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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 Jul 2023.

    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. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    2. 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.
    3. Sylvia Fruhwirth-Schnatter & Peter Knaus, 2022. "Sparse Bayesian State-Space and Time-Varying Parameter Models," Papers 2207.12147, arXiv.org.
    4. Helmut Lutkepohl & Fei Shang & Luis Uzeda & Tomasz Wo'zniak, 2024. "Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference," Papers 2404.11057, arXiv.org.
    5. 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.
    6. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Smoothing volatility targeting," Papers 2212.07288, arXiv.org.
    7. Będowska-Sójka, Barbara & Kliber, Agata, 2022. "Can cryptocurrencies hedge oil price fluctuations? A pandemic perspective," Energy Economics, Elsevier, vol. 115(C).
    8. 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.
    9. 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.
    10. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Jul 2023.
    11. Ioannis Papageorgiou & Ioannis Kontoyiannis, 2023. "The Bayesian Context Trees State Space Model for time series modelling and forecasting," Papers 2308.00913, arXiv.org, revised Oct 2023.
    12. Zexuan Yin & Paolo Barucca, 2022. "Variational Heteroscedastic Volatility Model," Papers 2204.05806, arXiv.org.
    13. Omar Abbara & Mauricio Zevallos, 2022. "Maximum Likelihood Inference for Asymmetric Stochastic Volatility Models," Econometrics, MDPI, vol. 11(1), pages 1-18, December.

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

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Florian Huber & Maria Teresa Punzi, 2016. "International Housing Markets, Unconventional Monetary Policy and the Zero Lower Bound," Department of Economics Working Papers wuwp216, Vienna University of Economics and Business, Department of Economics.
    6. Hernández Juan R., 2020. "Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band," Working Papers 2020-02, Banco de México.
    7. 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.
    8. Florian Huber & Daniel Kaufmann, 2015. "Trend Fundamentals and Exchange Rate Dynamics," KOF Working papers 15-393, KOF Swiss Economic Institute, ETH Zurich.
    9. Alok Johri & Shahed K. Khan & Cesar Sosa-Padilla, 2018. "Interest Rate Uncertainty and Sovereign Default Risk," Department of Economics Working Papers 2018-17, McMaster University.
    10. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    11. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    12. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2020. "Bayesian Modelling of TVP-VARs Using Regression Trees," Working Papers 2308, University of Strathclyde Business School, Department of Economics, revised Aug 2023.
    13. Feldkircher, Martin & Lukmanova, Elizaveta & Tondl, Gabriele, 2019. "Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment," Department of Economics Working Paper Series 289, WU Vienna University of Economics and Business.
    14. 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.
    15. 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.
    16. Florian Huber & Katrin Rabitsch, 2019. "Exchange rate dynamics and monetary policy -- Evidence from a non-linear DSGE-VAR approach," Department of Economics Working Papers wuwp295, Vienna University of Economics and Business, Department of Economics.
    17. Gleb Kurovskiy, 2017. "Modelling terms of trade volatility impact on output dynamics in Russia," EcoMod2017 10361, EcoMod.
    18. 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.
    19. 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.
    20. 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.
    21. Feldkircher, Martin & Kastner, Gregor & Huber, Florian, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Paper Series 260, WU Vienna University of Economics and Business.
    22. 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.
    23. Niko Hauzenberger & Maximilian Bock & Michael Pfarrhofer & Anna Stelzer & Gregor Zens, 2018. "Implications of macroeconomic volatility in the Euro area," Papers 1801.02925, arXiv.org, revised Jun 2018.
    24. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2019. "The regional transmission of uncertainty shocks on income inequality in the United States," Working Papers in Regional Science 2019/01, WU Vienna University of Economics and Business.
    25. Niko Hauzenberger & Michael Pfarrhofer & Luca Rossini, 2020. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," Papers 2011.04577, arXiv.org, revised Apr 2023.
    26. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    27. 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.
    28. Ringwald, Leopold & Zörner, Thomas O., 2023. "The money-inflation nexus revisited," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 293-333.
    29. Karlsson, Sune & Mazur, Stepan, 2020. "Flexible Fat-tailed Vector Autoregression," Working Papers 2020:5, Örebro University, School of Business.
    30. Patrick Aschermayr & Konstantinos Kalogeropoulos, 2023. "Sequential Bayesian Learning for Hidden Semi-Markov Models," Papers 2301.10494, arXiv.org.
    31. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    32. 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.
    33. 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.
    34. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    35. 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.
    36. 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.
    37. 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).
    38. 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.
    39. 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.
    40. Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.
    41. 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).
    42. 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.
    43. 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.
    44. Davidovic, Milivoje, 2021. "From pandemic to financial contagion: High-frequency risk metrics and Bayesian volatility analysis," Finance Research Letters, Elsevier, vol. 42(C).
    45. Hwai-Chung Ho, 2022. "Forecasting the distribution of long-horizon returns with time-varying volatility," Papers 2201.07457, arXiv.org.
    46. 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.
    47. Zhao, Yixiu & Upreti, Vineet & Cai, Yuzhi, 2021. "Stock returns, quantile autocorrelation, and volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 73(C).
    48. 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.
    49. 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.
    50. 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.
    51. Gupta, Rangan & Huber, Florian & Piribauer, Philipp, 2020. "Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    52. 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).
    53. 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).
    54. 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.
    55. Gregor Kastner & Sylvia Fruhwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Papers 1602.08154, arXiv.org, revised Jul 2017.
    56. Roberto Leon-Gonzalez & Blessings Majoni, 2023. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," Working Paper series 23-11, Rimini Centre for Economic Analysis.
    57. Michael Pfarrhofer & Anna Stelzer, 2019. "The international effects of central bank information shocks," Papers 1912.03158, arXiv.org.
    58. 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.
    59. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    60. 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.
    61. 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.
    62. 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.
    63. 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.
    64. Sophie Altermatt & Simon Beyeler, 2018. "Shall We Twist?," Diskussionsschriften dp1825, Universitaet Bern, Departement Volkswirtschaft.
    65. 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.
    66. Luo, Weijie & Wang, Yong & Zhang, Xiaoge, 2022. "Monetary policy uncertainty and firm risk-taking," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).

