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Moving Average Stochastic Volatility Models with Application to Inflation Forecast
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Cited by:
- Nonejad Nima, 2016. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," Journal of Time Series Econometrics, De Gruyter, vol. 8(1), pages 55-90, January.
- Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
- Chan, Joshua C.C. & Grant, Angelia L., 2015.
"Pitfalls of estimating the marginal likelihood using the modified harmonic mean,"
Economics Letters, Elsevier, vol. 131(C), pages 29-33.
- Joshua C.C. Chan & Angelia L. Grant, 2015. "Pitfalls of Estimating the Marginal Likelihood Using the Modified Harmonic Mean," CAMA Working Papers 2015-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Dimitris Korobilis & Maximilian Schroder, 2023.
"Monitoring multicountry macroeconomic risk,"
Papers
2305.09563, arXiv.org.
- Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Paper series 23-06, Rimini Centre for Economic Analysis.
- Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Paper 2023/9, Norges Bank.
- Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Papers 2023_07, Business School - Economics, University of Glasgow.
- Qureshi, Irfan, 2015. "What are monetary policy shocks?," Economic Research Papers 270008, University of Warwick - Department of Economics.
- Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
- Luis Uzeda, 2022.
"State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models,"
Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53,
Emerald Group Publishing Limited.
- Luis Uzeda, 2016. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," ANU Working Papers in Economics and Econometrics 2016-632, Australian National University, College of Business and Economics, School of Economics.
- Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
- Bo Zhang, 2019. "Real‐time inflation forecast combination for time‐varying coefficient models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 175-191, April.
- Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2016.
"Large Bayesian VARMAs,"
Journal of Econometrics, Elsevier, vol. 192(2), pages 374-390.
- Joshua C C Chan & Eric Eisenstat & Gary Koop, 2014. "Large Bayesian VARMAs," Working Papers 1409, University of Strathclyde Business School, Department of Economics.
- Joshua Chan & Eric Eisenstat & Gary Koop, 2015. "Large Bayesian VARMAs," Working Paper series 15-36, Rimini Centre for Economic Analysis.
- Joshua C.C. Chan & Eric Eisenstat & Gary Koop, 2014. "Large Bayesian VARMAs," Working Paper series 40_14, Rimini Centre for Economic Analysis.
- Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2014. "Large Bayesian VARMAs," SIRE Discussion Papers 2015-06, Scottish Institute for Research in Economics (SIRE).
- Hsiao, Cody Yu-Ling & Chen, Hsing Hung, 2018. "The contagious effects on economic development after resuming construction policy for nuclear power plants in Coastal China," Energy, Elsevier, vol. 152(C), pages 291-302.
- Barnett William A. & Jawadi Fredj & Ftiti Zied, 2020.
"Causal relationships between inflation and inflation uncertainty,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-26, December.
- William A. Barnett & Zied Ftiti & Fredj Jawadi, 2018. "The Causal Relationships between Inflation and Inflation Uncertainty," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201803, University of Kansas, Department of Economics, revised Mar 2018.
- Barnett, William A. & Jawadi, Fredj & Ftiti, Zied, 2020. "Causal Relationships between Inflation and Inflation Uncertainty," MPRA Paper 101682, University Library of Munich, Germany.
- William A. Barnett & Fredj Jawadi & Zied Ftiti, 2020. "Causal Relationships Between Inflation and Inflation Uncertainty," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202010, University of Kansas, Department of Economics, revised Jul 2020.
- Barnett, William & Ftiti, Zied & Jawadi, Fredj, 2018. "The Causal Relationships between Inflation and Inflation Uncertainty," MPRA Paper 86478, University Library of Munich, Germany.
- Nonejad, Nima, 2018. "Déjà vol oil? Predicting S&P 500 equity premium using crude oil price volatility: Evidence from old and recent time-series data," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 260-270.
- Joshua C. C. Chan, 2022.
"Asymmetric conjugate priors for large Bayesian VARs,"
Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
- Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Joshua C. C. Chan, 2021. "Asymmetric Conjugate Priors for Large Bayesian VARs," Papers 2111.07170, arXiv.org.
- Ramis Khabibullin, 2019. "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series wps50, Bank of Russia.
- Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2020. "Forecasting natural gas prices using highly flexible time-varying parameter models," Working Papers 2020-01, University of Tasmania, Tasmanian School of Business and Economics.
