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Pockets of Predictability

Citations

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Cited by:

  1. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
  2. Gary Koop & Dimitris Korobilis, 2023. "Bayesian Dynamic Variable Selection In High Dimensions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 1047-1074, August.
  3. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
  4. Jinbo Cai & Wenze Li & Wenjie Wang, 2025. "Electricity Market Predictability: Virtues of Machine Learning and Links to the Macroeconomy," Papers 2507.07477, arXiv.org.
  5. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
  6. Yu, Deshui & Chen, Li, 2024. "Local predictability of stock returns and cash flows," Journal of Empirical Finance, Elsevier, vol. 77(C).
  7. Deshui Yu & Yayi Yan, 2023. "Joint dynamics of stock returns and cash flows: A time‐varying present‐value framework," Financial Management, Financial Management Association International, vol. 52(3), pages 513-541, September.
  8. Sun, Yulong & Wang, Kai & Zhou, Zhiping, 2025. "Fear propagation and return dynamics," Journal of Banking & Finance, Elsevier, vol. 173(C).
  9. Fan, Rui & Lee, Ji Hyung & Shin, Youngki, 2023. "Predictive quantile regression with mixed roots and increasing dimensions: The ALQR approach," Journal of Econometrics, Elsevier, vol. 237(2).
  10. Moench, Emanuel & Stein, Tobias, 2019. "Comment on “Monetary Policy Communication, Policy Slope, and the Stock Market” by Andreas Neuhierl and Michael Weber," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 156-161.
  11. Rahman, Oriana & Semenov, Andrei, 2025. "Subjective probabilities under behavioral heuristics," International Review of Economics & Finance, Elsevier, vol. 98(C).
  12. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
  13. David I. Harvey & Stephen J. Leybourne & Robert Sollis & A.M. Robert Taylor, 2021. "Real‐time detection of regimes of predictability in the US equity premium," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 45-70, January.
  14. Wan, Runqing & Xing, Bingxin Ann, 2025. "Can switching between predictive models and the historical average improve bond return predictability?," Finance Research Letters, Elsevier, vol. 75(C).
  15. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
  16. Guillaume Coqueret & Martial Laguerre, 2025. "Overparametrized models with posterior drift," Papers 2506.23619, arXiv.org.
  17. Barbara Rossi, 2021. "Forecasting in the Presence of Instabilities: How We Know Whether Models Predict Well and How to Improve Them," Journal of Economic Literature, American Economic Association, vol. 59(4), pages 1135-1190, December.
  18. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
  19. Demetrescu, Matei & Georgiev, Iliyan & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2022. "Testing for episodic predictability in stock returns," Journal of Econometrics, Elsevier, vol. 227(1), pages 85-113.
  20. Yu, Deshui & Yan, Yayi, 2025. "A system of time-varying models for predictive regressions," Journal of Empirical Finance, Elsevier, vol. 82(C).
  21. Yannick Hoga, 2024. "Persistence-Robust Break Detection in Predictive Quantile and CoVaR Regressions," Papers 2410.05861, arXiv.org.
  22. Anibal Emiliano Da Silva Neto & Jesús Gonzalo & Jean‐Yves Pitarakis, 2021. "Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 713-741, June.
  23. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2019. "Predictive Regressions," UC3M Working papers. Economics 28554, Universidad Carlos III de Madrid. Departamento de Economía.
  24. Schlosky, Minh Tam Tammy & Karadas, Serkan & Stivers, Adam, 2024. "Forecasting U.S. Stock Returns Conditional on Geopolitical Risk and Business Cycles," International Review of Financial Analysis, Elsevier, vol. 96(PB).
  25. 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.
  26. Eraslan, Sercan & Schröder, Maximilian, 2023. "Nowcasting GDP with a pool of factor models and a fast estimation algorithm," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1460-1476.
  27. Lof, Matthijs & Nyberg, Henri, 2024. "Discount rates and cash flows: A local projection approach," Journal of Banking & Finance, Elsevier, vol. 162(C).
  28. 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).
  29. Dong, Dairui & Hua, Xia & Wang, Binxu, 2025. "The short-term predictability pockets in China," Pacific-Basin Finance Journal, Elsevier, vol. 91(C).
  30. 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).
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