Forecast evaluation and combination

Citations

Cited by:

1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
2. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
   • Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
3. Jose A. Lopez & Christian Walter, 1997. "Is implied correlation worth calculating? Evidence from foreign exchange options and historical data," Research Paper 9730, Federal Reserve Bank of New York.
   • Jose A. Lopez & Christian Walter, 2000. "Is implied correlation worth calculating? Evidence from foreign exchange options and historical data," Working Paper Series 2000-02, Federal Reserve Bank of San Francisco.
4. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2022. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 29-50, Emerald Group Publishing Limited.
   • Kajal Lahiri & Huaming Peng & Xuguang Sheng, 2015. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," CESifo Working Paper Series 5468, CESifo.
   • Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
   • Kajal Lahiri & Huaming Peng & Xuguang Sheng, 2020. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," CESifo Working Paper Series 8810, CESifo.
5. Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
6. Bofinger, Peter & Schmidt, Robert, 2003. "Should one rely on professional exchange rate forecasts: An empirical analysis of professional forecasts for the €/US-$ rate," W.E.P. - Würzburg Economic Papers 38, University of Würzburg, Department of Economics.
7. Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Anthony S. Tay & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics: International Evidence," PIER Working Paper Archive 06-016, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
   • Anthony S. Tay & Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence," Finance Working Papers 22481, East Asian Bureau of Economic Research.
   • Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Anthony S. Tay & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence," Finance Working Papers 22075, East Asian Bureau of Economic Research.
8. Christoffersen, Peter F & Diebold, Francis X, 1998. "Cointegration and Long-Horizon Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 450-458, October.
   • Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and Long-Horizon Forecasting," NBER Technical Working Papers 0217, National Bureau of Economic Research, Inc.
   • Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and long-horizon forecasting," Working Papers 97-14, Federal Reserve Bank of Philadelphia.
   • Mr. Francis X. Diebold & Mr. Peter F. Christoffersen, 1997. "Cointegration and Long-Horizon Forecasting," IMF Working Papers 1997/061, International Monetary Fund.
9. Ke Yang & Langnan Chen & Fengping Tian, 2015. "Realized Volatility Forecast of Stock Index Under Structural Breaks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(1), pages 57-82, January.
10. Jose A. Lopez, 1999. "Methods for evaluating value-at-risk estimates," Economic Review, Federal Reserve Bank of San Francisco, pages 3-17.
    • Jose A. Lopez, 1998. "Methods for evaluating value-at-risk estimates," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Oct), pages 119-124.
    • Jose A. Lopez, 1998. "Methods for evaluating value-at-risk estimates," Research Paper 9802, Federal Reserve Bank of New York.
11. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
12. Jeremy Berkowitz, 1999. "Evaluating the forecasts of risk models," Finance and Economics Discussion Series 1999-11, Board of Governors of the Federal Reserve System (U.S.).
13. Shahzad Ahmad & Farooq Pasha, 2015. "A Pragmatic Model for Monetary Policy Analysis I: The Case of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 1-42.
14. M. Hashem Pesaran & Paolo Zaffaroni, 2004. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi Asset Volatility Models for Risk Management," CESifo Working Paper Series 1358, CESifo.
    • Hashem Pesaran & Paolo Zaffaroni & Banca d'Italia), 2004. "Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management," Money Macro and Finance (MMF) Research Group Conference 2004 101, Money Macro and Finance Research Group.
    • Pesaran, M. Hashem & Zaffaroni, Paolo, 2005. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi-Asset Volatility Models for Risk Management," CEPR Discussion Papers 5279, C.E.P.R. Discussion Papers.
    • M. Hashem Pesaran & Paolo Zaffaroni, 2004. "Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management," IEPR Working Papers 04.3, Institute of Economic Policy Research (IEPR).
15. Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
16. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, "undated". "Evaluating Density Forecasts," CARESS Working Papres 97-18, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences.
    • Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating Density Forecasts," Center for Financial Institutions Working Papers 97-37, Wharton School Center for Financial Institutions, University of Pennsylvania.
    • Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating density forecasts," Working Papers 97-6, Federal Reserve Bank of Philadelphia.
    • Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating Density Forecasts," NBER Technical Working Papers 0215, National Bureau of Economic Research, Inc.
17. Dopke, Jorg & Fritsche, Ulrich, 2006. "When do forecasters disagree? An assessment of German growth and inflation forecast dispersion," International Journal of Forecasting, Elsevier, vol. 22(1), pages 125-135.
18. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
19. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
20. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
    • Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2009. "Does forecast combination improve Norges Bank inflation forecasts?," Working Paper 2009/01, Norges Bank.
