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Gregor Kastner

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Feb 2025.

    Cited by:

    1. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.

  2. 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.

    Cited by:

    1. Joseph P. Byrne & Prince Asare Vitenu-Sackey, 2024. "The Macroeconomic Impact of Global and Country-Specific Climate Risk," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(3), pages 655-682, March.
    2. Ioannis Papageorgiou & Ioannis Kontoyiannis, 2023. "The Bayesian Context Trees State Space Model for time series modelling and forecasting," Papers 2308.00913, arXiv.org, revised Aug 2025.
    3. Hernández, Juan R., 2025. "Covered interest parity: A forecasting approach to estimate the neutral band," Economic Modelling, Elsevier, vol. 148(C).
    4. Sylvia Fruhwirth-Schnatter & Peter Knaus, 2022. "Sparse Bayesian State-Space and Time-Varying Parameter Models," Papers 2207.12147, arXiv.org.
    5. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    6. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2018. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Papers 1805.12217, arXiv.org, revised Jul 2019.
    7. Zexuan Yin & Paolo Barucca, 2022. "Variational Heteroscedastic Volatility Model," Papers 2204.05806, arXiv.org.
    8. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Smoothing volatility targeting," Papers 2212.07288, arXiv.org.
    9. Będowska-Sójka, Barbara & Kliber, Agata, 2022. "Can cryptocurrencies hedge oil price fluctuations? A pandemic perspective," Energy Economics, Elsevier, vol. 115(C).
    10. Ewa Feder-Sempach & Piotr Szczepocki & Joanna Bogołębska, 2024. "Global uncertainty and potential shelters: gold, bitcoin, and currencies as weak and strong safe havens for main world stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
    11. David Edmund Allen, 2020. "Stochastic Volatility and GARCH: Do Squared End-of-Day Returns Provide Similar Information?," JRFM, MDPI, vol. 13(9), pages 1-25, September.
    12. Ghaemi Asl, Mahdi & Raheem, Ibrahim D. & Rashidi, Muhammad Mahdi, 2023. "Do stochastic risks flow between industrial and precious metals, Islamic stocks, green bonds, green stocks, clean investments, major foreign exchange rates, and Bitcoin?," Resources Policy, Elsevier, vol. 86(PA).
    13. Helmut Lutkepohl & Fei Shang & Luis Uzeda & Tomasz Wo'zniak, 2024. "Partial Identification of Structural Vector Autoregressions with Non-Centred Stochastic Volatility," Papers 2404.11057, arXiv.org, revised Oct 2025.
    14. Martin, Ertl & Fortin, Ines & Hlouskova, Jaroslava & Koch, Sebastian P. & Kunst, Robert M. & Soegner, Leopold, 2024. "Inflation Forecasting in Turbulent Times," IHS Working Paper Series 56, Institute for Advanced Studies.
      • Martin Ertl & Ines Fortin & Jaroslava Hlouskova & Sebastian P. Koch & Robert M. Kunst & Leopold Sögner, 2025. "Inflation forecasting in turbulent times," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 52(1), pages 5-37, February.
    15. Howard Caulfield & James P. Gleeson, 2024. "Systematic comparison of deep generative models applied to multivariate financial time series," Papers 2412.06417, arXiv.org.
    16. Niko Hauzenberger & Daniel Kaufmann & Rebecca Stuart & Cédric Tille, 2022. "What Drives Long-Term Interest Rates? Evidence from the Entire Swiss Franc History 1852-2020," IRENE Working Papers 22-03, IRENE Institute of Economic Research.
    17. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in international dairy commodity markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(3), pages 704-728, July.
    18. Helmut Lütkepohl & Fei Shang & Luis Uzeda & Tomasz Woźniak, 2025. "Partial Identification of Heteroskedastic Structural Vector Autoregressions: Theory and Bayesian Inference," Staff Working Papers 25-14, Bank of Canada.
    19. Omar Abbara & Mauricio Zevallos, 2022. "Maximum Likelihood Inference for Asymmetric Stochastic Volatility Models," Econometrics, MDPI, vol. 11(1), pages 1-18, December.
    20. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2024. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2126-2145, September.
    21. Helmut Lütkepohl & Fei Shang & Luis Uzeda & Tomasz Woźniak, 2024. "Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference," Discussion Papers of DIW Berlin 2081, DIW Berlin, German Institute for Economic Research.
    22. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Feb 2025.

  3. Gregor Kastner, 2019. "Dealing with Stochastic Volatility in Time Series Using the R Package stochvol," Papers 1906.12134, arXiv.org.

    Cited by:

