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Optimal Portfolio Choice Under Decision‐Based Model Combinations

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Cited by:

  1. Faria, Gonçalo & Verona, Fabio, 2023. "Forecast combination in the frequency domain," Bank of Finland Research Discussion Papers 1/2023, Bank of Finland.
  2. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
  3. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
  4. Baştürk, N. & Borowska, A. & Grassi, S. & Hoogerheide, L. & van Dijk, H.K., 2019. "Forecast density combinations of dynamic models and data driven portfolio strategies," Journal of Econometrics, Elsevier, vol. 210(1), pages 170-186.
  5. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore & Wing-Keung Wong, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
  6. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  7. Martin, Gael M. & Loaiza-Maya, Rubén & Maneesoonthorn, Worapree & Frazier, David T. & Ramírez-Hassan, Andrés, 2022. "Optimal probabilistic forecasts: When do they work?," International Journal of Forecasting, Elsevier, vol. 38(1), pages 384-406.
  8. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
  9. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
  10. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
  11. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
  12. repec:zbw:bofrdp:2020_006 is not listed on IDEAS
  13. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
  14. Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2023. "Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 523-537, April.
  15. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
  16. Li, Chenxing, 2022. "A multivariate GARCH model with an infinite hidden Markov mixture," MPRA Paper 112792, University Library of Munich, Germany.
  17. 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.
  18. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
  19. Nuno Silva, 2015. "Industry based equity premium forecasts," GEMF Working Papers 2015-19, GEMF, Faculty of Economics, University of Coimbra.
  20. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
  21. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
  22. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
  23. Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
  24. McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
  25. Vigo Pereira, Caio, 2021. "Portfolio efficiency with high-dimensional data as conditioning information," International Review of Financial Analysis, Elsevier, vol. 77(C).
  26. David Puelz & P. Richard Hahn & Carlos M. Carvalho, 2020. "Portfolio selection for individual passive investing," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(1), pages 124-142, January.
  27. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
  28. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
  29. K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.
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