Density Forecasting: A Survey

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1. > Econometrics > Forecasting

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Cited by:

1. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
   • Li Li & Yanfei Kang & Feng Li, 2021. "Bayesian forecast combination using time-varying features," Papers 2108.02082, arXiv.org, revised Jun 2022.
2. Wojciech CHAREMZA & Carlos DÍAZ & Svetlana MAKAROVA, 2019. "Conditional Term Structure of Inflation Forecast Uncertainty: The Copula Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-18, March.
   • Wojciech Charemza & Carlos Díaz & Svetlana Makarova, 2015. "Conditional Term Structure of Inflation Forecast Uncertainty: The Copula Approach," Discussion Papers in Economics 15/07, Division of Economics, School of Business, University of Leicester.
3. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
   • van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
   • van Dijk, Dick & Teräsvirta, Timo & Franses, Philip Hans, 2000. "Smooth Transition Autoregressive Models - A Survey of Recent Developments," SSE/EFI Working Paper Series in Economics and Finance 380, Stockholm School of Economics, revised 17 Jan 2001.
4. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
   • Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2013. "Can macroeconomists forecast risk? Event-based evidence from the euro area SPF," Working Paper Series 1540, European Central Bank.
5. Balcilar, Mehmet & Katzke, Nico & Gupta, Rangan, 2017. "Do precious metal prices help in forecasting South African inflation?," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 63-72.
   • Mehmet Balcilar & Nico Katzke & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 03/2015, Stellenbosch University, Department of Economics.
   • Mehmet Balcilar & NICO KATZKE & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 15-05, Eastern Mediterranean University, Department of Economics.
   • Mehmet Balcilar & Nico Katzke & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 201510, University of Pretoria, Department of Economics.
6. Covas, Francisco B. & Rump, Ben & Zakrajšek, Egon, 2014. "Stress-testing US bank holding companies: A dynamic panel quantile regression approach," International Journal of Forecasting, Elsevier, vol. 30(3), pages 691-713.
   • Francisco Covas & Ben Rump & Egon Zakrajšek, 2013. "Stress-testing U.S. bank holding companies: a dynamic panel quantile regression approach," Finance and Economics Discussion Series 2013-55, Board of Governors of the Federal Reserve System (U.S.).
7. Pierre L Siklos, 2010. "Relative Price Shocks, Inflation Expectations, and the Role of Monetary Policy," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
8. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
   • Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
9. Perez-Quiros, Gabriel & Timmermann, Allan, 2001. "Business cycle asymmetries in stock returns: Evidence from higher order moments and conditional densities," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 259-306, July.
   • Allan Timmermann & Gabriel Perez-Quiros, 2000. "Business Cycle Asymmetries in Stock Returns: Evidence from Higher Order Moments and Conditional Densities," FMG Discussion Papers dp360, Financial Markets Group.
   • Perez-Quiros, G. & Timmermann, A., 2001. "Business Cycle Asymmetries in Stock Returns: Evidence from Higher Order Moments and Conditional Densities," Papers 58, Quebec a Montreal - Recherche en gestion.
   • Pérez Quirós, Gabriel & Timmermann, Allan, 2001. "Business cycle asymmetries in stock returns: evidence from higher order moments and conditional densities," Working Paper Series 58, European Central Bank.
   • Perez-Quiros, Gabriel & Timmermann, Allan, 2000. "Business cycle asymmetries in stock returns: evidence from higher order moments and conditional densities," LSE Research Online Documents on Economics 119098, London School of Economics and Political Science, LSE Library.
10. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
11. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
12. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    • David Hendry & Michael P. Clements, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Papers 2002-W11, Economics Group, Nuffield College, University of Oxford.
    • Hendry, David F & Michael P. Clements, 2002. "Economic Forecasting: Some Lessons from Recent Research," Royal Economic Society Annual Conference 2002 99, Royal Economic Society.
    • David Hendry & Michael P. Clements & Department of Economics & University of Warwick, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Series Working Papers 78, University of Oxford, Department of Economics.
    • Clements, Michael P. & Hendry, David F., 2001. "Economic forecasting: some lessons from recent research," Working Paper Series 82, European Central Bank.
13. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
14. Giacomini, Raffaella & Haefke, Christian & White, Halbert & Gottschling, Andreas, 2002. "Hypernormal Densities," University of California at San Diego, Economics Working Paper Series qt9wr373nt, Department of Economics, UC San Diego.