- Nima Nonejad, 2013. "Long Memory and Structural Breaks in Realized Volatility: An Irreversible Markov Switching Approach," CREATES Research Papers 2013-26, Department of Economics and Business Economics, Aarhus University.
- Frazier, David T. & Maneesoonthorn, Worapree & Martin, Gael M. & McCabe, Brendan P.M., 2019.
"Approximate Bayesian forecasting,"
International Journal of Forecasting, Elsevier, vol. 35(2), pages 521-539.
- David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Brendan P.M. McCabe, 2018. "Approximate Bayesian forecasting," Monash Econometrics and Business Statistics Working Papers 2/18, Monash University, Department of Econometrics and Business Statistics.
- Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2014. "Large Bayesian VARMAs," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-06, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2017.
"Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 275-295, March.
- Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2015. "Inside the crystal ball: New approaches to predicting the gasoline price at the pump," CFS Working Paper Series 500, Center for Financial Studies (CFS).
- Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2016. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CESifo Working Paper Series 5759, CESifo.
- Kilian, Lutz & Baumeister, Christiane & Lee, Thomas K, 2015. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CEPR Discussion Papers 10362, C.E.P.R. Discussion Papers.
- Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
- Nima Nonejad, 2020. "Does the price of crude oil help predict the conditional distribution of aggregate equity return?," Empirical Economics, Springer, vol. 58(1), pages 313-349, January.
- Doğan, Osman & Taşpınar, Süleyman & Bera, Anil K., 2021. "A Bayesian robust chi-squared test for testing simple hypotheses," Journal of Econometrics, Elsevier, vol. 222(2), pages 933-958.
- Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2019. "Non-Gaussian VARMA model with stochastic volatility and applications in stock market bubbles," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 129-136.
- Le Bihan, Hervé & Leiva-Leon, Danilo & Pacce, Matías, 2023.
"Underlying inflation and asymmetric risks,"
Working Paper Series
2848, European Central Bank.
- Hervé Le Bihan & Danilo Leiva-León & Matías Pacce, 2023. "Underlying inflation and asymetric risks," Working Papers 2319, Banco de España.
- Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
- Angelia L. Grant & Joshua C.C. Chan, 2017.
"A Bayesian Model Comparison for Trend‐Cycle Decompositions of Output,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(2-3), pages 525-552, March.
- Joshua C.C. Chan & Angelia L. Grant, 2015. "A Bayesian model comparison for trend-cycle decompositions of output," CAMA Working Papers 2015-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Agbeyegbe, Terence D., 2020. "Bayesian analysis of output gap in Barbados," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
- Zied Ftiti & Fredj Jawadi, 2019. "Forecasting Inflation Uncertainty in the United States and Euro Area," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 455-476, June.
- Dominik Bertsche & Robin Braun, 2022.
"Identification of Structural Vector Autoregressions by Stochastic Volatility,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 328-341, January.
- Dominik Bertsche & Robin Braun, 2017. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2017-11, Department of Economics, University of Konstanz.
- 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.
- Bertsche, Dominik & Braun, Robin, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181631, Verein für Socialpolitik / German Economic Association.
- Bertsche, Dominik & Braun, Robin, 2020. "Identification of structural vector autoregressions by stochastic volatility," Bank of England working papers 869, Bank of England.
- Joshua C.C. Chan & Todd E. Clark & Gary Koop, 2018.
"A New Model of Inflation, Trend Inflation, and Long‐Run Inflation Expectations,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(1), pages 5-53, February.
- Joshua C. C. Chan & Todd E. Clark & Gary Koop, 2015. "A New Model of Inflation, Trend Inflation, and Long-Run Inflation Expectations," Working Papers (Old Series) 1520, Federal Reserve Bank of Cleveland.
- repec:bny:wpaper:0117 is not listed on IDEAS
- Michael P Clements & Ana Beatriz Galvao, 2017. "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance icma-dp2017-01, Henley Business School, University of Reading.
- Joshua C C Chan & Cody Y L Hsiao, 2013. "Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence," CAMA Working Papers 2013-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Juan Angel García & Sebastian E. V. Werner, 2021. "Inflation News and Euro-Area Inflation Expectations," International Journal of Central Banking, International Journal of Central Banking, vol. 17(3), pages 1-60, September.
