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Comparing Possibly Misspecified Forecasts

Citations

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Cited by:

  1. Tobias Fissler & Yannick Hoga, 2024. "How to Compare Copula Forecasts?," Papers 2410.04165, arXiv.org.
  2. Xenxo Vidal-Llana & Carlos Salort Sánchez & Vincenzo Coia & Montserrat Guillen, 2022. ""Non-Crossing Dual Neural Network: Joint Value at Risk and Conditional Tail Expectation estimations with non-crossing conditions"," IREA Working Papers 202215, University of Barcelona, Research Institute of Applied Economics, revised Oct 2022.
  3. Llorens-Terrazas, Jordi & Brownlees, Christian, 2023. "Projected Dynamic Conditional Correlations," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1761-1776.
  4. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
  5. Alexander Henzi & Johanna F Ziegel, 2022. "Valid sequential inference on probability forecast performance [A comparison of the ECMWF, MSC, and NCEP global ensemble prediction systems]," Biometrika, Biometrika Trust, vol. 109(3), pages 647-663.
  6. Onno Kleen, 2024. "Scaling and measurement error sensitivity of scoring rules for distribution forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 833-849, August.
  7. Fissler Tobias & Ziegel Johanna F., 2021. "On the elicitability of range value at risk," Statistics & Risk Modeling, De Gruyter, vol. 38(1-2), pages 25-46, January.
  8. Tobias Fissler & Jana Hlavinová & Birgit Rudloff, 2021. "Elicitability and identifiability of set-valued measures of systemic risk," Finance and Stochastics, Springer, vol. 25(1), pages 133-165, January.
  9. Denuit, Michel & Trufin, Julien, 2024. "Convex and Lorenz orders under balance correction in nonlife insurance pricing: Review and new developments," Insurance: Mathematics and Economics, Elsevier, vol. 118(C), pages 123-128.
  10. Conrad, Christian & Lahiri, Kajal, 2024. "Heterogeneous Expectations among Professional Forecasters," Working Papers 0754, University of Heidelberg, Department of Economics.
  11. Denuit, Michel & Trufin, Julien, 2022. "Autocalibration by balance correction in nonlife insurance pricing," LIDAM Discussion Papers ISBA 2022041, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  12. Takaaki Koike & Cathy W. S. Chen & Edward M. H. Lin, 2024. "Forecasting and Backtesting Gradient Allocations of Expected Shortfall," Papers 2401.11701, arXiv.org, revised Jun 2024.
  13. Alexander I. Jordan & Anja Mühlemann & Johanna F. Ziegel, 2022. "Characterizing the optimal solutions to the isotonic regression problem for identifiable functionals," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(3), pages 489-514, June.
  14. Cathy W. S. Chen & Takaaki Koike & Wei‐Hsuan Shau, 2024. "Tail risk forecasting with semiparametric regression models by incorporating overnight information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1492-1512, August.
  15. Cathy W. S. Chen & Takaaki Koike & Wei-Hsuan Shau, 2024. "Tail risk forecasting with semi-parametric regression models by incorporating overnight information," Papers 2402.07134, arXiv.org.
  16. Oh, Dong Hwan & Patton, Andrew J., 2024. "Better the devil you know: Improved forecasts from imperfect models," Journal of Econometrics, Elsevier, vol. 242(1).
  17. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jul 2024.
  18. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.
  19. Charles F. Manski, 2021. "Econometrics for Decision Making: Building Foundations Sketched by Haavelmo and Wald," Econometrica, Econometric Society, vol. 89(6), pages 2827-2853, November.
  20. Lazar, Emese & Wang, Shixuan & Xue, Xiaohan, 2023. "Loss function-based change point detection in risk measures," European Journal of Operational Research, Elsevier, vol. 310(1), pages 415-431.
  21. Dong Hwan Oh & Andrew J. Patton, 2021. "Better the Devil You Know: Improved Forecasts from Imperfect Models," Finance and Economics Discussion Series 2021-071, Board of Governors of the Federal Reserve System (U.S.).
  22. Mucahit Aygun & Fabio Bellini & Roger J. A. Laeven, 2023. "Elicitability of Return Risk Measures," Papers 2302.13070, arXiv.org, revised Mar 2023.
  23. Tobias Fissler & Yannick Hoga, 2021. "Backtesting Systemic Risk Forecasts using Multi-Objective Elicitability," Papers 2104.10673, arXiv.org, revised Feb 2022.
  24. Boskabadi, Elahe, 2022. "Economic policy uncertainty and forecast bias in the survey of professional forecasters," MPRA Paper 115081, University Library of Munich, Germany.
  25. Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
  26. Yen, Yu-Min & Yen, Tso-Jung, 2021. "Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions," International Journal of Forecasting, Elsevier, vol. 37(2), pages 733-758.
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