    • Raffaella Giacomini & Andreas Gottschling & Christian Haefke & Halbert White, 2002. "Hypernormal densities," Economics Working Papers 638, Department of Economics and Business, Universitat Pompeu Fabra.
    • Raffaella Giacomini & Andreas Gottschling & Christian Haefke & Halbert White, 2002. "Hypernormal Densities," Boston College Working Papers in Economics 584, Boston College Department of Economics.
15. 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.
    • Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
    • Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
16. G. Ascari & E. Marrocu, 2003. "Forecasting inflation: a comparison of linear Phillips curve models and nonlinear time serie models," Working Paper CRENoS 200307, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
17. Geoff Kenny & Thomas Kostka & Federico Masera, 2014. "How Informative are the Subjective Density Forecasts of Macroeconomists?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(3), pages 163-185, April.
    • Geoff Kenny & Thomas Kostka & Federico Masera, 2011. "How Informative are the Subjective Density Forecasts of Macroeconomists?," CESifo Working Paper Series 3671, CESifo.
    • Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2012. "How informative are the subjective density forecasts of macroeconomists?," Working Paper Series 1446, European Central Bank.
18. Lucio Sarno, 2003. "Nonlinear Exchange Rate Models: A Selective Overview," Rivista di Politica Economica, SIPI Spa, vol. 93(4), pages 3-46, July-Augu.
    • Lucio Sarno, 2003. "Nonlinear Exchange Rate Models: A Selective Overview," IMF Working Papers 2003/111, International Monetary Fund.
19. Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
20. Choy, Keen Meng & Leong, Kenneth & Tay, Anthony S., 2006. "Non-fundamental expectations and economic fluctuations: Evidence from professional forecasts," Journal of Macroeconomics, Elsevier, vol. 28(2), pages 446-460, June.
    • Keen Meng Choy & Kenneth Leong & Anthony S. Tay, 2003. "Non-Fundamental Expectations and Economic Fluctuations: Evidence from Professional Forecasts," Departmental Working Papers wp0306, National University of Singapore, Department of Economics.
21. Allen, P. Geoffrey & Morzuch, Bernard J., 2006. "Twenty-five years of progress, problems, and conflicting evidence in econometric forecasting. What about the next 25 years?," International Journal of Forecasting, Elsevier, vol. 22(3), pages 475-492.
22. Trino-Manuel Niguez & Javier Perote, 2004. "Forecasting the density of asset returns," STICERD - Econometrics Paper Series 479, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Niguez, Trino-Manuel & Perote, Javier, 2004. "Forecasting the density of asset returns," LSE Research Online Documents on Economics 6845, London School of Economics and Political Science, LSE Library.
23. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    • Edward Knotek & Saeed Zaman, 2020. "Real-time density nowcasts of US inflation: a model-combination approach," Working Papers 2015, University of Strathclyde Business School, Department of Economics.
    • Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
24. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    • Gloria Gonzalez-Rivera & Joao Henrique Mazzeu & Esther Ruiz & Helena Veiga, 2017. "A Bootstrap Approach for Generalized Autocontour Testing. Implications for VIX Forecast Densities," Working Papers 201709, University of California at Riverside, Department of Economics.
25. Alquier Pierre & Li Xiaoyin & Wintenberger Olivier, 2014. "Prediction of time series by statistical learning: general losses and fast rates," Dependence Modeling, De Gruyter, vol. 1, pages 65-93, January.
    • Alquier Pierre & Li Xiaoyin & Wintenberger Olivier, 2013. "Prediction of time series by statistical learning: general losses and fast rates," Dependence Modeling, De Gruyter, vol. 1(2013), pages 65-93, January.
26. repec:wyi:journl:002081 is not listed on IDEAS
27. Kannika Duangnate & James W. Mjelde, 2020. "Prequential forecasting in the presence of structure breaks in natural gas spot markets," Empirical Economics, Springer, vol. 59(5), pages 2363-2384, November.
28. George A. Krause, 2006. "Beyond the Norm," Rationality and Society, , vol. 18(2), pages 157-191, May.
29. Yushu Li & Jonas Andersson, 2020. "A likelihood ratio and Markov chain‐based method to evaluate density forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 47-55, January.
30. Michal Franta, 2016. "The Effect of Nonlinearity between Credit Conditions and Economic Activity on Density Forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 147-166, March.