    1. Álvarez, Emiliano & Brida, Juan Gabriel & Moreno, Leonardo & Sosa, Andrés, 2025. "Comprehensive analysis of the crypto-assets market through multivariate analysis, clustering, and wavelet decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 660(C).
    2. Feldkircher, Martin & Gruber, Thomas & Huber, Florian, 2017. "Spreading the word or reducing the term spread? Assessing spillovers from euro area monetary policy," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168111, Verein für Socialpolitik / German Economic Association.
    3. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    4. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2018. "The transmission of uncertainty shocks on income inequality: State-level evidence from the United States," Working Papers in Regional Science 2018/06, WU Vienna University of Economics and Business.
    5. Dávid Zoltán Szabó & Kata Váradi, 2022. "Margin requirements based on a stochastic correlation model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1797-1820, October.
    6. David E. Allen & Michael McAleer, 2020. "Do We Need Stochastic Volatility and Generalised Autoregressive Conditional Heteroscedasticity? Comparing Squared End-Of-Day Returns on FTSE," Risks, MDPI, vol. 8(1), pages 1-20, February.
    7. Liu, Xinheng & Pan, Sishi & Li, Shuxian & Yang, Xin & Huang, Chuangxia, 2024. "Unraveling the causal impact: Oil price uncertainty on firms’ productivity in China," Resources Policy, Elsevier, vol. 96(C).
    8. Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.
    9. Huber, Florian & Punzi, Maria Teresa, 2020. "International Housing Markets, Unconventional Monetary Policy, And The Zero Lower Bound," Macroeconomic Dynamics, Cambridge University Press, vol. 24(4), pages 774-806, June.
    10. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    11. Liu, Wei-han, 2016. "A re-examination of maturity effect of energy futures price from the perspective of stochastic volatility," Energy Economics, Elsevier, vol. 56(C), pages 351-362.
    12. Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023. "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1673-1699, April.
    13. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    14. Hernández, Juan R., 2020. "Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band," MPRA Paper 100744, University Library of Munich, Germany.
    15. Martin Feldkircher & Florian Huber & Gregor Kastner, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Papers wuwp260, Vienna University of Economics and Business, Department of Economics.
    16. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    17. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2018. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Papers 1805.12217, arXiv.org, revised Jul 2019.
    18. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2022. "Bayesian Modeling of TVP-VARs Using Regression Trees," Papers 2209.11970, arXiv.org, revised May 2023.
    19. Niaz Bashiri Behmiri, Maryam Ahmadi, Juha-Pekka Junttila, and Matteo Manera, 2021. "Financial Stress and Basis in Energy Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    20. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    21. Alok Johri & Shahed Khan & César Sosa-Padilla, 2020. "Interest Rate Uncertainty and Sovereign Default Risk," Working Papers 31, Red Nacional de Investigadores en Economía (RedNIE).
    22. Cross, James L. & Nguyen, Bao H. & Tran, Trung Duc, 2020. "The role of precautionary and speculative demand in the global market for crude oil," Working Papers 2020-02, University of Tasmania, Tasmanian School of Business and Economics.
    23. Peter Knaus & Sylvia Fruhwirth-Schnatter, 2023. "The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models," Papers 2312.10487, arXiv.org, revised Jan 2025.
    24. Arthur T. Rego & Thiago R. dos Santos, 2018. "Non-Gaussian Stochastic Volatility Model with Jumps via Gibbs Sampler," Papers 1809.01501, arXiv.org, revised Oct 2018.
    25. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    26. Darjus Hosszejni & Gregor Kastner, 2019. "Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage," Papers 1901.11491, arXiv.org, revised Nov 2019.
    27. Ines Fortin & Jaroslava Hlouskova & Leopold Sögner, 2023. "Financial and economic uncertainties and their effects on the economy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(2), pages 481-521, May.
    28. Leopold Ringwald & Thomas O. Zörner, 2021. "The money-inflation nexus revisited," Department of Economics Working Papers wuwp310, Vienna University of Economics and Business, Department of Economics.
    29. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
    30. Davidovic, Milivoje, 2021. "From pandemic to financial contagion: High-frequency risk metrics and Bayesian volatility analysis," Finance Research Letters, Elsevier, vol. 42(C).
    31. Maticka, Martin J. & Mahmoud, Thair S., 2025. "Bayesian Belief Networks: Redefining wholesale electricity price modelling in high penetration non-firm renewable generation power systems," Renewable Energy, Elsevier, vol. 239(C).
    32. Huber, Florian & Rabitsch, Katrin, 2019. "Exchange rate dynamics and monetary policy - Evidence from a non-linear DSGE-VAR approach," Department of Economics Working Paper Series 295, WU Vienna University of Economics and Business.
    33. Hauzenberger, Niko & Böck, Maximilian & Pfarrhofer, Michael & Stelzer, Anna & Zens, Gregor, 2018. "Implications of macroeconomic volatility in the Euro area," ESRB Working Paper Series 80, European Systemic Risk Board.
    34. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    35. Hwai-Chung Ho, 2022. "Forecasting the distribution of long-horizon returns with time-varying volatility," Papers 2201.07457, arXiv.org.
    36. Martin Feldkircher & Elizaveta Lukmanova & Gabriele Tondl, 2019. "Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment," Department of Economics Working Papers wuwp289, Vienna University of Economics and Business, Department of Economics.
    37. Thomas Url & Serguei Kaniovski, 2020. "The Potential Capital Requirement for a Minimum Prices Insurance Scheme for Wheat, Maize, and Rape Seed," WIFO Working Papers 601, WIFO.
    38. Gregor Kastner & Sylvia Frühwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Business and Economics Working Papers 234, Unidade de Negocios e Economia, Insper.
    39. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.
    40. Hauzenberger, Niko & Pfarrhofer, Michael & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    41. Rangan Gupta & Florian Huber & Philipp Piribauer, 2018. "Predicting International Equity Returns: Evidence from Time-Varying Parameter Vector Autoregressive Models," Working Papers 201826, University of Pretoria, Department of Economics.
    42. 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.
    43. Huber, Florian & Kaufmann, Daniel, 2016. "Trend Fundamentals and Exchange Rate Dynamics," Department of Economics Working Paper Series 214, WU Vienna University of Economics and Business.
    44. Jong-Min Kim & Chulhee Jun & Junyoup Lee, 2021. "Forecasting the Volatility of the Cryptocurrency Market by GARCH and Stochastic Volatility," Mathematics, MDPI, vol. 9(14), pages 1-16, July.
    45. Zhao, Yixiu & Upreti, Vineet & Cai, Yuzhi, 2021. "Stock returns, quantile autocorrelation, and volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 73(C).
    46. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2021. "The regional transmission of uncertainty shocks on income inequality in the United States," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 887-900.
    47. David Edmund Allen, 2020. "Stochastic Volatility and GARCH: Do Squared End-of-Day Returns Provide Similar Information?," JRFM, MDPI, vol. 13(9), pages 1-25, September.
    48. Jamie L. Cross & Bao H. Nguyen & Trung Duc Tran, 2021. "The Role of Precautionary and Speculative Demand in the Global Market for Crude Oil," Working Papers No 06/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    49. Bogdan Dima & Ștefana Maria Dima, 2024. "The non-linear impact of monetary policy on shifts in economic policy uncertainty: evidence from the United States of America," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 51(3), pages 755-781, August.
    50. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    51. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    52. Tore Selland Kleppe, 2024. "Log‐density gradient covariance and automatic metric tensors for Riemann manifold Monte Carlo methods," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(3), pages 1206-1229, September.
    53. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    54. Jihyun Park & Andrey Sarantsev, 2024. "Zero-Coupon Treasury Rates and Returns using the Volatility Index," Papers 2411.03699, arXiv.org, revised Jan 2025.
    55. Roberto Leon-Gonzalez & Blessings Majon, 2024. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," GRIPS Discussion Papers 24-03, National Graduate Institute for Policy Studies.
    56. Sophie Altermatt & Simon Beyeler, 2018. "Shall We Twist?," Diskussionsschriften dp1825, Universitaet Bern, Departement Volkswirtschaft.
    57. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
    58. Huber, Florian & Kastner, Gregor & Feldkircher, Martin, 2016. "Should I stay or should I go? Bayesian inference in the threshold time varying parameter (TTVP) model," Department of Economics Working Paper Series 235, WU Vienna University of Economics and Business.
    59. Kreuzer, Alexander & Czado, Claudia, 2021. "Bayesian inference for a single factor copula stochastic volatility model using Hamiltonian Monte Carlo," Econometrics and Statistics, Elsevier, vol. 19(C), pages 130-150.
    60. Martin, Ertl & Fortin, Ines & Hlouskova, Jaroslava & Koch, Sebastian P. & Kunst, Robert M. & Soegner, Leopold, 2024. "Inflation Forecasting in Turbulent Times," IHS Working Paper Series 56, Institute for Advanced Studies.
      • Martin Ertl & Ines Fortin & Jaroslava Hlouskova & Sebastian P. Koch & Robert M. Kunst & Leopold Sögner, 2025. "Inflation forecasting in turbulent times," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 52(1), pages 5-37, February.
    61. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    62. Florian Huber & Tam'as Krisztin & Michael Pfarrhofer, 2018. "A Bayesian panel VAR model to analyze the impact of climate change on high-income economies," Papers 1804.01554, arXiv.org, revised Feb 2021.
    63. Karlsson, Sune & Mazur, Stepan, 2020. "Flexible Fat-tailed Vector Autoregression," Working Papers 2020:5, Örebro University, School of Business.
    64. Patrick Aschermayr & Konstantinos Kalogeropoulos, 2023. "Sequential Bayesian Learning for Hidden Semi-Markov Models," Papers 2301.10494, arXiv.org.
    65. De Luigi, Clara & Huber, Florian, 2018. "Debt regimes and the effectiveness of monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 218-238.
    66. Meng, Xiao-Li, 2018. "Conducting highly principled data science: A statistician’s job and joy," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 51-57.
    67. Feldkircher, Martin & Gruber, Thomas & Huber, Florian, 2020. "International effects of a compression of euro area yield curves," Journal of Banking & Finance, Elsevier, vol. 113(C).
    68. Szendrei, Tibor & Eross, Andrea & Mohammed, Mustapha & Ersoy, Erkal, 2024. "Investigating the effect of green finance initiatives on renewable energy penetration in Europe," Accountancy, Economics, and Finance Working Papers 2024-07, Heriot-Watt University, Department of Accountancy, Economics, and Finance.
    69. Bitto, Angela & Frühwirth-Schnatter, Sylvia, 2019. "Achieving shrinkage in a time-varying parameter model framework," Journal of Econometrics, Elsevier, vol. 210(1), pages 75-97.
    70. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    71. Osei K. Tweneboah & Kwesi A. Ohene-Obeng & Maria C. Mariani, 2024. "Characterization and Prediction of the Ghana Stock Exchange Composite Index Utilizing Bayesian Stochastic Volatility Models," Risks, MDPI, vol. 13(1), pages 1-17, December.
    72. Afees A. Salisu & Ahamuefula Ephraim Ogbonna, 2018. "Does time-variation matter in the stochastic volatility components for G7 stock returns," Working Papers 062, Centre for Econometric and Allied Research, University of Ibadan.
    73. Michael Grabchak & Eliana Christou, 2021. "A note on calculating expected shortfall for discrete time stochastic volatility models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-16, December.
    74. Bhattacharya, Arnab & Wilson, Simon P., 2018. "Sequential Bayesian inference for static parameters in dynamic state space models," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 187-203.
    75. Huber, Florian, 2018. "Dealing with heterogeneity in panel VARs using sparse finite mixtures," Department of Economics Working Paper Series 262, WU Vienna University of Economics and Business.
    76. László Márkus & Ashish Kumar & Amina Darougi, 2025. "Creating Tail Dependence by Rough Stochastic Correlation Satisfying a Fractional SDE; An Application in Finance," Mathematics, MDPI, vol. 13(13), pages 1-20, June.
    77. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2024. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2126-2145, September.
    78. Zens, Gregor & Böck, Maximilian & Zörner, Thomas O., 2020. "The heterogeneous impact of monetary policy on the US labor market," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    79. Luo, Weijie & Wang, Yong & Zhang, Xiaoge, 2022. "Monetary policy uncertainty and firm risk-taking," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    80. Gleb Kurovskiy, 2017. "Modelling terms of trade volatility impact on output dynamics in Russia," EcoMod2017 10361, EcoMod.

  4. Darjus Hosszejni & Gregor Kastner, 2019. "Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage," Papers 1901.11491, arXiv.org, revised Nov 2019.

    Cited by:

    1. Cross, Jamie L. & Hou, Chenghan & Trinh, Kelly, 2021. "Returns, volatility and the cryptocurrency bubble of 2017–18," Economic Modelling, Elsevier, vol. 104(C).
    2. 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.
    3. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2024. "A Bayesian approach for the determinants of bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 91(C).
    4. Theodore Panagiotidis & Georgios Papapanagiotou, 2025. "A note on the determinants of non‐fungible tokens returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 30(3), pages 3201-3211, July.

  5. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2018. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Papers 1805.12217, arXiv.org, revised Jul 2019.

    Cited by:

    1. Luis Gruber & Gregor Kastner & Anirban Bhattacharya & Debdeep Pati & Natesh Pillai & David Dunson, 2025. "A note on simulation methods for the Dirichlet-Laplace prior," Papers 2508.11982, arXiv.org.

  6. Gregor Kastner & Sylvia Fruhwirth-Schnatter, 2017. "Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models," Papers 1706.05280, arXiv.org.