    • Hilde C. Bj�rnland & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud & Christie Smith, 2010. "Does forecast combination improve Norges Bank inflation forecasts?," Working Papers No 2/2010, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
21. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
22. Zhang, Gang & Yang, Dazhi & Galanis, George & Androulakis, Emmanouil, 2022. "Solar forecasting with hourly updated numerical weather prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
23. No, Sung Chul & Salassi, Michael E., 2006. "Dynamic Analysis and Forecasts of Rough Rice Price under Government Price Support Program: An Application of Bayesian VAR," 2006 Annual Meeting, February 5-8, 2006, Orlando, Florida 35279, Southern Agricultural Economics Association.
24. Michael P. Clements & David I. Harvey, 2010. "Forecast encompassing tests and probability forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(6), pages 1028-1062.
    • Clements, Michael P & Harvey, David I, 2006. "Forecast Encompassing Tests and Probability Forecasts," The Warwick Economics Research Paper Series (TWERPS) 774, University of Warwick, Department of Economics.
    • Clements, Michael P. & Harvey, David I., 2006. "Forecast Encompassing Tests and Probability Forecasts," Economic Research Papers 269744, University of Warwick - Department of Economics.
25. Kitchen, John, 2003. "Observed Relationships Between Economic and Technical Receipts Revisions in Federal Budget Projections," National Tax Journal, National Tax Association;National Tax Journal, vol. 56(2), pages 337-353, June.
    • Kitchen, John, 2003. "Observed Relationships Between Economic And Technical Receipts Revisions In Federal Budget Projections," MPRA Paper 22004, University Library of Munich, Germany.
26. Fiechter, Chad & Kuethe, Todd & Zhang, Wendong, 2023. "Information Rigidities and Farmland Value Expectations," ISU General Staff Papers 202306131414240000, Iowa State University, Department of Economics.
27. Hofmann, Boris, 2009. "Do monetary indicators lead euro area inflation?," Journal of International Money and Finance, Elsevier, vol. 28(7), pages 1165-1181, November.
    • Hofmann, Boris, 2008. "Do monetary indicators lead euro area inflation?," Working Paper Series 867, European Central Bank.
28. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    • Bec, F. & Mogliani, M., 2013. "Nowcasting French GDP in Real-Time from Survey Opinions: Information or Forecast Combinations?," Working papers 436, Banque de France.
    • Frédérique Bec & Matteo Mogliani, 2013. "Nowcasting French GDP in Real-Time from Survey Opinions : Information or Forecast Combinations ?," Working Papers 2013-21, Center for Research in Economics and Statistics.
29. Malte Knüppel & Guido Schultefrankenfeld, 2012. "How Informative Are Central Bank Assessments of Macroeconomic Risks?," International Journal of Central Banking, International Journal of Central Banking, vol. 8(3), pages 87-139, September.
    • Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "How informative are central bank assessments of macroeconomic risks?," Discussion Paper Series 1: Economic Studies 2011,13, Deutsche Bundesbank.
30. Elliott, Graham & Timmermann, Allan, 2004. "Optimal forecast combinations under general loss functions and forecast error distributions," Journal of Econometrics, Elsevier, vol. 122(1), pages 47-79, September.
    • Elliott, Graham & Timmermann, Allan, 2002. "Optimal Forecast Combination Under General Loss Functions and Forecast Error Distributions," University of California at San Diego, Economics Working Paper Series qt15r9t2q2, Department of Economics, UC San Diego.
31. Shao, Renyuan & Roe, Brian E., 2001. "Underpinnings for Prospective, Net Revenue Forecasting in Hog Finishing: Characterizing the Joint Distribution of Corn, Soybean Meal and Lean Hogs Time Series," 2001 Annual meeting, August 5-8, Chicago, IL 20664, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
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32. Jose A. Lopez, 1996. "Regulatory Evaluation of Value-at-Risk Models," Center for Financial Institutions Working Papers 96-51, Wharton School Center for Financial Institutions, University of Pennsylvania.
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33. Bryan Campbell & Steve Murphy, 2006. "The Recent Performance of the Canadian Forecasting Industry," Canadian Public Policy, University of Toronto Press, vol. 32(1), pages 23-40, March.
34. Michael S. O’Doherty & N. E. Savin & Ashish Tiwari, 2016. "Evaluating Hedge Funds with Pooled Benchmarks," Management Science, INFORMS, vol. 62(1), pages 69-89, January.
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36. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
37. Robin C. Sickles & Jiaqi Hao & Chenjun Shang, 2014. "Panel data and productivity measurement: an analysis of Asian productivity trends," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 12(3), pages 211-231, August.
38. Leitner, Johannes & Schmidt, Robert & Bofinger, Peter, 2003. "Biases of professional exchange rate forecasts: Psychological explanations and an experimentally based comparison to novices," W.E.P. - Würzburg Economic Papers 39, University of Würzburg, Department of Economics.
