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Bayesian semiparametric stochastic volatility modeling
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Cited by:
- Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017.
"Autoregressive Moving Average Infinite Hidden Markov-Switching Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 162-182, April.
- Bauwens, Luc & Carpantier, Jean-François & Dufays, Arnaud, 2015. "Autoregressive moving average infinite hidden markov-switching models," LIDAM Discussion Papers CORE 2015007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc BAUWENS & Jean-François CARPENTIER & Arnaud DUFAYS, 2017. "Autoregressive moving average infinite hidden Markov-switching models," LIDAM Reprints CORE 2836, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017. "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Post-Print hal-01795051, HAL.
- Dimitrakopoulos, Stefanos, 2017. "Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility," Economics Letters, Elsevier, vol. 150(C), pages 10-14.
- Jensen Mark J., 2016.
"Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 455-475, September.
- Mark J. Jensen, 2015. "Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility," FRB Atlanta Working Paper 2015-12, Federal Reserve Bank of Atlanta.
- Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013.
"Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models,"
International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
- Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
- Jensen, Mark J. & Maheu, John M., 2010.
"Bayesian semiparametric stochastic volatility modeling,"
Journal of Econometrics, Elsevier, vol. 157(2), pages 306-316, August.
- Mark J Jensen & John M Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," Working Papers tecipa-314, University of Toronto, Department of Economics.
- Mark J. Jensen & John M. Maheu, 2009. "Bayesian Semiparametric Stochastic Volatility Modeling," Working Paper series 23_09, Rimini Centre for Economic Analysis.
- Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
- Jensen, Mark J. & Maheu, John M., 2013.
"Bayesian semiparametric multivariate GARCH modeling,"
Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
- Mark J. Jensen & John M. Maheu, 2012. "Bayesian Semiparametric Multivariate GARCH Modeling," Working Paper series 48_12, Rimini Centre for Economic Analysis.
- Mark J Jensen & John M Maheu, 2012. "Bayesian semiparametric multivariate GARCH modeling," Working Papers tecipa-458, University of Toronto, Department of Economics.
- Mark J. Jensen & John M. Maheu, 2012. "Bayesian semiparametric multivariate GARCH modeling," FRB Atlanta Working Paper 2012-09, Federal Reserve Bank of Atlanta.
- Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019.
"Bayesian nonparametric sparse VAR models,"
Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
- Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse VAR models," Papers 1608.02740, arXiv.org, revised Oct 2018.
- Burda, Martin & Prokhorov, Artem, 2014.
"Copula based factorization in Bayesian multivariate infinite mixture models,"
Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 200-213.
- Martin Burda & Artem Prokhorov, 2012. "Copula Based Factorization in Bayesian Multivariate Infinite Mixture Models," Working Papers 12012, Concordia University, Department of Economics.
- Martin Burda & Artem Prokhorov, 2013. "Copula Based Factorization in Bayesian Multivariate Infinite Mixture Models," Working Papers tecipa-473, University of Toronto, Department of Economics.
- Fisher, Mark & Jensen, Mark J., 2019.
"Bayesian inference and prediction of a multiple-change-point panel model with nonparametric priors,"
Journal of Econometrics, Elsevier, vol. 210(1), pages 187-202.
- Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
- Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," Working Paper series 18-12, Rimini Centre for Economic Analysis.
- Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
- Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2016.
"A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection,"
Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 814-829.
- Audrone Virbickaite & M. Concepci'on Aus'in & Pedro Galeano, 2013. "A Bayesian Non-Parametric Approach to Asymmetric Dynamic Conditional Correlation Model With Application to Portfolio Selection," Papers 1301.5129, arXiv.org, revised Jan 2014.
- Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2024.
"Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?,"
Finance Research Letters, Elsevier, vol. 67(PB).
- Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2023. "Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?," MPRA Paper 118459, University Library of Munich, Germany.
- Bassetti, Federico & Casarin, Roberto & Leisen, Fabrizio, 2011. "Beta-product Poisson-Dirichlet Processes," DES - Working Papers. Statistics and Econometrics. WS 12160, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Donelli, Nicola & Peluso, Stefano & Mira, Antonietta, 2021. "A Bayesian semiparametric vector Multiplicative Error Model," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
- Roberto León-González, 2019.
"Efficient Bayesian inference in generalized inverse gamma processes for stochastic volatility,"
Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 899-920, September.
- Roberto Leon-Gonzalez, 2014. "Efficient Bayesian Inference in Generalized Inverse Gamma Processes for Stochastic Volatility," Working Paper series 19_14, Rimini Centre for Economic Analysis.
- Roberto Leon-Gonzalez, 2015. "Efficient Bayesian Inference in Generalized Inverse Gamma Processes for Stochastic Volatility," GRIPS Discussion Papers 15-17, National Graduate Institute for Policy Studies.
- Roberto Leon-Gonzalez, 2014. "Efficient Bayesian Inference in Generalized Inverse Gamma Processes for Stochastic Volatility," GRIPS Discussion Papers 14-12, National Graduate Institute for Policy Studies.