    • Michal Franta, 2013. "The Effect of Non-Linearity Between Credit Conditions and Economic Activity on Density Forecasts," Working Papers 2013/09, Czech National Bank.
31. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    • Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
32. 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.
33. Chew Lian Chua & Sarantis Tsiaplias, 2009. "Can consumer sentiment and its components forecast Australian GDP and consumption?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 698-711.
    • Chew Lian Chua & Sarantis Tsiaplias, 2008. "Can Consumer Sentiment and Its Components Forecast Australian GDP and Consumption?," Melbourne Institute Working Paper Series wp2008n03, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
34. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.
    • Clements, Michael P, 2012. "Probability Distributions or Point Predictions? Survey Forecasts of US Output Growth and Inflation," The Warwick Economics Research Paper Series (TWERPS) 976, University of Warwick, Department of Economics.
    • Clements, Michael P., 2012. "Probability Distributions or Point Predictions? Survey Forecasts of US Output Growth and Inflation," Economic Research Papers 270748, University of Warwick - Department of Economics.
35. Hua, Zhongsheng & Zhang, Bin, 2008. "Improving density forecast by modeling asymmetric features: An application to S&P500 returns," European Journal of Operational Research, Elsevier, vol. 185(2), pages 716-725, March.
36. Matteo Luciani & Libero Monteforte, 2012. "Uncertainty and Heterogeneity in factor models forecasting," Working Papers 5, Department of the Treasury, Ministry of the Economy and of Finance.
    • Matteo Luciani & Libero Monteforte, 2013. "Uncertainty and heterogeneity in factor models forecasting," Temi di discussione (Economic working papers) 930, Bank of Italy, Economic Research and International Relations Area.
37. Götz, Thomas B. & Hecq, Alain & Urbain, Jean-Pierre, 2016. "Combining forecasts from successive data vintages: An application to U.S. growth," International Journal of Forecasting, Elsevier, vol. 32(1), pages 61-74.
38. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2011. "Multivariate semi-nonparametric distributions with dynamic conditional correlations," International Journal of Forecasting, Elsevier, vol. 27(2), pages 347-364.
    • Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2011. "Multivariate semi-nonparametric distributions with dynamic conditional correlations," International Journal of Forecasting, Elsevier, vol. 27(2), pages 347-364, April.
39. Polanski, Arnold & Stoja, Evarist, 2012. "Efficient evaluation of multidimensional time-varying density forecasts, with applications to risk management," International Journal of Forecasting, Elsevier, vol. 28(2), pages 343-352.
40. Wallis, Kenneth F., 2003. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 165-175.
    • Wallis, Kenneth F., 2001. "Chi-squared tests of interval and density forecasts and the Bank of England's fan charts," Working Paper Series 83, European Central Bank.
    • Wallis, Kenneth F., 2002. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," Royal Economic Society Annual Conference 2002 181, Royal Economic Society.
41. Brenda López Cabrera & Franziska Schulz, 2017. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 127-136, January.
    • Brenda Lopez Cabrera & Franziska Schulz, 2014. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," SFB 649 Discussion Papers SFB649DP2014-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
42. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Density characteristics and density forecast performance: a panel analysis," Empirical Economics, Springer, vol. 48(3), pages 1203-1231, May.
    • Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2014. "Density characteristics and density forecast performance: a panel analysis," Working Paper Series 1679, European Central Bank.
43. Wan, Shui Ki & Song, Haiyan & Ko, David, 2016. "Density forecasting for tourism demand," Annals of Tourism Research, Elsevier, vol. 60(C), pages 27-30.
44. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
45. repec:dau:papers:123456789/6805 is not listed on IDEAS
46. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 10973, Banco de la Republica.
47. Boero, Gianna & Marrocu, Emanuela, 2004. "The performance of SETAR models: a regime conditional evaluation of point, interval and density forecasts," International Journal of Forecasting, Elsevier, vol. 20(2), pages 305-320.
    • G. Boero & E. Marrocu, 2002. "The performance of Setar Models: a regime conditional evaluation of point, interval and density forecasts," Working Paper CRENoS 200208, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    • Boero, Gianna & Marrocu, Emanuela, 2003. "The Performance Of Setar Models : A Regime Conditional Evaluation Of Point, Interval And Density Forecasts," The Warwick Economics Research Paper Series (TWERPS) 663, University of Warwick, Department of Economics.