- 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).
- Joshua C. C. Chan & Aubrey Poon & Dan Zhu, 2023. "High-Dimensional Conditionally Gaussian State Space Models with Missing Data," Papers 2302.03172, arXiv.org.
- 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.
- Joshua C.C. Chan & Eric Eisenstat, 2013. "Gibbs Samplers for VARMA and Its Extensions," ANU Working Papers in Economics and Econometrics 2013-604, Australian National University, College of Business and Economics, School of Economics.
- Joshua Chan & Arnaud Doucet & Roberto León-González & Rodney W. Strachan, 2018.
"Multivariate stochastic volatility with co-heteroscedasticity,"
CAMA Working Papers
2018-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Joshua Chan & Arnaud Doucet & Roberto Leon-Gonzalez & Rodney W. Strachan, 2018. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," GRIPS Discussion Papers 18-12, National Graduate Institute for Policy Studies.
- CHAN Joshua & DOUCET Arnaud & Roberto Leon-Gonzalez & STRACHAN Rodney W., 2020. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," GRIPS Discussion Papers 20-09, National Graduate Institute for Policy Studies.
- Joshua Chan & Arnaud Doucet & Roberto León-González & Rodney W. Strachan, 2018. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," Working Paper series 18-38, Rimini Centre for Economic Analysis.
- Beatrice Franzolini & Alexandros Beskos & Maria De Iorio & Warrick Poklewski Koziell & Karolina Grzeszkiewicz, 2022. "Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market," Papers 2208.00952, arXiv.org, revised May 2023.
- Knüppel, Malte & Krüger, Fabian, 2017.
"Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts,"
VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking
168294, Verein für Socialpolitik / German Economic Association.
- Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
- Jean Pierre Fernández Prada Saucedo & Gabriel Rodríguez, 2020. "Modeling the Volatility of Returns on Commodities: An Application and Empirical Comparison of GARCH and SV Models," Documentos de Trabajo / Working Papers 2020-484, Departamento de Economía - Pontificia Universidad Católica del Perú.
- Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
- Na Guo & Bo Zhang & Jamie L. Cross, 2022. "Time‐varying trend models for forecasting inflation in Australia," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 316-330, March.
- Joshua C. C. Chan, 2018.
"Specification tests for time-varying parameter models with stochastic volatility,"
Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 807-823, September.
- 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.
- Chen, Liyuan & Zerilli, Paola & Baum, Christopher F., 2019.
"Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications,"
Energy Economics, Elsevier, vol. 79(C), pages 111-129.
- Liyuan Chen & Paola Zerilli & Christopher F Baum, 2018. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Boston College Working Papers in Economics 953, Boston College Department of Economics.
- Chenxing Li & John M. Maheu & Qiao Yang, 2024.
"An infinite hidden Markov model with stochastic volatility,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2187-2211, September.
- Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
- Baltuttis, Dennik & Töppel, Jannick & Tränkler, Timm & Wiethe, Christian, 2020. "Managing the risks of energy efficiency insurances in a portfolio context: An actuarial diversification approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
- Chang, Hao-Wen & Lin, Chinho, 2023. "Currency portfolio behavior in seven major Asian markets," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 540-559.
- Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
- Eric Eisenstat & Rodney W. Strachan, 2016.
"Modelling Inflation Volatility,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(5), pages 805-820, August.
- Eric Eisenstat & Rodney Strachan, 2014. "Modelling Inflation Volatility," Working Paper series 43_14, Rimini Centre for Economic Analysis.
- Eric Eisenstat & Rodney W. Strachan, 2014. "Modelling Inflation Volatility," CAMA Working Papers 2014-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Eric Eisenstat & Rodney W. Strachan, 2014. "Modelling Inflation Volatility," CAMA Working Papers 2014-21, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Nonejad, Nima, 2015. "Flexible model comparison of unobserved components models using particle Gibbs with ancestor sampling," Economics Letters, Elsevier, vol. 133(C), pages 35-39.
- Chan, Joshua C.C. & Grant, Angelia L., 2016.
"Modeling energy price dynamics: GARCH versus stochastic volatility,"
Energy Economics, Elsevier, vol. 54(C), pages 182-189.