  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. 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).
    2. Cross, Jamie L. & Hou, Chenghan & Trinh, Kelly, 2021. "Returns, volatility and the cryptocurrency bubble of 2017–18," Economic Modelling, Elsevier, vol. 104(C).
    3. 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.

  5. 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. 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.
    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. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    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. 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.
    6. Niko Hauzenberger & Florian Huber & Massimiliano Marcellino & Nico Petz, 2021. "Gaussian Process Vector Autoregressions and Macroeconomic Uncertainty," Papers 2112.01995, arXiv.org, revised Nov 2022.
    7. 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.
    8. 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.
    9. 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.
    10. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    11. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    12. 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.
    13. Li Li & Yanfei Kang & Feng Li, 2021. "Bayesian forecast combination using time-varying features," Papers 2108.02082, arXiv.org, revised Jun 2022.
    14. 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.
    15. Arnaud Dufays & Aristide Houndetoungan & Alain Coen, 2024. "Selective linear segmentation for detecting relevant parameter changes," Papers 2402.05329, arXiv.org.
    16. 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.
    17. Florian Huber & Maria Teresa Punzi, 2016. "International Housing Markets, Unconventional Monetary Policy and the Zero Lower Bound," Department of Economics Working Papers wuwp216, Vienna University of Economics and Business, Department of Economics.
    18. Andrejs Zlobins, 2019. "Country-Level Effects of the ECB's Expanded Asset Purchase Programme," Working Papers 2019/02, Latvijas Banka.
    19. 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.
    20. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    21. Michele Costola & Matteo Iacopini & Casper Wichers, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," Papers 2310.17473, arXiv.org.
    22. 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.
    23. 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.
    24. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    25. 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.
    26. Marcellino, Massimiliano & Clark, Todd & Huber, Florian & Koop, Gary, 2023. "Forecasting US Inflation Using Bayesian Nonparametric Models," CEPR Discussion Papers 18244, C.E.P.R. Discussion Papers.
    27. Crespo Cuaresma, Jesus & Doppelhofer, Gernot & Feldkircher, Martin & Huber, Florian, 2018. "Spillovers from US monetary policy: Evidence from a time-varying parameter GVAR model," Working Papers in Economics 2018-6, University of Salzburg.
    28. Huber, Florian & Krisztin, Tamás & Piribauer, Philipp, 2014. "Forecasting Global Equity Indices Using Large Bayesian VARs," Department of Economics Working Paper Series 184, WU Vienna University of Economics and Business.
    29. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    30. 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).
    31. Florian Huber & Daniel Kaufmann, 2015. "Trend Fundamentals and Exchange Rate Dynamics," KOF Working papers 15-393, KOF Swiss Economic Institute, ETH Zurich.
    32. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org.
    33. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    34. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    35. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    36. Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018. "Measuring international uncertainty: The case of Korea," Economics Letters, Elsevier, vol. 162(C), pages 22-26.
    37. 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).
    38. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2020. "Bayesian Modelling of TVP-VARs Using Regression Trees," Working Papers 2308, University of Strathclyde Business School, Department of Economics, revised Aug 2023.
    39. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. 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).
    45. 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.
    46. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    47. 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).
    48. Gregor Kastner & Sylvia Fruhwirth-Schnatter, 2017. "Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models," Papers 1706.05280, arXiv.org.
    49. 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.
    50. 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.
    51. 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).
    52. Florian Huber & Katrin Rabitsch, 2019. "Exchange rate dynamics and monetary policy -- Evidence from a non-linear DSGE-VAR approach," Department of Economics Working Papers wuwp295, Vienna University of Economics and Business, Department of Economics.