    Cited by:

    1. Álvarez, Emiliano & Brida, Juan Gabriel & Moreno, Leonardo & Sosa, Andrés, 2025. "Comprehensive analysis of the crypto-assets market through multivariate analysis, clustering, and wavelet decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 660(C).
    2. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    3. Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2025. "Bayesian neural networks for macroeconomic analysis," Journal of Econometrics, Elsevier, vol. 249(PC).
    4. Rui Luo & Weinan Zhang & Xiaojun Xu & Jun Wang, 2017. "A Neural Stochastic Volatility Model," Papers 1712.00504, arXiv.org, revised Dec 2018.
    5. Antonio A. F. Santos, 2021. "Bayesian Estimation for High-Frequency Volatility Models in a Time Deformed Framework," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 455-479, February.
    6. Andreas Dibiasi & Samad Sarferaz, 2020. "Measuring Macroeconomic Uncertainty: The Labor Channel of Uncertainty from a Cross-Country Perspective," Papers 2006.09007, arXiv.org, revised Dec 2020.
    7. Niko Hauzenberger & Florian Huber & Gary Koop, 2020. "Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods," Papers 2005.03906, arXiv.org, revised May 2023.
    8. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    9. Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
    10. Huber, Florian, 2017. "Structural breaks in Taylor rule based exchange rate models — Evidence from threshold time varying parameter models," Economics Letters, Elsevier, vol. 150(C), pages 48-52.
    11. Chris Redl, 2019. "Uncertainty Matters: Evidence from Close Elections," NBER Chapters, in: NBER International Seminar on Macroeconomics 2019, National Bureau of Economic Research, Inc.
    12. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    13. Sheng, Xin & Gupta, Rangan & Çepni, Oğuzhan, 2022. "The effects of climate risks on economic activity in a panel of US states: The role of uncertainty," Economics Letters, Elsevier, vol. 213(C).
    14. Joseph P. Byrne & Prince Asare Vitenu-Sackey, 2024. "The Macroeconomic Impact of Global and Country-Specific Climate Risk," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(3), pages 655-682, March.
    15. Florian Huber & Maria Teresa Punzi, 2017. "The shortage of safe assets in the US investment portfolio: Some international evidence," Department of Economics Working Papers wuwp243, Vienna University of Economics and Business, Department of Economics.
    16. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2018. "The transmission of uncertainty shocks on income inequality: State-level evidence from the United States," Working Papers in Regional Science 2018/06, WU Vienna University of Economics and Business.
    17. Dávid Zoltán Szabó & Kata Váradi, 2022. "Margin requirements based on a stochastic correlation model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1797-1820, October.
    18. David E. Allen & Michael McAleer, 2020. "Do We Need Stochastic Volatility and Generalised Autoregressive Conditional Heteroscedasticity? Comparing Squared End-Of-Day Returns on FTSE," Risks, MDPI, vol. 8(1), pages 1-20, February.
    19. Nguyen, Hoang & Nguyen, Trong-Nghia & Tran, Minh-Ngoc, 2021. "A dynamic leverage stochastic volatility model," Working Papers 2021:14, Örebro University, School of Business.
    20. Annika Camehl & Tomasz Wo'zniak, 2025. "Time-Varying Identification of Structural Vector Autoregressions," Papers 2502.19659, arXiv.org.
    21. Todd Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model," Working Papers 2307, University of Strathclyde Business School, Department of Economics.
    22. Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
    23. Valeriya V. Lakshina & Andrey M. Silaev, 2016. "Fluke of stochastic volatility versus GARCH inevitability or which model creates better forecasts?," Economics Bulletin, AccessEcon, vol. 36(4), pages 2368-2380.
    24. Huber, Florian & Punzi, Maria Teresa, 2020. "International Housing Markets, Unconventional Monetary Policy, And The Zero Lower Bound," Macroeconomic Dynamics, Cambridge University Press, vol. 24(4), pages 774-806, June.
    25. Florian Huber & Tamas Krisztin & Philipp Piribauer, 2014. "Forecasting Global Equity Indices using Large Bayesian VARs," Department of Economics Working Papers wuwp184, Vienna University of Economics and Business, Department of Economics.
    26. Niko Hauzenberger & Florian Huber & Massimiliano Marcellino & Nico Petz, 2021. "Gaussian Process Vector Autoregressions and Macroeconomic Uncertainty," Papers 2112.01995, arXiv.org, revised Nov 2022.
    27. Sylvia Fruhwirth-Schnatter & Peter Knaus, 2022. "Sparse Bayesian State-Space and Time-Varying Parameter Models," Papers 2207.12147, arXiv.org.
    28. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    29. Liu, Wei-han, 2016. "A re-examination of maturity effect of energy futures price from the perspective of stochastic volatility," Energy Economics, Elsevier, vol. 56(C), pages 351-362.
    30. Chernis Tony, 2024. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 293-317, April.
    31. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    32. Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Predictive Density Combination Using a Tree-Based Synthesis Function," Working Papers 23-30, Federal Reserve Bank of Cleveland.
    33. Zhang, Yixiao & Yu, Cindy L. & Li, Haitao, 2022. "Nowcasting GDP Using Dynamic Factor Model with Unknown Number of Factors and Stochastic Volatility: A Bayesian Approach," Econometrics and Statistics, Elsevier, vol. 24(C), pages 75-93.
    34. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    35. Martin Feldkircher & Florian Huber & Gregor Kastner, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Papers wuwp260, Vienna University of Economics and Business, Department of Economics.
    36. Xin Sheng & Rangan Gupta & Oguzhan Cepni, 2022. "Persistence of State-Level Uncertainty of the United States: The Role of Climate Risks," Working Papers 202208, University of Pretoria, Department of Economics.
    37. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    38. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    39. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    40. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    41. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2018. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Papers 1805.12217, arXiv.org, revised Jul 2019.
    42. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2022. "Bayesian Modeling of TVP-VARs Using Regression Trees," Papers 2209.11970, arXiv.org, revised May 2023.
    43. Niaz Bashiri Behmiri, Maryam Ahmadi, Juha-Pekka Junttila, and Matteo Manera, 2021. "Financial Stress and Basis in Energy Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    44. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    45. Souza, M.A.O. & Migon, H.S. & Pereira, J.B.M., 2018. "Extended dynamic generalized linear models: The two-parameter exponential family," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 164-179.
    46. Crespo Cuaresma, Jesus & Doppelhofer, Gernot & Feldkircher, Martin & Huber, Florian, 2018. "Spillovers from US monetary policy: Evidence from a time-varying parameter GVAR model," Discussion Paper Series in Economics 31/2018, Norwegian School of Economics, Department of Economics.
    47. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    48. Peter Knaus & Sylvia Fruhwirth-Schnatter, 2023. "The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models," Papers 2312.10487, arXiv.org, revised Jan 2025.
    49. Gabriella Conti & Sylvia Frühwirth-Schnatter & James Heckman & Rémi Piatek, 2014. "Bayesian exploratory factor analysis," CeMMAP working papers CWP30/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    50. Boeck, Maximilian & Feldkircher, Martin, 2021. "The Impact of Monetary Policy on Yield Curve Expectations," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 887-901.
    51. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    52. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.
    53. Maximilian Böck & Martin Feldkircher & Florian Huber, 2020. "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R," Globalization Institute Working Papers 395, Federal Reserve Bank of Dallas.
    54. Karin Klieber, 2023. "Non-linear dimension reduction in factor-augmented vector autoregressions," Papers 2309.04821, arXiv.org.
    55. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    56. Franz Xaver Zobl & Martin Ertl, 2021. "The Condemned Live Longer – New Evidence of the New Keynesian Phillips Curve in Central and Eastern Europe," Open Economies Review, Springer, vol. 32(4), pages 671-699, September.
    57. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    58. Darjus Hosszejni & Gregor Kastner, 2019. "Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage," Papers 1901.11491, arXiv.org, revised Nov 2019.
    59. Arnaud Dufays & Aristide Houndetoungan & Alain Coen, 2024. "Selective linear segmentation for detecting relevant parameter changes," Papers 2402.05329, arXiv.org.
    60. Chen Gong & David S. Stoffer, 2021. "A Note on Efficient Fitting of Stochastic Volatility Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(2), pages 186-200, March.
    61. Ines Fortin & Jaroslava Hlouskova & Leopold Sögner, 2023. "Financial and economic uncertainties and their effects on the economy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(2), pages 481-521, May.
    62. Leopold Ringwald & Thomas O. Zörner, 2021. "The money-inflation nexus revisited," Department of Economics Working Papers wuwp310, Vienna University of Economics and Business, Department of Economics.
    63. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
    64. Pantelis Samartsidis & Shaun R. Seaman & Silvia Montagna & André Charlett & Matthew Hickman & Daniela De Angelis, 2020. "A Bayesian multivariate factor analysis model for evaluating an intervention by using observational time series data on multiple outcomes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1437-1459, October.
    65. Nguyen, Hoang & Virbickaite, Audrone, 2022. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Working Papers 2022:5, Örebro University, School of Business.
    66. Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    67. Florian Huber & Gary Koop, 2024. "Fast and order‐invariant inference in Bayesian VARs with nonparametric shocks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1301-1320, November.
    68. Feldkircher Martin & Gruber Thomas & Huber Florian, 2019. "International effects of a compression of euro area yield curves," Working Papers in Economics 2019-1, University of Salzburg.
    69. Andrejs Zlobins, 2019. "Country-Level Effects of the ECB's Expanded Asset Purchase Programme," Working Papers 2019/02, Latvijas Banka.
    70. Rangan Gupta & Jacobus Nel & Afees A. Salisu & Qiang Ji, 2022. "Predictability of Economic Slowdowns in Advanced Countries over Eight Centuries: The Role of Climate Risks," Working Papers 202237, University of Pretoria, Department of Economics.
    71. Cross, Jamie L. & Hou, Chenghan & Trinh, Kelly, 2021. "Returns, volatility and the cryptocurrency bubble of 2017–18," Economic Modelling, Elsevier, vol. 104(C).
    72. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022. "Forecasting US Inflation Using Bayesian Nonparametric Models," Papers 2202.13793, arXiv.org.
    73. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2021. "General Bayesian time-varying parameter VARs for predicting government bond yields," Papers 2102.13393, arXiv.org.
    74. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    75. Zhenya Liu & Shixuan Wang, 2017. "Decoding Chinese stock market returns: Three-state hidden semi-Markov model," Post-Print hal-01794384, HAL.
    76. Markus Eller & Florian Huber & Helene Schuberth, 2018. "How Important are Global Factors for Understanding the Dynamics of International Capital Flows?," Working Papers in Economics 2018-2, University of Salzburg.
    77. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    78. Michele Costola & Matteo Iacopini & Casper Wichers, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," Papers 2310.17473, arXiv.org.
    79. Huber, Florian & Rabitsch, Katrin, 2019. "Exchange rate dynamics and monetary policy - Evidence from a non-linear DSGE-VAR approach," Department of Economics Working Paper Series 295, WU Vienna University of Economics and Business.
    80. Tony Chernis & Niko Hauzenberger & Haroon Mumtaz & Michael Pfarrhofer, 2025. "A Bayesian Gaussian Process Dynamic Factor Model," Papers 2509.04928, arXiv.org.
    81. Philippe Goulet Coulombe & Karin Klieber, 2025. "An Adaptive Moving Average for Macroeconomic Monitoring," Papers 2501.13222, arXiv.org.
    82. Florian Huber & Michael Pfarrhofer, 2020. "Dynamic shrinkage in time-varying parameter stochastic volatility in mean models," Papers 2005.06851, arXiv.org.
    83. Renee van Eyden & Geoffrey Ngene & Oguzhan Cepni & Rangan Gupta, 2022. "The Heterogeneous Impact of Temperature Growth on Real House Price Returns across the US States," Working Papers 202236, University of Pretoria, Department of Economics.
    84. Hauzenberger, Niko & Böck, Maximilian & Pfarrhofer, Michael & Stelzer, Anna & Zens, Gregor, 2018. "Implications of macroeconomic volatility in the Euro area," ESRB Working Paper Series 80, European Systemic Risk Board.
    85. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
    86. Valeria V. Lakshina, 2014. "The Fluke Of Stochastic Volatility Versus Garch Inevitability : Which Model Creates Better Forecasts?," HSE Working papers WP BRP 37/FE/2014, National Research University Higher School of Economics.
    87. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    88. Juan Manuel Julio-Román & Fredy Gamboa-Estrada, 2019. "The Exchange Rate and Oil Prices in Colombia: A High Frequency Analysis," Borradores de Economia 1091, Banco de la Republica de Colombia.
    89. Martin Feldkircher & Florian Huber, 2016. "Unconventional US Monetary Policy: New Tools, Same Channels?," Department of Economics Working Papers wuwp222, Vienna University of Economics and Business, Department of Economics.
    90. Hwai-Chung Ho, 2022. "Forecasting the distribution of long-horizon returns with time-varying volatility," Papers 2201.07457, arXiv.org.
    91. Tomasz Wo'zniak, 2024. "Fast and Efficient Bayesian Analysis of Structural Vector Autoregressions Using the R Package bsvars," Papers 2410.15090, arXiv.org, revised Apr 2025.