- Roberto Leon-Gonzalez, 2018. "Efficient Bayesian Inference in Generalized Inverse Gamma Processes for Stochastic Volatility," GRIPS Discussion Papers 17-16, National Graduate Institute for Policy Studies.
- Jensen, Mark J. & Maheu, John M., 2014.
"Estimating a semiparametric asymmetric stochastic volatility model with a Dirichlet process mixture,"
Journal of Econometrics, Elsevier, vol. 178(P3), pages 523-538.
- Mark J Jensen & John M Maheu, 2012. "Estimating a Semiparametric Asymmetric Stochastic Volatility Model with a Dirichlet Process Mixture," Working Papers tecipa-453, University of Toronto, Department of Economics.
- Mark J. Jensen & John M. Maheu, 2012. "Estimating a Semiparametric Asymmetric Stochastic Volatility Model with a Dirichlet Process Mixture," Working Paper series 45_12, Rimini Centre for Economic Analysis.
- Mark J. Jensen & John M. Maheu, 2012. "Estimating a semiparametric asymmetric stochastic volatility model with a Dirichlet process mixture," FRB Atlanta Working Paper 2012-06, Federal Reserve Bank of Atlanta.
- Griffin, J.E. & Steel, M.F.J., 2011. "Stick-breaking autoregressive processes," Journal of Econometrics, Elsevier, vol. 162(2), pages 383-396, June.
- Delatola, E.-I. & Griffin, J.E., 2013. "A Bayesian semiparametric model for volatility with a leverage effect," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 97-110.
- Fisher, Mark & Jensen, Mark J., 2022.
"Bayesian nonparametric learning of how skill is distributed across the mutual fund industry,"
Journal of Econometrics, Elsevier, vol. 230(1), pages 131-153.
- Mark Fisher & Mark J. Jensen & Paula A. Tkac, 2019. "Bayesian Nonparametric Learning of How Skill Is Distributed across the Mutual Fund Industry," FRB Atlanta Working Paper 2019-3, Federal Reserve Bank of Atlanta.
- Richard Gerlach & Zudi Lu & Hai Huang, 2013. "Exponentially Smoothing the Skewed Laplace Distribution for Value‐at‐Risk Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 534-550, September.
- Raanju R. Sundararajan & Wagner Barreto‐Souza, 2023. "Student‐t stochastic volatility model with composite likelihood EM‐algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 125-147, January.
- Maria Kalli & Jim Griffin, 2015. "Flexible Modeling of Dependence in Volatility Processes," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 102-113, January.
- Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022.
"Forecasting US Inflation Using Bayesian Nonparametric Models,"
Working Papers
22-05, Federal Reserve Bank of Cleveland.
- Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano, 2023. "Forecasting US Inflation Using Bayesian Nonparametric Models," CEPR Discussion Papers 18244, C.E.P.R. Discussion Papers.
- Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022. "Forecasting US Inflation Using Bayesian Nonparametric Models," Papers 2202.13793, arXiv.org.
- Federico Bassetti & Roberto Casarin & Marco Del Negro, 2022.
"A Bayesian Approach to Inference on Probabilistic Surveys,"
Staff Reports
1025, Federal Reserve Bank of New York.
- Bassetti, Federico & Casarin, Roberto & Del Negro, Marco, 2024. "A Bayesian Approach for Inference on Probabilistic Surveys," CEPR Discussion Papers 19426, C.E.P.R. Discussion Papers.
- Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024.
"Bayesian forecasting in economics and finance: A modern review,"
International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
- Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
- Ausín, M. Concepción & Galeano, Pedro & Ghosh, Pulak, 2014.
"A semiparametric Bayesian approach to the analysis of financial time series with applications to value at risk estimation,"
European Journal of Operational Research, Elsevier, vol. 232(2), pages 350-358.
- Galeano, Pedro & Ghosh, Pulak, 2010. "A semiparametric Bayesian approach to the analysis of financial time series with applications to value at risk estimation," DES - Working Papers. Statistics and Econometrics. WS ws103822, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Darjus Hosszejni & Gregor Kastner, 2019. "Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol," Papers 1906.12123, arXiv.org, revised Feb 2021.
- Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
- Frank C. Z. Wu, 2024. "Bayesian collapsed Gibbs sampling for a stochastic volatility model with a Dirichlet process mixture," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 697-704, June.
- Mark J. Jensen & John M. Maheu, 2018.
"Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis,"
JRFM, MDPI, vol. 11(3), pages 1-29, September.
- Jensen, Mark J & Maheu, John M, 2013. "Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis," MPRA Paper 52132, University Library of Munich, Germany.
- Mark J. Jensen & John M. Maheu, 2014. "Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis," Working Paper series 31_14, Rimini Centre for Economic Analysis.
- Mark J. Jensen & John M. Maheu, 2014. "Risk, Return, and Volatility Feedback: A Bayesian Nonparametric Analysis," FRB Atlanta Working Paper 2014-6, Federal Reserve Bank of Atlanta.
- Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2018.
"Bayesian Nonparametric Calibration and Combination of Predictive Distributions,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 675-685, April.
- Roberto Casarin & Federico Bassetti & Francesco Ravazzolo, 2015. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Working Papers 2015:04, Department of Economics, University of Venice "Ca' Foscari".
- Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2015. "Bayesian nonparametric calibration and combination of predictive distributions," Working Paper 2015/03, Norges Bank.
- Chan, Joshua C.C., 2013.
"Moving average stochastic volatility models with application to inflation forecast,"
Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
- Joshua C C Chan, 2012. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," ANU Working Papers in Economics and Econometrics 2012-591, Australian National University, College of Business and Economics, School of Economics.
- Joshua C.C. Chan, 2013. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," CAMA Working Papers 2013-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Wang, Nianling & Lou, Zhusheng, 2023. "Sequential Bayesian analysis for semiparametric stochastic volatility model with applications," Economic Modelling, Elsevier, vol. 123(C).
- Roberto Casarin & Domenico Sartore & Marco Tronzano, 2018. "A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 101-114, January.
- Shang, Yuhuang & Zheng, Tingguo, 2021. "Mixed-frequency SV model for stock volatility and macroeconomics," Economic Modelling, Elsevier, vol. 95(C), pages 462-472.
- Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
- Bassetti, Federico & Casarin, Roberto & Leisen, Fabrizio, 2014.
"Beta-product dependent Pitman–Yor processes for Bayesian inference,"
Journal of Econometrics, Elsevier, vol. 180(1), pages 49-72.
- Federico Bassetti & Roberto Casarin & Fabrizio Leisen, 2013. "Beta-Product Dependent Pitman-Yor Processes for Bayesian Inference," Working Papers 2013:13, Department of Economics, University of Venice "Ca' Foscari".
- Burda, Martin & Harding, Matthew & Hausman, Jerry, 2008.
"A Bayesian mixed logit-probit model for multinomial choice,"
Journal of Econometrics, Elsevier, vol. 147(2), pages 232-246, December.
- Martin Burda & Matthew C. Harding & Jerry Hausman, 2008. "A Bayesian mixed logit-probit model for multinomial choice," CeMMAP working papers CWP23/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Martina Danielova Zaharieva & Mark Trede & Bernd Wilfling, 2017. "Bayesian semiparametric multivariate stochastic volatility with an application to international stock-market co-movements," CQE Working Papers 6217, Center for Quantitative Economics (CQE), University of Muenster.
- Jim Griffin & Maria Kalli & Mark Steel, 2018. "Discussion of “Nonparametric Bayesian Inference in Applications”: Bayesian nonparametric methods in econometrics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 207-218, June.
- Huang, Shirley J. & Yu, Jun, 2010.
"Bayesian analysis of structural credit risk models with microstructure noises,"
Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2259-2272, November.
- Shirley J. Huang & Jun Yu, "undated". "Bayesian Analysis of Structural Credit Risk Models with Microstructure Noises," Working Papers CoFie-07-2008, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
- Shirley J. Huang & Jun Yu, 2009. "Bayesian Analysis of Structural Credit Risk Models with Microstructure Noises," Finance Working Papers 23054, East Asian Bureau of Economic Research.
- Chenxing Li & John M. Maheu & Qiao Yang, 2024.
"An infinite hidden Markov model with stochastic volatility,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2187-2211, September.
- Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
- Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
- Roland Langrock & Théo Michelot & Alexander Sohn & Thomas Kneib, 2015. "Semiparametric stochastic volatility modelling using penalized splines," Computational Statistics, Springer, vol. 30(2), pages 517-537, June.
- Omar Abbara & Mauricio Zevallos, 2022. "Maximum Likelihood Inference for Asymmetric Stochastic Volatility Models," Econometrics, MDPI, vol. 11(1), pages 1-18, December.
- Zu, Yang & Boswijk, H. Peter, 2017. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 53-75.
- Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse seemingly unrelated regression model (SUR)," Working Papers 2016:20, Department of Economics, University of Venice "Ca' Foscari".
- Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper series 59_12, Rimini Centre for Economic Analysis, revised Sep 2012.
- Casarin Roberto & Peruzzi Antonio, 2024. "A Dynamic Latent-Space Model for Asset Clustering," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 379-402, April.
- Yang, Qiao, 2019. "Stock returns and real growth: A Bayesian nonparametric approach," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 53-69.
- Lopes, Hedibert F., 2014. "Particle learning for Bayesian non-parametric Markov Switching Stochastic Volatility model," DES - Working Papers. Statistics and Econometrics. WS ws142819, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Yong Song & Tomasz Wo'zniak, 2020. "Markov Switching," Papers 2002.03598, arXiv.org.
- Peluso, Stefano & Mira, Antonietta & Muliere, Pietro, 2015. "Reinforced urn processes for credit risk models," Journal of Econometrics, Elsevier, vol. 184(1), pages 1-12.