    53. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.
    54. Nalan Baştürk & Cem Çakmakli & S. Pinar Ceyhan & Herman K. Van Dijk, 2014. "Posterior‐Predictive Evidence On Us Inflation Using Extended New Keynesian Phillips Curve Models With Non‐Filtered Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1164-1182, November.
    55. 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.
    56. Gleb Kurovskiy, 2017. "Modelling terms of trade volatility impact on output dynamics in Russia," EcoMod2017 10361, EcoMod.
    57. 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.
    58. 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.
    59. 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.
    60. 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.
    61. 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.
    62. Sylvia Fruhwirth-Schnatter & Peter Knaus, 2022. "Sparse Bayesian State-Space and Time-Varying Parameter Models," Papers 2207.12147, arXiv.org.
    63. 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.
    64. 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.
    65. 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.
    66. 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.
    67. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.
    68. Karin Klieber, 2023. "Non-linear dimension reduction in factor-augmented vector autoregressions," Papers 2309.04821, arXiv.org.
    69. Marcellino, Massimiliano & Clark, Todd & Huber, Florian & Koop, Gary & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    70. Martin, Feldkircher & Thomas, Gruber & Florian, Huber, 2019. "International effects of a compression of euro area yield curves," Working Papers in Economics 2019-1, University of Salzburg.
    71. Feldkircher, Martin & Kastner, Gregor & Huber, Florian, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Paper Series 260, WU Vienna University of Economics and Business.
    72. Eller, Markus & Huber, Florian & Schuberth, Helene, 2018. "How Important are Global Factors for Understanding the Dynamics of International Capital Flows?," Working Papers in Economics 2018-2, University of Salzburg.
    73. 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.
    74. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.
    75. Florian Huber & Michael Pfarrhofer, 2020. "Dynamic shrinkage in time-varying parameter stochastic volatility in mean models," Papers 2005.06851, arXiv.org.
    76. 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.
    77. 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.
    78. Steff De Visscher & Markus Eberhardt & Gerdie Everaert, 2017. "Measuring productivity and absorptive capacity evolution," Discussion Papers 2017-11, University of Nottingham, GEP.
    79. Gabriella Conti & Sylvia Frühwirth-Schnatter & James J. Heckman & Rémi Piatek, 2014. "Bayesian Exploratory Factor Analysis," NRN working papers 2014-08, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    80. Niko Hauzenberger & Maximilian Bock & Michael Pfarrhofer & Anna Stelzer & Gregor Zens, 2018. "Implications of macroeconomic volatility in the Euro area," Papers 1801.02925, arXiv.org, revised Jun 2018.
    81. Redl, Chris, 2020. "Uncertainty matters: Evidence from close elections," Journal of International Economics, Elsevier, vol. 124(C).
    82. Anzarut, Michelle & Mena, Ramsés H., 2019. "A Harris process to model stochastic volatility," Econometrics and Statistics, Elsevier, vol. 10(C), pages 151-169.
    83. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2019. "The regional transmission of uncertainty shocks on income inequality in the United States," Working Papers in Regional Science 2019/01, WU Vienna University of Economics and Business.
    84. 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.
    85. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis," Papers 2001.03935, arXiv.org.
    86. Niko Hauzenberger & Michael Pfarrhofer & Luca Rossini, 2020. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," Papers 2011.04577, arXiv.org, revised Apr 2023.
    87. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    88. 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.
    89. 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.
    90. 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.
    91. Helmut Lutkepohl & Fei Shang & Luis Uzeda & Tomasz Wo'zniak, 2024. "Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference," Papers 2404.11057, arXiv.org.
    92. 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.
    93. Liu, Zhenya & Wang, Shixuan, 2017. "Decoding Chinese stock market returns: Three-state hidden semi-Markov model," Pacific-Basin Finance Journal, Elsevier, vol. 44(C), pages 127-149.
    94. 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.
    95. 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.
    96. Ringwald, Leopold & Zörner, Thomas O., 2023. "The money-inflation nexus revisited," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 293-333.