    92. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    93. João Pedro Coli de Souza Monteneri Nacinben & Márcio Laurini, 2024. "Multivariate Stochastic Volatility Modeling via Integrated Nested Laplace Approximations: A Multifactor Extension," Econometrics, MDPI, vol. 12(1), pages 1-28, February.
    94. Takuji Kinkyo, 2022. "Hedging capabilities of Bitcoin for Asian currencies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1769-1784, April.
    95. Steff De Visscher & Markus Eberhardt & Gerdie Everaert, 2017. "Measuring productivity and absorptive capacity evolution," Discussion Papers 2017-11, University of Nottingham, GEP.
    96. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    97. Gregor Kastner & Sylvia Frühwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Business and Economics Working Papers 234, Unidade de Negocios e Economia, Insper.
    98. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.
    99. Virbickaitė, Audronė & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian predictive distributions of oil returns using mixed data sampling volatility models," Resources Policy, Elsevier, vol. 86(PA).
    100. Hauzenberger, Niko & Pfarrhofer, Michael & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    101. Rangan Gupta & Florian Huber & Philipp Piribauer, 2018. "Predicting International Equity Returns: Evidence from Time-Varying Parameter Vector Autoregressive Models," Working Papers 201826, University of Pretoria, Department of Economics.
    102. Dong Jin Lee & Minchul Shin & Boyuan Zhang & Molin Zhong, 2017. "Measuring International Uncertainty : The Case of Korea," Finance and Economics Discussion Series 2017-066, Board of Governors of the Federal Reserve System (U.S.).
    103. Huber, Florian & Kaufmann, Daniel, 2016. "Trend Fundamentals and Exchange Rate Dynamics," Department of Economics Working Paper Series 214, WU Vienna University of Economics and Business.
    104. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
    105. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2021. "The regional transmission of uncertainty shocks on income inequality in the United States," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 887-900.
    106. Dima, Bogdan & Dima, Ştefana Maria & Ioan, Roxana, 2025. "The short-run impact of investor expectations’ past volatility on current predictions: The case of VIX," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 98(C).
    107. David Edmund Allen, 2020. "Stochastic Volatility and GARCH: Do Squared End-of-Day Returns Provide Similar Information?," JRFM, MDPI, vol. 13(9), pages 1-25, September.
    108. Naeem, Muhammad Abubakr & Balli, Faruk & Shahzad, Syed Jawad Hussain & de Bruin, Anne, 2020. "Energy commodity uncertainties and the systematic risk of US industries," Energy Economics, Elsevier, vol. 85(C).
    109. Pedro A. Lima & Carlos M. Carvalho & Hedibert F. Lopes & Andrew Herren, 2025. "Minnesota BART," Papers 2503.13759, arXiv.org.
    110. Anzarut, Michelle & Mena, Ramsés H., 2019. "A Harris process to model stochastic volatility," Econometrics and Statistics, Elsevier, vol. 10(C), pages 151-169.
    111. Markus Eller & Florian Huber & Helene Schuberth, 2016. "Understanding the drivers of capital flows into the CESEE countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 79-104.
    112. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org, revised Aug 2024.
    113. Bogdan Dima & Ștefana Maria Dima, 2024. "The non-linear impact of monetary policy on shifts in economic policy uncertainty: evidence from the United States of America," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 51(3), pages 755-781, August.
    114. Stojanović, Vladica S. & Popović, Biljana Č. & Milovanović, Gradimir V., 2016. "The Split-SV model," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 560-581.
    115. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    116. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    117. Niko Hauzenberger & Massimiliano Marcellino & Michael Pfarrhofer & Anna Stelzer, 2024. "Nowcasting with Mixed Frequency Data Using Gaussian Processes," Papers 2402.10574, arXiv.org, revised Sep 2024.
    118. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    119. Sophie Altermatt & Simon Beyeler, 2018. "Shall We Twist?," Diskussionsschriften dp1825, Universitaet Bern, Departement Volkswirtschaft.
    120. Kenji Hatakenaka & Kosuke Oya, 2021. "Bayesian inference for time varying partial adjustment model with application to intraday price discovery," Discussion Papers in Economics and Business 21-19, Osaka University, Graduate School of Economics.
    121. German Rodikov & Nino Antulov-Fantulin, 2023. "Introducing the $\sigma$-Cell: Unifying GARCH, Stochastic Fluctuations and Evolving Mechanisms in RNN-based Volatility Forecasting," Papers 2309.01565, arXiv.org.
    122. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
    123. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2024. "A Bayesian approach for the determinants of bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 91(C).
    124. Helmut Lutkepohl & Fei Shang & Luis Uzeda & Tomasz Wo'zniak, 2024. "Partial Identification of Structural Vector Autoregressions with Non-Centred Stochastic Volatility," Papers 2404.11057, arXiv.org, revised Oct 2025.
    125. Annika Camehl & Tomasz Wo'zniak, 2023. "Time-Varying Identification of Monetary Policy Shocks," Papers 2311.05883, arXiv.org, revised May 2024.
    126. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.
    127. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
    128. Huber, Florian & Kastner, Gregor & Feldkircher, Martin, 2016. "Should I stay or should I go? Bayesian inference in the threshold time varying parameter (TTVP) model," Department of Economics Working Paper Series 235, WU Vienna University of Economics and Business.
    129. Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Renee van Eyden, 2021. "Climate Risks and U.S. Stock-Market Tail Risks: A Forecasting Experiment Using over a Century of Data," Working Papers 202165, University of Pretoria, Department of Economics.
    130. Makoto Nakakita & Teruo Nakatsuma, 2021. "Bayesian Analysis of Intraday Stochastic Volatility Models of High-Frequency Stock Returns with Skew Heavy-Tailed Errors," JRFM, MDPI, vol. 14(4), pages 1-29, March.
    131. Florian Huber, 2014. "Density Forecasting using Bayesian Global Vector Autoregressions with Common Stochastic Volatility," Department of Economics Working Papers wuwp179, Vienna University of Economics and Business, Department of Economics.
    132. Kreuzer, Alexander & Czado, Claudia, 2021. "Bayesian inference for a single factor copula stochastic volatility model using Hamiltonian Monte Carlo," Econometrics and Statistics, Elsevier, vol. 19(C), pages 130-150.
    133. Angelos Alexopoulos & Petros Dellaportas & Omiros Papaspiliopoulos, 2019. "Bayesian prediction of jumps in large panels of time series data," Papers 1904.05312, arXiv.org, revised Apr 2021.
    134. Yuki Toyoshima & Shigeyuki Hamori, 2018. "Measuring the Time-Frequency Dynamics of Return and Volatility Connectedness in Global Crude Oil Markets," Energies, MDPI, vol. 11(11), pages 1-18, October.
    135. Julio-Román, Juan Manuel, 2019. "Estimating the Exchange Rate Pass-Through: A Time-Varying Vector Auto-Regression with Residual Stochastic Volatility Approach," Working papers 21, Red Investigadores de Economía.
    136. Andreas Dibiasi & Samad Sarferaz, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," Post-Print hal-04167343, HAL.
    137. Qiang Zhang & Rui Luo & Yaodong Yang & Yuanyuan Liu, 2018. "Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series," Papers 1811.03711, arXiv.org.
    138. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    139. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2022. "The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area," Finance Research Letters, Elsevier, vol. 46(PA).
    140. Florian Huber & Tam'as Krisztin & Michael Pfarrhofer, 2018. "A Bayesian panel VAR model to analyze the impact of climate change on high-income economies," Papers 1804.01554, arXiv.org, revised Feb 2021.
    141. Karlsson, Sune & Mazur, Stepan, 2020. "Flexible Fat-tailed Vector Autoregression," Working Papers 2020:5, Örebro University, School of Business.
    142. Jorge M. Uribe & Montserrat Guillen, 2020. "Generalized Market Uncertainty Measurement in European Stock Markets in Real Time," Mathematics, MDPI, vol. 8(12), pages 1-11, December.
    143. De Luigi, Clara & Huber, Florian, 2018. "Debt regimes and the effectiveness of monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 218-238.
    144. Sergey Egiev, 2016. "On Persistence of Uncertainty Shocks," HSE Working papers WP BRP 144/EC/2016, National Research University Higher School of Economics.
    145. A. López-Pérez & M. Febrero-Bande & W. González-Manteiga, 2025. "Estimation and specification test for diffusion models with stochastic volatility," Statistical Papers, Springer, vol. 66(2), pages 1-36, February.
    146. Niko Hauzenberger & Daniel Kaufmann & Rebecca Stuart & Cédric Tille, 2022. "What Drives Long-Term Interest Rates? Evidence from the Entire Swiss Franc History 1852-2020," IRENE Working Papers 22-03, IRENE Institute of Economic Research.
    147. Meng, Xiao-Li, 2018. "Conducting highly principled data science: A statistician’s job and joy," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 51-57.
    148. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended New Keynesian Phillips Curve Models with Non-filtered Data," Tinbergen Institute Discussion Papers 13-090/III, Tinbergen Institute.
    149. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    150. Kastner, Gregor, 2016. "Dealing with Stochastic Volatility in Time Series Using the R Package stochvol," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i05).
    151. Eberhardt, Markus & Everaert, Gerdie & De Visscher, Stef, 2017. "Measuring Productivity and Absorptive Capacity Evolution in OECD Economies," CEPR Discussion Papers 12261, C.E.P.R. Discussion Papers.
    152. Bitto, Angela & Frühwirth-Schnatter, Sylvia, 2019. "Achieving shrinkage in a time-varying parameter model framework," Journal of Econometrics, Elsevier, vol. 210(1), pages 75-97.
    153. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2021. "Vector autoregression models with skewness and heavy tails," Working Papers 2021:8, Örebro University, School of Business.
    154. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in international dairy commodity markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(3), pages 704-728, July.
    155. Theodore Panagiotidis & Georgios Papapanagiotou, 2025. "A note on the determinants of non‐fungible tokens returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 30(3), pages 3201-3211, July.
    156. Crespo Cuaresma, Jesús & Huber, Florian & Onorante, Luca, 2020. "Fragility and the effect of international uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 108(C).
    157. Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2025. "Machine learning the macroeconomic effects of financial shocks," Economics Letters, Elsevier, vol. 250(C).
    158. Zhongfang He, 2024. "Locally time-varying parameter regression," Econometric Reviews, Taylor & Francis Journals, vol. 43(5), pages 269-300, May.
    159. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    160. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2020. "Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction," Energy Economics, Elsevier, vol. 92(C).
    161. Nakajima, Jouchi, 2022. "Macroeconomic uncertainty matters: A nonlinear effect of financial volatility on real economic activity," Discussion paper series HIAS-E-121, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    162. Karim Moussa, 2025. "On the Correlations in Linearized Multivariate Stochastic Volatility Models," Tinbergen Institute Discussion Papers 25-021/V, Tinbergen Institute.
    163. Kumar, Utkarsh & Ahmad, Wasim, 2024. "Navigating the “twin titans” of global manufacturing: The impact of US and China on industrial production forecasting in G20 nations," Pacific-Basin Finance Journal, Elsevier, vol. 87(C).
    164. Kim C. Raath & Katherine B. Ensor, 2023. "Wavelet-L2E Stochastic Volatility Models: an Application to the Water-Energy Nexus," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 150-176, May.
    165. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2024. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2126-2145, September.
    166. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang, 2022. "Predicting returns and dividend growth — The role of non-Gaussian innovations," Finance Research Letters, Elsevier, vol. 46(PA).
    167. Zens, Gregor & Böck, Maximilian & Zörner, Thomas O., 2020. "The heterogeneous impact of monetary policy on the US labor market," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    168. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.
    169. Markus Eller & Martin Feldkircher & Florian Huber, 2017. "How would a fiscal shock in Germany affect other European countries? Evidence from a Bayesian GVAR model with sign restrictions," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 1, pages 54-77.
    170. Chaim, Pedro & Laurini, Márcio P., 2019. "Nonlinear dependence in cryptocurrency markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 32-47.
    171. Theodore Panagiotidis & Georgios Papapanagiotou, 2024. "A note on the determinants of NFTs returns," Discussion Paper Series 2024_02, Department of Economics, University of Macedonia, revised Feb 2024.
    172. Sakaria, D.K. & Griffin, J.E., 2017. "On efficient Bayesian inference for models with stochastic volatility," Econometrics and Statistics, Elsevier, vol. 3(C), pages 23-33.
    173. Marín Díazaraque, Juan Miguel & Romero, Eva & Lopes Moreira da Veiga, María Helena, 2025. "Switching the leverage switch," DES - Working Papers. Statistics and Econometrics. WS 47005, Universidad Carlos III de Madrid. Departamento de Estadística.
    174. Costola, Michele & Iacopini, Matteo & Wichers, Casper, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," SAFE Working Paper Series 407, Leibniz Institute for Financial Research SAFE.
    175. Helmut Lütkepohl & Fei Shang & Luis Uzeda & Tomasz Woźniak, 2024. "Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference," Discussion Papers of DIW Berlin 2081, DIW Berlin, German Institute for Economic Research.
    176. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Feb 2025.
    177. Gleb Kurovskiy, 2017. "Modelling terms of trade volatility impact on output dynamics in Russia," EcoMod2017 10361, EcoMod.