- Joshua C.C. Chan & Angelia L. Grant, 2015. "Modeling energy price dynamics: GARCH versus stochastic volatility," CAMA Working Papers 2015-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Joshua C. C. Chan, 2020.
"Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
- Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Zhang, Bo & Chan, Joshua C.C. & Cross, Jamie L., 2020.
"Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts,"
International Journal of Forecasting, Elsevier, vol. 36(4), pages 1318-1328.
- Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," CAMA Working Papers 2018-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Nima Nonejad, 2021. "Using the conditional volatility channel to improve the accuracy of aggregate equity return predictions," Empirical Economics, Springer, vol. 61(2), pages 973-1009, August.
- Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar & Wolfgang Schmid & Anil K. Bera, 2023. "Spatial and Spatiotemporal Volatility Models: A Review," Papers 2308.13061, arXiv.org.
- Nonejad, Nima, 2014. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," MPRA Paper 55662, University Library of Munich, Germany.
- Mengheng Li & Siem Jan Koopman, 2021. "Unobserved components with stochastic volatility: Simulation‐based estimation and signal extraction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 614-627, August.
- Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
- Joshua C. C. Chan, 2017.
"The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
- Joshua C.C. Chan, 2015. "The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling," CAMA Working Papers 2015-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Terence D. Agbeyegbe, 2023. "The Link Between Output Growth and Output Growth Volatility: Barbados," Annals of Data Science, Springer, vol. 10(3), pages 787-804, June.
- Daniel Kaufmann, 2019. "Nominal stability over two centuries," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 155(1), pages 1-23, December.
- Zouhaier Dhifaoui, 2022. "Determinism and Non-linear Behaviour of Log-return and Conditional Volatility: Empirical Analysis for 26 Stock Markets," South Asian Journal of Macroeconomics and Public Finance, , vol. 11(1), pages 69-94, June.
- Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
- Nima Nonejad, 2019. "Has the 2008 financial crisis and its aftermath changed the impact of inflation on inflation uncertainty in member states of the european monetary union?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(2), pages 246-276, May.
- Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
- Joshua C.C. Chan & Angelia L. Grant, 2014. "Issues in Comparing Stochastic Volatility Models Using the Deviance Information Criterion," CAMA Working Papers 2014-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Lu Yang & Shigeyuki Hamori, 2018. "Modeling The Dynamics Of International Agricultural Commodity Prices: A Comparison Of Garch And Stochastic Volatility Models," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(03), pages 1-20, September.
- Wang, Renhe & Wang, Tong & Qian, Zhiyong & Hu, Shulan, 2023. "A Bayesian estimation approach of random switching exponential smoothing with application to credit forecast," Finance Research Letters, Elsevier, vol. 58(PC).
- Qureshi, Irfan, 2015. "What are monetary policy shocks?," The Warwick Economics Research Paper Series (TWERPS) 1086, University of Warwick, Department of Economics.
- Chan, Joshua C.C. & Santi, Caterina, 2021. "Speculative bubbles in present-value models: A Bayesian Markov-switching state space approach," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
- Nonejad, Nima, 2014. "Particle Gibbs with Ancestor Sampling Methods for Unobserved Component Time Series Models with Heavy Tails, Serial Dependence and Structural Breaks," MPRA Paper 55664, University Library of Munich, Germany.
- Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
- Töppel, Jannick & Tränkler, Timm, 2019. "Modeling energy efficiency insurances and energy performance contracts for a quantitative comparison of risk mitigation potential," Energy Economics, Elsevier, vol. 80(C), pages 842-859.
- Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.
- Joshua C.C. Chan & Eric Eisenstat, 2015. "Efficient estimation of Bayesian VARMAs with time-varying coefficients," CAMA Working Papers 2015-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- repec:bny:wpaper:0092 is not listed on IDEAS
- Malte Knüppel & Fabian Krüger, 2022.
"Forecast uncertainty, disagreement, and the linear pool,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
- Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
- Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.
- Jiang, Yong & Zhou, Zhongbao & Liu, Qing & Lin, Ling & Xiao, Helu, 2020. "How do oil price shocks affect the output volatility of the U.S. energy mining industry? The roles of structural oil price shocks," Energy Economics, Elsevier, vol. 87(C).
- Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
- Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
- Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.