    97. Karlsson, Sune & Mazur, Stepan, 2020. "Flexible Fat-tailed Vector Autoregression," Working Papers 2020:5, Örebro University, School of Business.
    98. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    99. 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.
    100. Sergey Egiev, 2016. "On Persistence of Uncertainty Shocks," HSE Working papers WP BRP 144/EC/2016, National Research University Higher School of Economics.
    101. 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.
    102. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.
    103. 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.
    104. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    105. 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.
    106. 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).
    107. 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.
    108. 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).
    109. Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm, 2023. "Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 347-368, March.
    110. 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.
    111. 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.
    112. 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.
    113. Hoang Nguyen & Trong-Nghia Nguyen & Minh-Ngoc Tran, 2023. "A dynamic leverage stochastic volatility model," Applied Economics Letters, Taylor & Francis Journals, vol. 30(1), pages 97-102, January.
    114. Rui Luo & Weinan Zhang & Xiaojun Xu & Jun Wang, 2017. "A Neural Stochastic Volatility Model," Papers 1712.00504, arXiv.org, revised Dec 2018.
    115. 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).
    116. 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).
    117. 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.
    118. 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.
    119. 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).
    120. 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.
    121. 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.
    122. 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.
    123. 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.
    124. 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.
    125. Hwai-Chung Ho, 2022. "Forecasting the distribution of long-horizon returns with time-varying volatility," Papers 2201.07457, arXiv.org.
    126. 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.
    127. 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.
    128. 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.
    129. 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.
    130. 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.
    131. Gupta, Rangan & Huber, Florian & Piribauer, Philipp, 2020. "Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    132. 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).
    133. 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.
    134. 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.
    135. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    136. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Jul 2023.
    137. Gregor Kastner & Sylvia Fruhwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Papers 1602.08154, arXiv.org, revised Jul 2017.
    138. 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.
    139. 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.
    140. 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.
    141. Michael Pfarrhofer & Anna Stelzer, 2019. "The international effects of central bank information shocks," Papers 1912.03158, arXiv.org.
    142. 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.
    143. 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.
    144. Tony Chernis, 2023. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Staff Working Papers 23-45, Bank of Canada.
    145. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    146. 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.
    147. 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.
    148. Cross, Jamie L. & Hou, Chenghan & Trinh, Kelly, 2021. "Returns, volatility and the cryptocurrency bubble of 2017–18," Economic Modelling, Elsevier, vol. 104(C).
    149. 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.
    150. 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.
    151. 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.
    152. Niko Hauzenberger & Massimiliano Marcellino & Michael Pfarrhofer & Anna Stelzer, 2024. "Nowcasting with mixed frequency data using Gaussian processes," Papers 2402.10574, arXiv.org.
    153. Sophie Altermatt & Simon Beyeler, 2018. "Shall We Twist?," Diskussionsschriften dp1825, Universitaet Bern, Departement Volkswirtschaft.
    154. Annika Camehl & Tomasz Wo'zniak, 2023. "Time-Varying Identification of Monetary Policy Shocks," Papers 2311.05883, arXiv.org, revised May 2024.
    155. 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.
    156. 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).
    157. 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.
    158. 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.