  7. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2017. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Papers 1711.00564, arXiv.org, revised Mar 2024.

    Cited by:

    1. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    2. Sylvia Fruhwirth-Schnatter & Peter Knaus, 2022. "Sparse Bayesian State-Space and Time-Varying Parameter Models," Papers 2207.12147, arXiv.org.
    3. Annalisa Cadonna & Sylvia Fruhwirth-Schnatter & Peter Knaus, 2019. "Triple the gamma -- A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models," Papers 1912.03100, arXiv.org.
    4. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    5. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    6. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    7. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    8. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.
    9. Michael Pfarrhofer & Hauzenberger Niko, 2019. "Bayesian state-space modeling for analyzing heterogeneous network effects of US monetary policy," Working Papers in Economics 2019-6, University of Salzburg.
    10. Rangan Gupta & Florian Huber & Philipp Piribauer, 2018. "Predicting International Equity Returns: Evidence from Time-Varying Parameter Vector Autoregressive Models," Working Papers 201826, University of Pretoria, Department of Economics.
    11. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    12. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    13. Crespo Cuaresma, Jesús & Huber, Florian & Onorante, Luca, 2020. "Fragility and the effect of international uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 108(C).
    14. Annalisa Cadonna & Sylvia Frühwirth-Schnatter & Peter Knaus, 2020. "Triple the Gamma—A Unifying Shrinkage Prior for Variance and Variable Selection in Sparse State Space and TVP Models," Econometrics, MDPI, vol. 8(2), pages 1-36, May.
    15. Michael Pfarrhofer & Philipp Piribauer, 2018. "Flexible shrinkage in high-dimensional Bayesian spatial autoregressive models," Papers 1805.10822, arXiv.org.