    • Boero, Gianna & Marrocu, Emanuela, 2003. "The Performance Of Setar Models: A Regime Conditional Evaluation Of Point, Interval And Density Forecasts," Economic Research Papers 269476, University of Warwick - Department of Economics.
48. Niango Ange Joseph Yapi, 2020. "Exchange rate predictive densities and currency risks: A quantile regression approach," EconomiX Working Papers 2020-16, University of Paris Nanterre, EconomiX.
49. Yongmiao Hong & Haitao Li & Feng Zhao, 2013. "Can the Random Walk Model be Beaten in Out-of-Sample Density Forecasts? Evidence from Intraday Forei," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
50. Gabriela De Raaij & Burkhard Raunig, 2005. "Evaluating density forecasts from models of stock market returns," The European Journal of Finance, Taylor & Francis Journals, vol. 11(2), pages 151-166.
51. Andreas Lindemann & Christian Dunis & Paulo Lisboa, 2005. "Probability distributions and leveraged trading strategies: an application of Gaussian mixture models to the Morgan Stanley Technology Index Tracking Fund," Quantitative Finance, Taylor & Francis Journals, vol. 5(5), pages 459-474.
52. Kevin Dowd, 2007. "Validating multiple-period density-forecasting models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 251-270.
53. Patrick Afflerbach & Christopher Dun & Henner Gimpel & Dominik Parak & Johannes Seyfried, 2021. "A Simulation-Based Approach to Understanding the Wisdom of Crowds Phenomenon in Aggregating Expert Judgment," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 329-348, August.
54. Pascual, Lorenzo & Ruiz Ortega, Esther & Fresoli, Diego Eduardo, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," DES - Working Papers. Statistics and Econometrics. WS ws113426, Universidad Carlos III de Madrid. Departamento de Estadística.
55. Conflitti, Cristina & De Mol, Christine & Giannone, Domenico, 2015. "Optimal combination of survey forecasts," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1096-1103.
    • Giannone, Domenico & De Mol, Christine & Conflitti, Cristina, 2012. "Optimal Combination of Survey Forecasts," CEPR Discussion Papers 9096, C.E.P.R. Discussion Papers.
    • Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
56. Izquierdo, Segismundo S. & Hernández, Cesáreo & del Hoyo, Juan, 2006. "Forecasting VARMA processes using VAR models and subspace-based state space models," MPRA Paper 4235, University Library of Munich, Germany.
57. David L. Reifschneider & Peter Tulip, 2007. "Gauging the uncertainty of the economic outlook from historical forecasting errors," Finance and Economics Discussion Series 2007-60, Board of Governors of the Federal Reserve System (U.S.).
58. Tosapol Apaitan & Pongsak Luangaram & Pym Manopimoke, 2020. "Uncertainty and Economic Activity: Does it Matter for Thailand?," PIER Discussion Papers 130, Puey Ungphakorn Institute for Economic Research.
59. Clarida, Richard H. & Sarno, Lucio & Taylor, Mark P. & Valente, Giorgio, 2003. "The out-of-sample success of term structure models as exchange rate predictors: a step beyond," Journal of International Economics, Elsevier, vol. 60(1), pages 61-83, May.
    • Richard Clarida & Lucio Sarno & Mark Taylor & Giorgio Valente, 2001. "The Out-of-Sample Success of Term Structure Models as Exchange Rate Predictors: A Step Beyond," NBER Working Papers 8601, National Bureau of Economic Research, Inc.
    • Taylor, Mark & Clarida, Richard & Sarno, Lucio & Valente, Giorgio, 2002. "The Out-of-Sample Success of Term Structure Models as Exchange Rate Predictors: A Step Beyond," CEPR Discussion Papers 3281, C.E.P.R. Discussion Papers.
60. Benedikt Rotermann & Bernd Wilfling, 2015. "Estimating rational stock-market bubbles with sequential Monte Carlo methods," CQE Working Papers 4015, Center for Quantitative Economics (CQE), University of Muenster.
61. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
62. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
63. Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2005. "Bootstrap prediction intervals for power-transformed time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 219-235.
    • Pascual, Lorenzo & Romo, Juan & Ruiz Ortega, Esther, 2001. "Bootstrap prediction intervals for power-transformed time series," DES - Working Papers. Statistics and Econometrics. WS ws010503, Universidad Carlos III de Madrid. Departamento de Estadística.