    • Bofinger, Peter & Schmidt, Robert & Leitner, Johannes, 2004. "Biases of Professional Exchange Rate Forecasts: Psychological Explanations and an Experimentally-Based Comparison to Novices," CEPR Discussion Papers 4230, C.E.P.R. Discussion Papers.
39. Barbara Rossi & Tatevik Sekhposyan, 2016. "Forecast Rationality Tests in the Presence of Instabilities, with Applications to Federal Reserve and Survey Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 507-532, April.
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40. Chen, Yi-Ting & Liu, Chu-An, 2023. "Model averaging for asymptotically optimal combined forecasts," Journal of Econometrics, Elsevier, vol. 235(2), pages 592-607.
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41. Friedrich Heinemann, 2006. "Planning or Propaganda? An Evaluation of Germany's Medium-term Budgetary Planning," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 62(4), pages 551-578, December.
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42. Barrera, Carlos R., 2010. "Redes neuronales para predecir el tipo de cambio diario," Working Papers 2010-001, Banco Central de Reserva del Perú.
43. Raffaella Giacomini, 2002. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests: Asymptotic and Bootstrap Methods," Boston College Working Papers in Economics 583, Boston College Department of Economics.
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44. Grömling, Michael, 2002. "Konjunkturprognosen: Methoden, Risiken und Treffsicherheiten," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, vol. 29(2), pages 18-26.
45. Weidong Tian & Qing Zhou, 2017. "Asset Pricing Model Uncertainty: A Tradeoff between Bias and Variance," International Review of Finance, International Review of Finance Ltd., vol. 17(2), pages 289-324, June.
46. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
47. Blanc, Sebastian M. & Setzer, Thomas, 2016. "When to choose the simple average in forecast combination," Journal of Business Research, Elsevier, vol. 69(10), pages 3951-3962.
48. Muhammad Nadim Hanif & Muhammad Jahanzeb Malik, 2015. "Evaluating the Performance of Inflation Forecasting Models of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 43-78.
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49. Ulrich Fritsche & Artur Tarassow, 2017. "Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014," IMK Studies 54-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
50. Andrawis, Robert R. & Atiya, Amir F. & El-Shishiny, Hisham, 2011. "Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition," International Journal of Forecasting, Elsevier, vol. 27(3), pages 672-688, July.
51. Masahiro Fukuhara & Yasufumi Saruwatari, 2007. "A Model Forecasting Risk for Emerging Market Currencies," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(4), pages 325-340, December.
52. Yudong Wang & Li Liu, 2016. "Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging," Empirical Economics, Springer, vol. 50(4), pages 1481-1509, June.
53. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.
54. Giorgio Valente & Lucio Sarno, 2004. "Comparing the accuracy of density forecasts from competing models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(8), pages 541-557.
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55. Hamid Baghestani, 2022. "Mortgage rate predictability and consumer home-buying assessments," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 593-603, July.
56. Cheng, Xu & Hansen, Bruce E., 2015. "Forecasting with factor-augmented regression: A frequentist model averaging approach," Journal of Econometrics, Elsevier, vol. 186(2), pages 280-293.
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59. Grant Allan, 2012. "Evaluating the usefulness of forecasts of relative growth," Working Papers 1214, University of Strathclyde Business School, Department of Economics.
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63. Diebold, Francis X. & Shin, Minchul, 2019. "Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1679-1691.
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64. Zvi Schwartz & Timothy Webb & Jean-Pierre I van der Rest & Larissa Koupriouchina, 2021. "Enhancing the accuracy of revenue management system forecasts: The impact of machine and human learning on the effectiveness of hotel occupancy forecast combinations across multiple forecasting horizo," Tourism Economics, , vol. 27(2), pages 273-291, March.
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73. Khoshrou, Abdolrahman & Pauwels, Eric J., 2019. "Short-term scenario-based probabilistic load forecasting: A data-driven approach," Applied Energy, Elsevier, vol. 238(C), pages 1258-1268.
74. Laura Coroneo & Fabrizio Iacone, 2020. "Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 391-409, June.
75. Peter Reinhard Hansen & Asger Lunde, 2005. "A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 525-554.
76. Murray, Paul W. & Agard, Bruno & Barajas, Marco A., 2018. "ASACT - Data preparation for forecasting: A method to substitute transaction data for unavailable product consumption data," International Journal of Production Economics, Elsevier, vol. 203(C), pages 264-275.
77. Di Bu & Simone Kelly & Yin Liao & Qing Zhou, 2018. "A hybrid information approach to predict corporate credit risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1062-1078, September.
78. Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
79. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
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