  8. Gregor Kastner & Florian Huber, 2017. "Sparse Bayesian vector autoregressions in huge dimensions," Papers 1704.03239, arXiv.org, revised Dec 2019.

    Cited by:

    1. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    2. Niko Hauzenberger & Florian Huber & Gary Koop, 2020. "Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods," Papers 2005.03906, arXiv.org, revised May 2023.
    3. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    4. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    5. Chan, Joshua C.C., 2023. "Comparing stochastic volatility specifications for large Bayesian VARs," Journal of Econometrics, Elsevier, vol. 235(2), pages 1419-1446.
    6. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    7. Luis Gruber & Gregor Kastner & Anirban Bhattacharya & Debdeep Pati & Natesh Pillai & David Dunson, 2025. "A note on simulation methods for the Dirichlet-Laplace prior," Papers 2508.11982, arXiv.org.
    8. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using hierarchical aggregation constraints to nowcast regional economic aggregates," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-04, Economic Statistics Centre of Excellence (ESCoE).
    9. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    10. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
    11. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    12. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    13. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2018. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Papers 1805.12217, arXiv.org, revised Jul 2019.
    14. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    15. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    16. Katz, Harrison & Brusch, Kai Thomas & Weiss, Robert E., 2024. "A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1556-1567.
    17. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    18. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.
    19. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    20. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    21. Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
    22. Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    23. Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
    24. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    25. Joshua C. C. Chan & Aubrey Poon & Dan Zhu, 2023. "High-Dimensional Conditionally Gaussian State Space Models with Missing Data," Papers 2302.03172, arXiv.org.
    26. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    27. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-14, Economic Statistics Centre of Excellence (ESCoE).
    28. Pedro A. Lima & Carlos M. Carvalho & Hedibert F. Lopes & Andrew Herren, 2025. "Minnesota BART," Papers 2503.13759, arXiv.org.
    29. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.
    30. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    31. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    32. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    33. Liu, Yixuan & Kirch, Claudia & Lee, Jeong Eun & Meyer, Renate, 2024. "A nonparametrically corrected likelihood for Bayesian spectral analysis of multivariate time series," Computational Statistics & Data Analysis, Elsevier, vol. 199(C).
    34. Ghaemi Asl, Mahdi & Raheem, Ibrahim D. & Rashidi, Muhammad Mahdi, 2023. "Do stochastic risks flow between industrial and precious metals, Islamic stocks, green bonds, green stocks, clean investments, major foreign exchange rates, and Bitcoin?," Resources Policy, Elsevier, vol. 86(PA).
    35. Lai, Wei-Ting & Chen, Ray-Bing & Chen, Ying & Koch, Thorsten, 2022. "Variational Bayesian inference for network autoregression models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    36. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
    37. Simon Beyeler & Sylvia Kaufmann, 2021. "Reduced‐form factor augmented VAR—Exploiting sparsity to include meaningful factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 989-1012, November.
    38. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates," Working Papers 22-06, Federal Reserve Bank of Cleveland.
    39. Florian Huber & Tam'as Krisztin & Michael Pfarrhofer, 2018. "A Bayesian panel VAR model to analyze the impact of climate change on high-income economies," Papers 1804.01554, arXiv.org, revised Feb 2021.
    40. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
    41. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    42. Martin Feldkircher & Karin Klieber, 2024. "Integration or fragmentation? A closer look at euro area financial markets," Chapters, in: Guglielmo M. Caporale (ed.), Handbook of Financial Integration, chapter 19, pages 443-469, Edward Elgar Publishing.
    43. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
    44. Hauber, Philipp, 2022. "Real-time nowcasting with sparse factor models," EconStor Preprints 251551, ZBW - Leibniz Information Centre for Economics.
    45. Yuan Yan & Hsin-Cheng Huang & Marc G. Genton, 2021. "Vector Autoregressive Models with Spatially Structured Coefficients for Time Series on a Spatial Grid," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 387-408, September.
    46. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2024. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2126-2145, September.
    47. Wu, Ping, 2024. "Should I open to forecast? Implications from a multi-country unobserved components model with sparse factor stochastic volatility," International Journal of Forecasting, Elsevier, vol. 40(3), pages 903-917.
    48. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    49. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Feb 2025.

  9. Gregor Kastner & Sylvia Frühwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Business and Economics Working Papers 234, Unidade de Negocios e Economia, Insper.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Sifat, Imtiaz, 2021. "On cryptocurrencies as an independent asset class: Long-horizon and COVID-19 pandemic era decoupling from global sentiments," Finance Research Letters, Elsevier, vol. 43(C).
    3. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    4. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2019. "Decomposing global yield curve co-movement," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 500-513.
    5. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    6. Kinkyo, Takuji, 2021. "Region-wide connectedness of Asian equity and currency markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    7. Chernis Tony, 2024. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 293-317, April.
    8. Zhang, Yixiao & Yu, Cindy L. & Li, Haitao, 2022. "Nowcasting GDP Using Dynamic Factor Model with Unknown Number of Factors and Stochastic Volatility: A Bayesian Approach," Econometrics and Statistics, Elsevier, vol. 24(C), pages 75-93.
    9. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    10. Guanyu Hu & Ming-Hui Chen & Nalini Ravishanker, 2023. "Bayesian analysis of spherically parameterized dynamic multivariate stochastic volatility models," Computational Statistics, Springer, vol. 38(2), pages 845-869, June.
    11. Kinkyo, Takuji, 2022. "The intermediating role of the Chinese renminbi in Asian currency markets: Evidence from partial wavelet coherence," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    12. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    13. Kaufmann, Sylvia & Schumacher, Christian, 2019. "Bayesian estimation of sparse dynamic factor models with order-independent and ex-post mode identification," Journal of Econometrics, Elsevier, vol. 210(1), pages 116-134.
    14. Shi, Yongjing & Tiwari, Aviral Kumar & Gozgor, Giray & Lu, Zhou, 2020. "Correlations among cryptocurrencies: Evidence from multivariate factor stochastic volatility model," Research in International Business and Finance, Elsevier, vol. 53(C).
    15. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    16. Benjamin Poignard & Manabu Asaiz, 2020. "A Penalised OLS Framework for High-Dimensional Multivariate Stochastic Volatility Models," Discussion Papers in Economics and Business 20-02, Osaka University, Graduate School of Economics.
    17. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Working Paper 2018/10, Norges Bank.
    18. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    19. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    20. Ewa Feder-Sempach & Piotr Szczepocki & Joanna Bogołębska, 2024. "Global uncertainty and potential shelters: gold, bitcoin, and currencies as weak and strong safe havens for main world stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
    21. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    22. Mike West, 2020. "Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 1-31, February.
    23. João Pedro Coli de Souza Monteneri Nacinben & Márcio Laurini, 2024. "Multivariate Stochastic Volatility Modeling via Integrated Nested Laplace Approximations: A Multifactor Extension," Econometrics, MDPI, vol. 12(1), pages 1-28, February.
    24. Takuji Kinkyo, 2022. "Hedging capabilities of Bitcoin for Asian currencies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1769-1784, April.
    25. 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.
    26. 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.
    27. 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.
    28. Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Papers 2020_21, Business School - Economics, University of Glasgow.
    29. Lopes, Hedibert F. & McCulloch, Robert E. & Tsay, Ruey S., 2022. "Parsimony inducing priors for large scale state–space models," Journal of Econometrics, Elsevier, vol. 230(1), pages 39-61.
    30. David Edmund Allen, 2020. "Stochastic Volatility and GARCH: Do Squared End-of-Day Returns Provide Similar Information?," JRFM, MDPI, vol. 13(9), pages 1-25, September.
    31. Kishor, N. Kundan & Pratap, Bhanu, 2023. "The Role of Inflation Targeting in Anchoring Long-Run Inflation Expectations: Evidence from India," MPRA Paper 118951, University Library of Munich, Germany.
    32. Shang, Yuhuang & Zheng, Tingguo, 2021. "Mixed-frequency SV model for stock volatility and macroeconomics," Economic Modelling, Elsevier, vol. 95(C), pages 462-472.
    33. Rodolfo C. Moura & Márcio P. Laurini, 2021. "Spillovers and jumps in global markets: A comparative analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5997-6013, October.
    34. Kreuzer, Alexander & Czado, Claudia, 2021. "Bayesian inference for a single factor copula stochastic volatility model using Hamiltonian Monte Carlo," Econometrics and Statistics, Elsevier, vol. 19(C), pages 130-150.
    35. Niyati Bhanja & Samia Nasreen & Arif Billah Dar & Aviral Kumar Tiwari, 2022. "Connectedness in International Crude Oil Markets," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 227-262, January.
    36. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
    37. Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
    38. Peter Knaus & Angela Bitto-Nemling & Annalisa Cadonna & Sylvia Fruhwirth-Schnatter, 2019. "Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP," Papers 1907.07065, arXiv.org, revised Nov 2020.
    39. Howard Caulfield & James P. Gleeson, 2024. "Systematic comparison of deep generative models applied to multivariate financial time series," Papers 2412.06417, arXiv.org.
    40. Gunawan, David & Kohn, Robert & Tran, Minh Ngoc, 2025. "Flexible and Robust Particle Tempering for State Space Models," Econometrics and Statistics, Elsevier, vol. 33(C), pages 35-55.
    41. Benjamin Poignard & Manabu Asai, 2023. "High‐dimensional sparse multivariate stochastic volatility models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 4-22, January.
    42. Bitto, Angela & Frühwirth-Schnatter, Sylvia, 2019. "Achieving shrinkage in a time-varying parameter model framework," Journal of Econometrics, Elsevier, vol. 210(1), pages 75-97.
    43. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in international dairy commodity markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(3), pages 704-728, July.
    44. Gunawan, David & Kohn, Robert & Nott, David, 2021. "Variational Bayes approximation of factor stochastic volatility models," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1355-1375.
    45. Karim Moussa, 2025. "On the Correlations in Linearized Multivariate Stochastic Volatility Models," Tinbergen Institute Discussion Papers 25-021/V, Tinbergen Institute.
    46. Kim C. Raath & Katherine B. Ensor, 2023. "Wavelet-L2E Stochastic Volatility Models: an Application to the Water-Energy Nexus," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 150-176, May.
    47. Giorgio Calzolari & Roxana Halbleib & Christian Mucher, 2023. "Sequential Estimation of Multivariate Factor Stochastic Volatility Models," Papers 2302.07052, arXiv.org.
    48. Vipul Bhatt & N. Kundan Kishor, 2025. "(A)Synchronous Housing Markets of Global Cities," The Journal of Real Estate Finance and Economics, Springer, vol. 71(2), pages 178-208, August.
    49. Bhatt, Vipul & Kishor, N. Kundan, 2021. "(A)Synchronous Housing Markets of Global Cities," MPRA Paper 107175, University Library of Munich, Germany.

