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Forecasting in the Presence of Instabilities: How We Know Whether Models Predict Well and How to Improve Them

Citations

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Cited by:

  1. Moramarco, Graziano, 2024. "Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States," International Journal of Forecasting, Elsevier, vol. 40(2), pages 777-795.
  2. Massacci, Daniele & Kapetanios, George, 2024. "Forecasting in factor augmented regressions under structural change," International Journal of Forecasting, Elsevier, vol. 40(1), pages 62-76.
  3. N. Kundan Kishor, 2024. "Does the Zillow rent measure help predict CPI rent inflation?," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 59(4), pages 220-226, October.
  4. Carola Conces Binder & Rodrigo Sekkel, 2024. "Central bank forecasting: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 342-364, April.
  5. Pietro Giorgio Lovaglio, 2025. "Cross‐Learning With Panel Data Modeling for Stacking and Forecast Time Series Employment in Europe," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 753-780, March.
  6. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
  7. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
  8. Philip Hans Franses, 2024. "Incorporating judgment in forecasting models in times of crisis," Futures & Foresight Science, John Wiley & Sons, vol. 6(4), December.
  9. James Mitchell & Aubrey Poon & Dan Zhu, 2024. "Constructing density forecasts from quantile regressions: Multimodality in macrofinancial dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 790-812, August.
  10. Thompson, Ryan & Qian, Yilin & Vasnev, Andrey L., 2024. "Flexible global forecast combinations," Omega, Elsevier, vol. 126(C).
  11. Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Predictive Density Combination Using a Tree-Based Synthesis Function," Staff Working Papers 23-61, Bank of Canada.
  12. Andrea Bastianin & Elisabetta Mirto & Yan Qin & Luca Rossini, 2024. "What drives the European carbon market? Macroeconomic factors and forecasts," Papers 2402.04828, arXiv.org, revised Feb 2024.
  13. Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023. "Empirically-transformed linear opinion pools," International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.
  14. Mekelburg, Erik & Strauss, Jack, 2024. "Pooling and winsorizing machine learning forecasts to predict stock returns with high-dimensional data," Journal of Empirical Finance, Elsevier, vol. 79(C).
  15. Li, Dongxin & Zhang, Li & Li, Lihong, 2023. "Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model," International Review of Financial Analysis, Elsevier, vol. 88(C).
  16. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
  17. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
  18. Héctor M. Zárate-Solano & Norberto Rodríguez-Niño, 2024. "Consumer Prices Trends in Colombia: Detecting Breaks and Forecasting Infation," Borradores de Economia 1289, Banco de la Republica de Colombia.
  19. Stylianos Asimakopoulos & Marco Lorusso & Francesco Ravazzolo, 2023. "A Bayesian DSGE Approach to Modelling Cryptocurrency"," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 1012-1035, December.
  20. Konstantin Boss & Finja Krueger & Conghan Zheng & Tobias Heidland & Andre Groeger, 2023. "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers 1387, Barcelona School of Economics.
  21. Fameliti Stavroula & Skintzi Vasiliki, 2024. "Macroeconomic attention and commodity market volatility," Empirical Economics, Springer, vol. 67(5), pages 1967-2007, November.
  22. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
  23. Bennett, Donyetta & Mekelburg, Erik & Strauss, Jack & Williams, T.H., 2024. "Unlocking the black box of sentiment and cryptocurrency: What, which, why, when and how?," Global Finance Journal, Elsevier, vol. 60(C).
  24. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org, revised May 2024.
  25. Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
  26. Fabrizio Iacone & Luca Rossini & Andrea Viselli, 2024. "Comparing predictive ability in presence of instability over a very short time," Papers 2405.11954, arXiv.org.
  27. Eric Hillebrand & Jakob Guldbæk Mikkelsen & Lars Spreng & Giovanni Urga, 2023. "Exchange rates and macroeconomic fundamentals: Evidence of instabilities from time‐varying factor loadings," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 857-877, September.
  28. Yolanda S. Stander, 2024. "A News Sentiment Index to Inform International Financial Reporting Standard 9 Impairments," JRFM, MDPI, vol. 17(7), pages 1-23, July.
  29. Bobeica, Elena & Hartwig, Benny, 2021. "The COVID-19 shock and challenges for time series models," Working Paper Series 2558, European Central Bank.
  30. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2025. "MLOps Monitoring at Scale for Digital Platforms," Papers 2504.16789, arXiv.org.
  31. Ray C. Fair, 2022. "A note on the fed’s power to lower inflation," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 57(2), pages 56-63, April.
  32. Ciner, Cetin, 2025. "Forecasting the aggregate market volatility by boosted neural networks," Finance Research Letters, Elsevier, vol. 72(C).
  33. Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.
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