64. Gomes-Gonçalves, Erika & Gzyl, Henryk & Mayoral, Silvia, 2015. "Two maxentropic approaches to determine the probability density of compound risk losses," Insurance: Mathematics and Economics, Elsevier, vol. 62(C), pages 42-53.
    • Erika Gomes-Gonc{c}alves & Henryk Gzyl & Silvia Mayoral, 2014. "Two maxentropic approaches to determine the probability density of compound risk losses," Papers 1411.5625, arXiv.org, revised Nov 2014.
65. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
66. Perez-Quiros, Gabriel & Timmermann, Allan, 2001. "Business cycle asymmetries in stock returns: Evidence from higher order moments and conditional densities," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 259-306, July.
    • Allan Timmermann & Gabriel Perez-Quiros, 2000. "Business Cycle Asymmetries in Stock Returns: Evidence from Higher Order Moments and Conditional Densities," FMG Discussion Papers dp360, Financial Markets Group.
    • Pérez Quirós, Gabriel & Timmermann, Allan, 2001. "Business cycle asymmetries in stock returns: evidence from higher order moments and conditional densities," Working Paper Series 0058, European Central Bank.
    • Perez-Quiros, G. & Timmermann, A., 2001. "Business Cycle Asymmetries in Stock Returns: Evidence from Higher Order Moments and Conditional Densities," Papers 58, Quebec a Montreal - Recherche en gestion.
67. Michael K. Adjemian & Valentina G. Bruno & Michel A. Robe, 2020. "Incorporating Uncertainty into USDA Commodity Price Forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 696-712, March.
68. Raunig, Burkhard, 2006. "The longer-horizon predictability of German stock market volatility," International Journal of Forecasting, Elsevier, vol. 22(2), pages 363-372.
69. Brandt, Patrick T. & Freeman, John R. & Schrodt, Philip A., 2014. "Evaluating forecasts of political conflict dynamics," International Journal of Forecasting, Elsevier, vol. 30(4), pages 944-962.
70. Marco Vega, 2004. "Policy Makers Priors and Inflation Density Forecasts," Econometrics 0403005, University Library of Munich, Germany.
71. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
72. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
73. Dario Rukelj & Barbara Ulloa, 2011. "Incorporating uncertainties into economic forecasts: an application to forecasting economic activity in Croatia," Financial Theory and Practice, Institute of Public Finance, vol. 35(2), pages 140-170.
74. Hong, Yongmiao & Li, Haitao & Zhao, Feng, 2007. "Can the random walk model be beaten in out-of-sample density forecasts? Evidence from intraday foreign exchange rates," Journal of Econometrics, Elsevier, vol. 141(2), pages 736-776, December.
75. 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.
    • Sarno, Lucio & Valente, Giorgio, 2002. "Comparing the Accuracy of Density Forecasts from Competing Models," Computing in Economics and Finance 2002 223, Society for Computational Economics.
76. Vacca, Gianmarco & Zoia, Maria Grazia & Bagnato, Luca, 2022. "Forecasting in GARCH models with polynomially modified innovations," International Journal of Forecasting, Elsevier, vol. 38(1), pages 117-141.
77. Koop, Gary & Onorante, Luca, 2011. "Estimating Phillips Curves in Turbulent Times using the ECB’s Survey of Professional Forecasters," SIRE Discussion Papers 2011-19, Scottish Institute for Research in Economics (SIRE).
78. De Gooijer, Jan G. & Henter, Gustav Eje & Yuan, Ao, 2022. "Kernel-based hidden Markov conditional densities," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
79. Paulo M. Sánchez & Luis Fernando Melo, 2013. "Combinación de brechas del producto colombiano," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 31(72), pages 74-82, December.
    • Paulo M. Sánchez & Luis Fernando Melo, 2013. "Combinación de brechas del producto colombiano," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 31(72), pages 74-82, December.
    • Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 775, Banco de la Republica de Colombia.
80. Dong Jin Lee, 2009. "Testing Parameter Stability in Quantile Models: An Application to the U.S. Inflation Process," Working papers 2009-26, University of Connecticut, Department of Economics.
81. Hecq, A.W. & Götz, T.B. & Urbain, J.R.Y.J., 2012. "Real-time forecast density combinations (forecasting US GDP growth using mixed-frequency data)," Research Memorandum 021, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    • Götz, T.B. & Hecq, A.W. & Urbain, J.R.Y.J., 2014. "Combining distributions of real-time forecasts: An application to U.S. growth," Research Memorandum 027, Maastricht University, Graduate School of Business and Economics (GSBE).