  10. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? Bayesian inference in the threshold time varying parameter (TTVP) model," Department of Economics Working Papers wuwp235, Vienna University of Economics and Business, Department of Economics.

    Cited by:

    1. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    2. Huber, Florian, 2017. "Structural breaks in Taylor rule based exchange rate models — Evidence from threshold time varying parameter models," Economics Letters, Elsevier, vol. 150(C), pages 48-52.
    3. Crespo Cuaresma, Jesus & Doppelhofer, Gernot & Feldkircher, Martin & Huber, Florian, 2018. "Spillovers from US monetary policy: Evidence from a time-varying parameter GVAR model," Discussion Paper Series in Economics 31/2018, Norwegian School of Economics, Department of Economics.
    4. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    5. Arnaud Dufays & Aristide Houndetoungan & Alain Coen, 2024. "Selective linear segmentation for detecting relevant parameter changes," Papers 2402.05329, arXiv.org.
    6. Rangan Gupta & Florian Huber & Philipp Piribauer, 2018. "Predicting International Equity Returns: Evidence from Time-Varying Parameter Vector Autoregressive Models," Working Papers 201826, University of Pretoria, Department of Economics.
    7. Bian, Zhicun & Liao, Yin & O’Neill, Michael & Shi, Jing & Zhang, Xueyong, 2020. "Large-scale minimum variance portfolio allocation using double regularization," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    8. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    9. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    10. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    11. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.
    12. Jesús Crespo Cuaresma & Gernot Doppelhofer & Martin Feldkircher & Florian Huber, 2019. "Spillovers from US monetary policy: evidence from a time varying parameter global vector auto‐regressive model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(3), pages 831-861, June.
    13. Bernaciak, Dawid & Griffin, Jim E., 2024. "A loss discounting framework for model averaging and selection in time series models," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1721-1733.
    14. Zhongfang He, 2024. "Locally time-varying parameter regression," Econometric Reviews, Taylor & Francis Journals, vol. 43(5), pages 269-300, May.

  11. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Zhang, Bo & Nguyen, Bao H. & Sun, Chuanwang, 2024. "Forecasting oil prices: Can large BVARs help?," Energy Economics, Elsevier, vol. 137(C).
    3. Pedro Chaim & Márcio Poletti Laurini, 2024. "Bayesian Inference for Long Memory Stochastic Volatility Models," Econometrics, MDPI, vol. 12(4), pages 1-28, November.
    4. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    5. Kinkyo, Takuji, 2021. "Region-wide connectedness of Asian equity and currency markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    6. Sung, Bongjung & Lee, Jaeyong, 2023. "Covariance structure estimation with Laplace approximation," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
    7. BahooToroody, Ahmad & Abaei, Mohammad Mahdi & Banda, Osiris Valdez & Kujala, Pentti & De Carlo, Filippo & Abbassi, Rouzbeh, 2022. "Prognostic health management of repairable ship systems through different autonomy degree; From current condition to fully autonomous ship," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    8. Emanuela Ciapanna & Marco Taboga, 2019. "Bayesian Analysis of Coefficient Instability in Dynamic Regressions," Econometrics, MDPI, vol. 7(3), pages 1-32, June.
    9. Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2024. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 825-837, April.
    10. Qiao, W. & Bu, D. & Gibberd, A. & Liao, Y. & Wen, T. & Li, E., 2023. "When “time varying” volatility meets “transaction cost” in portfolio selection," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 220-237.
    11. Chan, Joshua C.C., 2023. "Comparing stochastic volatility specifications for large Bayesian VARs," Journal of Econometrics, Elsevier, vol. 235(2), pages 1419-1446.
    12. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
    13. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    14. Kinkyo, Takuji, 2022. "The intermediating role of the Chinese renminbi in Asian currency markets: Evidence from partial wavelet coherence," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    15. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    16. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2018. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Papers 1805.12217, arXiv.org, revised Jul 2019.
    17. Sylvia Frühwirth-Schnatter & Darjus Hosszejni & Hedibert Freitas Lopes, 2023. "When It Counts—Econometric Identification of the Basic Factor Model Based on GLT Structures," Econometrics, MDPI, vol. 11(4), pages 1-30, November.
    18. Joshua Chan & Eric Eisenstat & Xuewen Yu, 2022. "Large Bayesian VARs with Factor Stochastic Volatility: Identification, Order Invariance and Structural Analysis," Papers 2207.03988, arXiv.org.
    19. Sinha, Avik & Balsalobre-Lorente, Daniel & Zafar, Wasif & Saleem, Muhammad Mansoor, 2021. "Analyzing Global Inequality in Access to Energy: Developing Policy Framework by Inequality Decomposition," MPRA Paper 111061, University Library of Munich, Germany, revised 2021.
    20. Gregor Zens, 2018. "Bayesian shrinkage in mixture of experts models: Identifying robust determinants of class membership," Papers 1809.04853, arXiv.org, revised Jan 2019.
    21. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    22. Joshua C. C. Chan & Aubrey Poon & Dan Zhu, 2023. "High-Dimensional Conditionally Gaussian State Space Models with Missing Data," Papers 2302.03172, arXiv.org.
    23. Takuji Kinkyo, 2022. "Hedging capabilities of Bitcoin for Asian currencies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1769-1784, April.
    24. Gregor Kastner & Sylvia Frühwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Business and Economics Working Papers 234, Unidade de Negocios e Economia, Insper.
    25. Michael Pfarrhofer & Hauzenberger Niko, 2019. "Bayesian state-space modeling for analyzing heterogeneous network effects of US monetary policy," Working Papers in Economics 2019-6, University of Salzburg.
    26. Bian, Zhicun & Liao, Yin & O’Neill, Michael & Shi, Jing & Zhang, Xueyong, 2020. "Large-scale minimum variance portfolio allocation using double regularization," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    27. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    28. Lopes, Hedibert F. & McCulloch, Robert E. & Tsay, Ruey S., 2022. "Parsimony inducing priors for large scale state–space models," Journal of Econometrics, Elsevier, vol. 230(1), pages 39-61.
    29. 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.
    30. Sylvia Fruhwirth-Schnatter, 2023. "Generalized Cumulative Shrinkage Process Priors with Applications to Sparse Bayesian Factor Analysis," Papers 2303.00473, arXiv.org.
    31. Ghaemi Asl, Mahdi & Raheem, Ibrahim D. & Rashidi, Muhammad Mahdi, 2023. "Do stochastic risks flow between industrial and precious metals, Islamic stocks, green bonds, green stocks, clean investments, major foreign exchange rates, and Bitcoin?," Resources Policy, Elsevier, vol. 86(PA).
    32. Wenying Zeng & Songbai Song & Yan Kang & Xuan Gao & Rui Ma, 2022. "Response of Runoff to Meteorological Factors Based on Time-Varying Parameter Vector Autoregressive Model with Stochastic Volatility in Arid and Semi-Arid Area of Weihe River Basin," Sustainability, MDPI, vol. 14(12), pages 1-12, June.
    33. Huang Yu-Fan, 2021. "An effcient exact Bayesian method For state space models with stochastic volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-10, April.
    34. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    35. Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    36. Jose Ruiz-Tamayo & Jose Antonio Vazquez-Lopez & Edgar Augusto Ruelas-Santoyo & Aidee Hernandez-Lopez & Ismael Lopez-Juarez & Armando Javier Rios-Lira, 2021. "Multivariate Pattern Recognition in MSPC Using Bayesian Inference," Mathematics, MDPI, vol. 9(4), pages 1-18, February.
    37. Kreuzer, Alexander & Czado, Claudia, 2021. "Bayesian inference for a single factor copula stochastic volatility model using Hamiltonian Monte Carlo," Econometrics and Statistics, Elsevier, vol. 19(C), pages 130-150.
    38. Roberto Leon-Gonzalez & Blessings Majon, 2024. "Approximate Factor Models with a Common Multiplicative Factor for Stochastic Volatility," GRIPS Discussion Papers 24-02, National Graduate Institute for Policy Studies.
    39. Niyati Bhanja & Samia Nasreen & Arif Billah Dar & Aviral Kumar Tiwari, 2022. "Connectedness in International Crude Oil Markets," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 227-262, January.
    40. Martin, Ertl & Fortin, Ines & Hlouskova, Jaroslava & Koch, Sebastian P. & Kunst, Robert M. & Soegner, Leopold, 2024. "Inflation Forecasting in Turbulent Times," IHS Working Paper Series 56, Institute for Advanced Studies.
      • Martin Ertl & Ines Fortin & Jaroslava Hlouskova & Sebastian P. Koch & Robert M. Kunst & Leopold Sögner, 2025. "Inflation forecasting in turbulent times," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 52(1), pages 5-37, February.
    41. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
    42. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
    43. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in international dairy commodity markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(3), pages 704-728, July.
    44. Gunawan, David & Kohn, Robert & Nott, David, 2021. "Variational Bayes approximation of factor stochastic volatility models," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1355-1375.
    45. Martin Feldkircher & Karin Klieber, 2024. "Integration or fragmentation? A closer look at euro area financial markets," Chapters, in: Guglielmo M. Caporale (ed.), Handbook of Financial Integration, chapter 19, pages 443-469, Edward Elgar Publishing.
    46. Michael Pfarrhofer & Philipp Piribauer, 2018. "Flexible shrinkage in high-dimensional Bayesian spatial autoregressive models," Papers 1805.10822, arXiv.org.
    47. Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).
    48. Giorgio Calzolari & Roxana Halbleib & Christian Mucher, 2023. "Sequential Estimation of Multivariate Factor Stochastic Volatility Models," Papers 2302.07052, arXiv.org.
    49. Marín Díazaraque, Juan Miguel & Romero, Eva & Lopes Moreira da Veiga, María Helena, 2025. "Switching the leverage switch," DES - Working Papers. Statistics and Econometrics. WS 47005, Universidad Carlos III de Madrid. Departamento de Estadística.
    50. Tao Sun, 2024. "Bundle Choice Model with Endogenous Regressors: An Application to Soda Tax," Papers 2412.05794, arXiv.org.
    51. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Feb 2025.