  6. 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. 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.
    3. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    4. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    5. 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.
    6. Sylvia Fruhwirth-Schnatter & Peter Knaus, 2022. "Sparse Bayesian State-Space and Time-Varying Parameter Models," Papers 2207.12147, arXiv.org.
    7. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis," Papers 2001.03935, arXiv.org.
    8. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    9. Niko Hauzenberger & Michael Pfarrhofer, 2021. "Bayesian State‐Space Modeling for Analyzing Heterogeneous Network Effects of US Monetary Policy," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(4), pages 1261-1291, October.
    10. 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).
    11. 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.
    12. 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.
    13. Gupta, Rangan & Huber, Florian & Piribauer, Philipp, 2020. "Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    14. Michael Pfarrhofer & Philipp Piribauer, 2018. "Flexible shrinkage in high-dimensional Bayesian spatial autoregressive models," Papers 1805.10822, arXiv.org.
    15. Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.

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

    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. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    3. 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).
    4. 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.
    5. 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.
    6. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
    7. 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.
    8. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    9. 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.
    10. 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.
    11. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    12. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    13. 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.
    14. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    15. 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.
    16. 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.
    17. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.
    18. Marcellino, Massimiliano & Clark, Todd & Huber, Florian & Koop, Gary & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    19. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    20. 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).
    21. Joshua C. C. Chan, 2019. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," CAMA Working Papers 2019-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    22. 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.
    23. 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.
    24. 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.
    25. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    26. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
    27. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    28. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    29. 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.
    30. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    31. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Jul 2023.
    32. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    33. Michael Pfarrhofer & Anna Stelzer, 2019. "The international effects of central bank information shocks," Papers 1912.03158, arXiv.org.
    34. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.

  8. 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. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    3. 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.
    4. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    5. 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.
    6. 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.
    7. Sylvia Fruhwirth-Schnatter, 2023. "Generalized Cumulative Shrinkage Process Priors with Applications to Sparse Bayesian Factor Analysis," Papers 2303.00473, arXiv.org.
    8. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    9. 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.
    10. 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.
    11. 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.
    12. Kinkyo, Takuji, 2021. "Region-wide connectedness of Asian equity and currency markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    13. 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).
    14. Gregor Zens, 2018. "Bayesian shrinkage in mixture of experts models: Identifying robust determinants of class membership," Papers 1809.04853, arXiv.org, revised Jan 2019.
    15. 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.
    16. 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).
    17. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis," Papers 2001.03935, arXiv.org.
    18. Niko Hauzenberger & Michael Pfarrhofer, 2021. "Bayesian State‐Space Modeling for Analyzing Heterogeneous Network Effects of US Monetary Policy," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(4), pages 1261-1291, October.
    19. 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.
    20. 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.
    21. Sung, Bongjung & Lee, Jaeyong, 2023. "Covariance structure estimation with Laplace approximation," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
    22. 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).
    23. Emanuela Ciapanna & Marco Taboga, 2019. "Bayesian Analysis of Coefficient Instability in Dynamic Regressions," Econometrics, MDPI, vol. 7(3), pages 1-32, June.
    24. 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.
    25. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    26. 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).
    27. 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.
    28. 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.
    29. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    30. Giorgio Calzolari & Roxana Halbleib & Christian Mucher, 2023. "Sequential Estimation of Multivariate Factor Stochastic Volatility Models," Papers 2302.07052, arXiv.org.
    31. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Jul 2023.
    32. Gregor Kastner & Sylvia Fruhwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Papers 1602.08154, arXiv.org, revised Jul 2017.
    33. 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.
    34. 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.
    35. Sylvia Fruhwirth-Schnatter & Darjus Hosszejni & Hedibert Freitas Lopes, 2023. "When it counts -- Econometric identification of the basic factor model based on GLT structures," Papers 2301.06354, arXiv.org.
    36. 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.
    37. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
    38. 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.
    39. Michael Pfarrhofer & Philipp Piribauer, 2018. "Flexible shrinkage in high-dimensional Bayesian spatial autoregressive models," Papers 1805.10822, arXiv.org.
    40. 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).

