. "Time-varying correlation between agricultural commodity and energy price dynamics with Bayesian multivariate DCC-GARCH models." Physica A: Statistical Mechanics and its Applications 526 (July 2019): 120807. http://dx.doi.org/10.1016/j.physa.2019.04.043.
Full textWU, EDMOND H. C., PHILIP L. H. YU, and W. K. LI. "VALUE AT RISK ESTIMATION USING INDEPENDENT COMPONENT ANALYSIS-GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (ICA-GARCH) MODELS." International Journal of Neural Systems 16, no. 05 (October 2006): 371–82. http://dx.doi.org/10.1142/s0129065706000779.
Full textPradhan, Kailash. "The Hedging Effectiveness of Stock Index Futures: Evidence for the S&P CNX Nifty Index Traded in India." South East European Journal of Economics and Business 6, no. 1 (April 1, 2011): 111–23. http://dx.doi.org/10.2478/v10033-011-0010-2.
Full textBurda, Martin, and Louis Bélisle. "Copula multivariate GARCH model with constrained Hamiltonian Monte Carlo." Dependence Modeling 7, no. 1 (June 3, 2019): 133–49. http://dx.doi.org/10.1515/demo-2019-0006.
Full textMetsileng, Lebotsa Daniel, Ntebogang Dinah Moroke, and Johannes Tshepiso Tsoku. "The Application of the Multivariate GARCH Models on the BRICS Exchange Rates." Academic Journal of Interdisciplinary Studies 9, no. 4 (July 10, 2020): 23. http://dx.doi.org/10.36941/ajis-2020-0058.
Full textLinton, Oliver B., and Yang Yan. "Semi- and Nonparametric ARCH Processes." Journal of Probability and Statistics 2011 (2011): 1–17. http://dx.doi.org/10.1155/2011/906212.
Full textDissertations / Theses on the topic "Time-Varying Multivariate GARCH Models"
Grziska, Martin. "Multivariate GARCH and dynamic copula models for financial time series." Diss., Ludwig-Maximilians-Universität München, 2014. http://nbn-resolving.de/urn:nbn:de:bvb:19-179219.
Full textNoureldin, Diaa. "Essays on multivariate volatility and dependence models for financial time series." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:fdf82d35-a5e7-4295-b7bf-c7009cad7b56.
Full textAndersson-Säll, Tim, and Johan Lindskog. "A STUDY ON THE DCC-GARCH MODEL’S FORECASTING ABILITY WITH VALUE-AT-RISK APPLICATIONS ON THE SCANDINAVIAN FOREIGN EXCHANGE MARKET." Thesis, Uppsala universitet, Statistiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-375201.
Full textGrziska, Martin [Verfasser], and Stefan [Akademischer Betreuer] Mittnik. "Multivariate GARCH and dynamic copula models for financial time series : with an application to emerging markets / Martin Grziska. Betreuer: Stefan Mittnik." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2014. http://d-nb.info/1068460628/34.
Full textGrziska, Martin Verfasser], and Stefan [Akademischer Betreuer] [Mittnik. "Multivariate GARCH and dynamic copula models for financial time series : with an application to emerging markets / Martin Grziska. Betreuer: Stefan Mittnik." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2014. http://nbn-resolving.de/urn:nbn:de:bvb:19-179219.
Full textSeerattan, Dave Arnold. "The effectiveness of central bank interventions in the foreign exchange market." Thesis, Brunel University, 2012. http://bura.brunel.ac.uk/handle/2438/7361.
Full textGuesmi, Khaled. "Dynamique d'intégration des marchés boursiers émergents." Thesis, Paris 10, 2011. http://www.theses.fr/2011PA100169.
Full textThe purpose of this thesis is to study the dynamics of the global integration process of four emerging market regions into the world and the regional market, while taking into account the importance of exchange rate and local market risk. An international capital asset pricing model suitable for partially integrated markets and departure from purchasing power parity was developed in the spirit of Bekaert and Harvey (1995)’s regime-switching model in order to explain the time-variations in expected returns on regional emerging market indices. In its fully functional form, the model allows the market integration measure as well as the global and local risk premiums to vary through time. We mainly find that the integration degree in emerging market regions (Latin America, Asia, Southeastern Europe, and the Middle East) varied widely through time over the period 1996-2008 and is satisfactorily explained by global, regional and national factors. Even though it reaches fairly high values during several periods, and exhibit an upward trend towards the end of the estimation period, the emerging market regions under consideration still remain segmented from the world and regional market. These results thus suggest that diversification into emerging market assets continue to produce substantial profits and that the asset pricing rules should reflect a state of partial integration. Our investigation, which addresses the evolution and formation of total risk premiums, confirm this empirically
Wu, Hao. "Forecasting the time-varying beta of UK and US firms: evidence from GARCH and non-GARCH models." Thesis, University of Southampton, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.494769.