  12. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.

    Cited by:

    1. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    2. Huber, Florian, 2017. "Structural breaks in Taylor rule based exchange rate models — Evidence from threshold time varying parameter models," Economics Letters, Elsevier, vol. 150(C), pages 48-52.
    3. Crespo Cuaresma, Jesus & Doppelhofer, Gernot & Feldkircher, Martin & Huber, Florian, 2018. "Spillovers from US monetary policy: Evidence from a time-varying parameter GVAR model," Discussion Paper Series in Economics 31/2018, Norwegian School of Economics, Department of Economics.
    4. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    5. Arnaud Dufays & Aristide Houndetoungan & Alain Coen, 2024. "Selective linear segmentation for detecting relevant parameter changes," Papers 2402.05329, arXiv.org.
    6. Rangan Gupta & Florian Huber & Philipp Piribauer, 2018. "Predicting International Equity Returns: Evidence from Time-Varying Parameter Vector Autoregressive Models," Working Papers 201826, University of Pretoria, Department of Economics.
    7. Bian, Zhicun & Liao, Yin & O’Neill, Michael & Shi, Jing & Zhang, Xueyong, 2020. "Large-scale minimum variance portfolio allocation using double regularization," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    8. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    9. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    10. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    11. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.
    12. Jesús Crespo Cuaresma & Gernot Doppelhofer & Martin Feldkircher & Florian Huber, 2019. "Spillovers from US monetary policy: evidence from a time varying parameter global vector auto‐regressive model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(3), pages 831-861, June.
    13. Bernaciak, Dawid & Griffin, Jim E., 2024. "A loss discounting framework for model averaging and selection in time series models," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1721-1733.
    14. Zhongfang He, 2024. "Locally time-varying parameter regression," Econometric Reviews, Taylor & Francis Journals, vol. 43(5), pages 269-300, May.

  13. Ziegelback, Martin & Kastner, Gregor, 2011. "European Rapeseed And Fossil Diesel: Threshold Cointegration Analysis And Possible Implications," 51st Annual Conference, Halle, Germany, September 28-30, 2011 114741, German Association of Agricultural Economists (GEWISOLA).

    Cited by:

    1. Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2012. "Biofuels: review of policies and impacts," CUDARE Working Papers 120415, University of California, Berkeley, Department of Agricultural and Resource Economics.
    2. Karel Janda & Ladislav Kristoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods, Outcomes, and Lessons for Commodity Price Risk Management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Filip, Ondrej & Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2019. "Food versus fuel: An updated and expanded evidence," Energy Economics, Elsevier, vol. 82(C), pages 152-166.
    4. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, "undated". "Relationship Between Prices of Food, Fuel and Biofuel," 131st Seminar, September 18-19, 2012, Prague, Czech Republic 135793, European Association of Agricultural Economists.
    5. Sergio Adriani David & Claudio M. C. Inácio & José A. Tenreiro Machado, 2019. "Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
    6. Karel Janda & Ladislav Kristoufek & David Zilberman, 2011. "Modeling the Environmental and Socio-Economic Impacts of Biofuels," Working Papers IES 2011/33, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2011.
    7. Fernandez-Perez, Adrian & Frijns, Bart & Tourani-Rad, Alireza, 2016. "Contemporaneous interactions among fuel, biofuel and agricultural commodities," Energy Economics, Elsevier, vol. 58(C), pages 1-10.
    8. Guo, Jin & Tanaka, Tetsuji, 2022. "Energy security versus food security: An analysis of fuel ethanol- related markets using the spillover index and partial wavelet coherence approaches," Energy Economics, Elsevier, vol. 112(C).
    9. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective," Energy Economics, Elsevier, vol. 34(5), pages 1380-1391.
    10. Serra, Teresa & Zilberman, David, 2013. "Biofuel-related price transmission literature: A review," Energy Economics, Elsevier, vol. 37(C), pages 141-151.
    11. Franken, Jason R.V. & Irwin, Scott H. & Garcia, Philip, 2021. "Biodiesel hedging under binding renewable fuel standard mandates," Energy Economics, Elsevier, vol. 96(C).

Articles

  1. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2025. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Empirical Economics, Springer, vol. 68(2), pages 535-553, February.
    See citations under working paper version above.
  2. Rezitis, Anthony N. & Kastner, Gregor, 2021. "On the joint volatility dynamics in international dairy commodity markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 60(2), January.

    Cited by:

    1. Ghaemi Asl, Mahdi & Raheem, Ibrahim D. & Rashidi, Muhammad Mahdi, 2023. "Do stochastic risks flow between industrial and precious metals, Islamic stocks, green bonds, green stocks, clean investments, major foreign exchange rates, and Bitcoin?," Resources Policy, Elsevier, vol. 86(PA).
    2. Anthony N. Rezitis & Ourania A. Tremma, 2022. "The linkage between international dairy commodity prices and volatility: a panel-GARCH analysis," Journal of Agribusiness in Developing and Emerging Economies, Emerald Group Publishing Limited, vol. 13(5), pages 685-705, April.

  3. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    See citations under working paper version above.
  4. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    See citations under working paper version above.
  5. Florian Huber & Gregor Kastner & Martin Feldkircher, 2019. "Should I stay or should I go? A latent threshold approach to large‐scale mixture innovation models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 621-640, August.
    See citations under working paper version above.
  6. Kastner, Gregor, 2016. "Dealing with Stochastic Volatility in Time Series Using the R Package stochvol," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i05).
    See citations under working paper version above.
  7. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
    See citations under working paper version above.
  8. Martin ZIEGELBÄCK & Gregor KASTNER, 2013. "Arbitrage hedging in markets for the US lean hogs and the EU live pigs," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 59(11), pages 505-511.

    Cited by:

    1. Oscar V. De la Torre-Torres & Rodolfo A. López-Torres & María de la Cruz del Río-Rama & José Álvarez-García, 2025. "Mexican White Corn Spot Price Hedging with US Agricultural Futures Portfolios Using the Surplus Efficient Frontier," Agriculture, MDPI, vol. 15(17), pages 1-28, August.
    2. Eewoud Lievens & Kobe Tielens & Erik Mathijs, 2021. "Creating a market for price swaps: Case study of an innovative risk management instrument in the Belgian-Dutch pear market," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(1), pages 33-40.

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