  9. Gregor Kastner & Sylvia Fruhwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Papers 1602.08154, arXiv.org, revised Jul 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. 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.
    3. 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.
    4. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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).
    15. 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.
    16. 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.
    17. Kinkyo, Takuji, 2021. "Region-wide connectedness of Asian equity and currency markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    18. 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.
    19. 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).
    20. 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).
    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. Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Paper series 20-09, Rimini Centre for Economic Analysis.
    23. 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.
    24. Shang, Yuhuang & Zheng, Tingguo, 2021. "Mixed-frequency SV model for stock volatility and macroeconomics," Economic Modelling, Elsevier, vol. 95(C), pages 462-472.
    25. 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.
    26. 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.
    27. 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.
    28. Bhatt, Vipul & Kishor, N. Kundan, 2021. "(A)Synchronous Housing Markets of Global Cities," MPRA Paper 107175, University Library of Munich, Germany.
    29. Benjamin Poignard & Manabu Asai, 2022. "High-Dimensional Sparse Multivariate Stochastic Volatility Models," Papers 2201.08584, arXiv.org, revised May 2022.
    30. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. Giorgio Calzolari & Roxana Halbleib & Christian Mucher, 2023. "Sequential Estimation of Multivariate Factor Stochastic Volatility Models," Papers 2302.07052, arXiv.org.
    39. 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.
    40. Tony Chernis, 2023. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Staff Working Papers 23-45, Bank of Canada.
    41. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    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. 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.
    44. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.

  10. 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. 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.
    2. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    3. Arnaud Dufays & Aristide Houndetoungan & Alain Coen, 2024. "Selective linear segmentation for detecting relevant parameter changes," Papers 2402.05329, arXiv.org.
    4. Crespo Cuaresma, Jesus & Doppelhofer, Gernot & Feldkircher, Martin & Huber, Florian, 2018. "Spillovers from US monetary policy: Evidence from a time-varying parameter GVAR model," Working Papers in Economics 2018-6, University of Salzburg.
    5. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    6. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    7. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    8. 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.
    9. 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).
    10. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    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. Gupta, Rangan & Huber, Florian & Piribauer, Philipp, 2020. "Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models," International Review of Financial Analysis, Elsevier, vol. 68(C).

  11. 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. 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.
    2. 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).
    3. 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.
    4. 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.
    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. 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.
    7. 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.
    8. Serra, Teresa & Zilberman, David, 2013. "Biofuel-related price transmission literature: A review," Energy Economics, Elsevier, vol. 37(C), pages 141-151.
    9. Janda, Karel & Kristoufek, Ladislav & Zilberman, David, "undated". "Biofuels: review of policies and impacts," CUDARE Working Papers 120415, University of California, Berkeley, Department of Agricultural and Resource Economics.
    10. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Relationship Between Prices of Food, Fuel and Biofuel," 131st Seminar, September 18-19, 2012, Prague, Czech Republic 135793, European Association of Agricultural Economists.
    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. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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. 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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