Volatility Estimation via Hidden Markov Models
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- Rossi, Alessandro & Gallo, Giampiero M., 2006. "Volatility estimation via hidden Markov models," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 203-230, March.
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- Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
- Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
- Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022.
"Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model,"
Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
- Pennoni, Fulvia & Bartolucci, Francesco & Forte, Gianfranco & Ametrano, Ferdinando, 2020. "Exploring the dependencies among main cryptocurrency log-returns: A hidden Markov model," MPRA Paper 106150, University Library of Munich, Germany.
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- Markus Eller & Michael Frömmel & Nora Srzentic, 2010. "Private Sector Credit in CESEE: Long-Run Relationships and Short-Run Dynamics," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 50-78.
- AUGUSTYNIAK, Maciej & BAUWENS, Luc & DUFAYS, Arnaud, 2016.
"A New Approach to Volatility Modeling : The High-Dimensional Markov Model,"
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2016042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Arnaud Dufays & Maciej Augustyniak & Luc Bauwens, 2016. "A new approach to volatility modeling: the High-Dimensional Markov model," Cahiers de recherche 1609, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
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"Volatility Regimes in Central and Eastern European Countries’ Exchange Rates,"
Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(1), pages 2-21, February.
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- M. Frömmel, 2007. "Volatility Regimes in Central and Eastern European Countries’ Exchange Rates," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/487, Ghent University, Faculty of Economics and Business Administration.
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- Michael C. Fu & Bingqing Li & Rongwen Wu & Tianqi Zhang, 2020. "Option Pricing Under a Discrete-Time Markov Switching Stochastic Volatility with Co-Jump Model," Papers 2006.15054, arXiv.org.
- Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
- L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).
- Carlos A. Abanto‐Valle & Roland Langrock & Ming‐Hui Chen & Michel V. Cardoso, 2017. "Maximum likelihood estimation for stochastic volatility in mean models with heavy‐tailed distributions," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(4), pages 394-408, August.
- Xun Huang & Huiyue Tang, 2022. "Measuring multi‐volatility states of financial markets based on multifractal clustering model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 422-434, April.
- Dias, José G. & Vermunt, Jeroen K. & Ramos, Sofia, 2015. "Clustering financial time series: New insights from an extended hidden Markov model," European Journal of Operational Research, Elsevier, vol. 243(3), pages 852-864.
- Langrock, Roland & MacDonald, Iain L. & Zucchini, Walter, 2012. "Some nonstandard stochastic volatility models and their estimation using structured hidden Markov models," Journal of Empirical Finance, Elsevier, vol. 19(1), pages 147-161.
- Francesco Bartolucci & Silvia Bacci & Fulvia Pennoni, 2014. "Longitudinal analysis of self-reported health status by mixture latent auto-regressive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(2), pages 267-288, February.
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More about this item
Keywords
Stochastic volatility; Hidden Markov; GARCH; Smile-consistent option pricing; Forecasting.;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2002-07-10 (Econometrics)
- NEP-ETS-2002-07-04 (Econometric Time Series)
- NEP-FIN-2002-07-04 (Finance)
- NEP-FMK-2002-07-04 (Financial Markets)
Statistics
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