Full textLiu, Yi. "Time-Varying Coefficient Models for Recurrent Events." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/97999.
Full textPHD
Sørensen, Steffen. "Estimation of time-varying risk premia on stock market indices and exchange rates pricing macroeconomic variables : a multivariate GARCH-in-mean approach." Thesis, University of York, 2004. http://etheses.whiterose.ac.uk/10957/.
Full textBooks on the topic "Time-Varying Multivariate GARCH Models"
Prado, Raquel. Multistate models for mental fatigue. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.29.
Full textBook chapters on the topic "Time-Varying Multivariate GARCH Models"
Silvennoinen, Annastiina, and Timo Teräsvirta. "Multivariate GARCH Models." In Handbook of Financial Time Series, 201–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-71297-8_9.
Full textLütkepohl, Helmut. "Multivariate ARCH and GARCH Models." In New Introduction to Multiple Time Series Analysis, 557–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-27752-1_16.
Full textWu, Edmond H. C., and Philip L. H. Yu. "Volatility Modelling of Multivariate Financial Time Series by Using ICA-GARCH Models." In Lecture Notes in Computer Science, 571–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11508069_74.
Full textČížek, Pavel, and Vladimir Spokoiny. "Varying Coefficient GARCH Models." In Handbook of Financial Time Series, 169–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-71297-8_7.
Full textKridsadarat, Muttalath. "Estimating Time-Varying Systematic Risk by Using Multivariate GARCH." In Uncertainty Analysis in Econometrics with Applications, 227–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35443-4_16.
Full textGrimm, Kevin J., and Ross Jacobucci. "Individually Varying Time Metrics in Latent Change Score Models 1." In Longitudinal Multivariate Psychology, 61–79. New York, NY : Routledge, 2019. | Series: Multivariate applications series |: Routledge, 2018. http://dx.doi.org/10.4324/9781315160542-4.
Full textFranceschini, Cinzia, and Nicola Loperfido. "A skewed GARCH-type model for multivariate financial time series." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 143–52. Milano: Springer Milan, 2010. http://dx.doi.org/10.1007/978-88-470-1481-7_15.
Full textChu, Jingjia, Reg Kulperger, and Hao Yu. "Modelling the Common Risk Among Equities: A Multivariate Time Series Model with an Additive GARCH Structure." In Advanced Statistical Methods in Data Science, 205–18. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2594-5_12.
Full text"Multivariate GARCH models." In Multivariate Time Series Analysis and Applications, 203–35. Chichester, UK: John Wiley & Sons, Ltd, 2019. http://dx.doi.org/10.1002/9781119502951.ch6.
Full textGuidolin, Massimo, and Manuela Pedio. "Multivariate GARCH and Conditional Correlation Models." In Essentials of Time Series for Financial Applications, 229–66. Elsevier, 2018. http://dx.doi.org/10.1016/b978-0-12-813409-2.00006-6.
Full textConference papers on the topic "Time-Varying Multivariate GARCH Models"
Yu Lin and Yanxiang Chen. "Notice of Retraction: Study on time varying conditional correlations of stock market returns based on multivariate GARCH model." In 2010 IEEE International Conference on Advanced Management Science (ICAMS). IEEE, 2010. http://dx.doi.org/10.1109/icams.2010.5553092.
Full textXifra-Porxas, Alba, Kyriaki Kostoglou, Sara Lariviere, Guiomar Niso, Michalis Kassinopoulos, Marie-Helene Boudrias, and Georgios D. Mitsis. "Identification of Time-Varying Cortico-cortical and Cortico-Muscular Coherence during Motor Tasks with Multivariate Autoregressive Models." In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018. http://dx.doi.org/10.1109/embc.2018.8512475.
Full textPoli, Michael, Jinkyoo Park, and Ilija Ilievski. "WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/630.
Full textBhattacharjya, Debarun, Dharmashankar Subramanian, and Tian Gao. "State Variable Effects in Graphical Event Models." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/592.
Full textElinger, Jared D., and Jonathan D. Rogers. "Information Theoretic Tools for Parameter Estimation and Model Order Reduction for Mechanical Systems." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-70744.
Full text