82. Michael P. Clements & David F. Hendry, 2005. "Guest Editors’ Introduction: Information in Economic Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 713-753, December.
83. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
84. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2017. "Euromind‐ D : A Density Estimate of Monthly Gross Domestic Product for the Euro Area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 683-703, April.
    • Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CREATES Research Papers 2015-12, Department of Economics and Business Economics, Aarhus University.
    • Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CEIS Research Paper 340, Tor Vergata University, CEIS, revised 10 Apr 2015.
    • Proietti, Tommaso & Marczak, Martyna & Mazzi, Gianluigi, 2015. "EuroMInd-D: A density estimate of monthly gross domestic product for the euro area," Hohenheim Discussion Papers in Business, Economics and Social Sciences 03-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
85. repec:syb:wpbsba:01/2013 is not listed on IDEAS
86. Yeliz Ekinci & Nicoleta Serban & Ekrem Duman, 2021. "Optimal ATM replenishment policies under demand uncertainty," Operational Research, Springer, vol. 21(2), pages 999-1029, June.
87. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
88. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
89. Cortés, Lina M. & Mora-Valencia, Andrés & Perote, Javier, 2020. "Retrieving the implicit risk neutral density of WTI options with a semi-nonparametric approach," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
90. An-Sing Chen & Yan-Zhen Liu, 2008. "Enhancing hedging performance with the spanning polynomial projection," Quantitative Finance, Taylor & Francis Journals, vol. 8(6), pages 605-617.
91. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
92. Doaa Akl Ahmed & Mamdouh M. Abdelsalam, 2015. "Modelling the Density of Egyptian Quarterly CPI Inflation," Working Papers 936, Economic Research Forum, revised Aug 2015.
93. 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.
94. Athanasopoulos, George & Hyndman, Rob J. & Song, Haiyan & Wu, Doris C., 2011. "The tourism forecasting competition," International Journal of Forecasting, Elsevier, vol. 27(3), pages 822-844.
    • Athanasopoulos, George & Hyndman, Rob J. & Song, Haiyan & Wu, Doris C., 2011. "The tourism forecasting competition," International Journal of Forecasting, Elsevier, vol. 27(3), pages 822-844, July.
    • George Athanasopoulos & Rob J Hyndman & Haiyan Song & Doris C Wu, 2008. "The tourism forecasting competition," Monash Econometrics and Business Statistics Working Papers 10/08, Monash University, Department of Econometrics and Business Statistics, revised Oct 2009.
95. Mr. Prakash Kannan & Mr. Selim A Elekdag, 2009. "Incorporating Market Information into the Construction of the Fan Chart," IMF Working Papers 2009/178, International Monetary Fund.
96. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Inflation fan charts, monetary policy and skew normal distribution," Discussion Papers in Economics 13/06, Division of Economics, School of Business, University of Leicester.
    • Wojciech Charemza & Carlos Diaz & Svetlana Makarova, 2014. "Term Structure Of Inflation Forecast Uncertainties And Skew Normal Distributions," Discussion Papers in Economics 14/01, Division of Economics, School of Business, University of Leicester.
    • Wojciech Charemza & Carlos Díaz & Svetlana Makarova, 2015. "Ex-post Inflation Forecast Uncertainty and Skew Normal Distribution: ‘Back from the Future’ Approach," Discussion Papers in Economics 15/09, Division of Economics, School of Business, University of Leicester.
97. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2018. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 675-685, April.
    • Roberto Casarin & Federico Bassetti & Francesco Ravazzolo, 2015. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Working Papers 2015:04, Department of Economics, University of Venice "Ca' Foscari".
    • Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2015. "Bayesian nonparametric calibration and combination of predictive distributions," Working Paper 2015/03, Norges Bank.
98. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01442618, HAL.
    • Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Documents de travail du Centre d'Economie de la Sorbonne 17006, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
99. H. Kent Baker & Satish Kumar & Debidutta Pattnaik, 2021. "Research constituents, intellectual structure, and collaboration pattern in the Journal of Forecasting: A bibliometric analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 577-602, July.
100. Song, Haiyan & Wen, Long & Liu, Chang, 2019. "Density tourism demand forecasting revisited," Annals of Tourism Research, Elsevier, vol. 75(C), pages 379-392.
101. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
102. Shamiri, Ahmed & Shaari, Abu Hassan & Isa, Zaidi, 2007. "Practical Volatility Modeling for Financial Market Risk Management," MPRA Paper 9790, University Library of Munich, Germany, revised 15 May 2008.
103. Malte Knüppel, 2015. "Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 270-281, April.
     • Knüppel, Malte, 2011. "Evaluating the calibration of multi-step-ahead density forecasts using raw moments," Discussion Paper Series 1: Economic Studies 2011,32, Deutsche Bundesbank.
104. Andres Trujillo-Barrera & Philip Garcia & Mindy L Mallory, 2018. "Short-term price density forecasts in the lean hog futures market," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 121-142.
105. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
106. Nalban, Valeriu, 2018. "Forecasting with DSGE models: What frictions are important?," Economic Modelling, Elsevier, vol. 68(C), pages 190-204.
107. Mr. Ananthakrishnan Prasad & Mr. Selim A Elekdag & Mr. Phakawa Jeasakul & Romain Lafarguette & Mr. Adrian Alter & Alan Xiaochen Feng & Changchun Wang, 2019. "Growth at Risk: Concept and Application in IMF Country Surveillance," IMF Working Papers 2019/036, International Monetary Fund.
108. 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.
109. Lucio Sarno & Giorgio Valente, 2005. "Modelling and forecasting stock returns: exploiting the futures market, regime shifts and international spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 345-376, March.
     • Giorgio Valente & Lucio Sarno, 2005. "Modelling and forecasting stock returns: exploiting the futures market, regime shifts and international spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 345-376.
     • Sarno, Lucio & Giorgio Valente, 2002. "Modelling and Forecasting Stock Returns: Exploiting the Futures Market, Regime Shifts and International Spillovers," Royal Economic Society Annual Conference 2002 160, Royal Economic Society.
110. Christian Kascha & Francesco Ravazzolo, 2010. "Combining inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 231-250.
     • Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
111. Felix Wick & Ulrich Kerzel & Martin Hahn & Moritz Wolf & Trapti Singhal & Daniel Stemmer & Jakob Ernst & Michael Feindt, 2021. "Demand Forecasting of Individual Probability Density Functions with Machine Learning," SN Operations Research Forum, Springer, vol. 2(3), pages 1-39, September.
112. Hansen, Bruce E., 2006. "Interval forecasts and parameter uncertainty," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 377-398.
113. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
114. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
115. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
     • Gianni Amisano & Raffaella Giacomini, 2005. "Comparing Density Forecsts via Weighted Likelihood Ratio Tests," Working Papers ubs0504, University of Brescia, Department of Economics.
116. Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
117. Xiao-Ming Li & Qing Xu, 2007. "Evaluating density forecasts of the model with a conditional skewed-t distribution for China's stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 18(3), pages 213-227.
118. Jorge Fornero & Andrés Gatty, 2020. "Back testing fan charts of activity and inflation: the Chilean case," Working Papers Central Bank of Chile 881, Central Bank of Chile.
119. Richard H. Clarida & Lucio Sarno & Mark P. Taylor & Giorgio Valente, 2006. "The Role of Asymmetries and Regime Shifts in the Term Structure of Interest Rates," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1193-1224, May.
     • Taylor, Mark & Clarida, Richard & Sarno, Lucio & Valente, Giorgio, 2005. "The Role of Asymmetries and Regime Shifts in the Term Structure of Interest Rates," CEPR Discussion Papers 4835, C.E.P.R. Discussion Papers.
120. Sarno, Lucio & Valente, Giorgio, 2005. "Empirical exchange rate models and currency risk: some evidence from density forecasts," Journal of International Money and Finance, Elsevier, vol. 24(2), pages 363-385, March.
121. Agosto, Arianna & Cavaliere, Giuseppe & Kristensen, Dennis & Rahbek, Anders, 2016. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 640-663.
     • Arianna Agosto & Giuseppe Cavaliere & Dennis Kristensen & Anders Rahbek, 2015. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," CREATES Research Papers 2015-11, Department of Economics and Business Economics, Aarhus University.
122. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
123. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
     • Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Papers No 3/2014, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
     • Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
124. Lucio Sarno, 2005. "Viewpoint: Towards a solution to the puzzles in exchange rate economics: where do we stand?," Canadian Journal of Economics, Canadian Economics Association, vol. 38(3), pages 673-708, August.
     • Lucio Sarno, 2005. "Viewpoint: Towards a solution to the puzzles in exchange rate economics: where do we stand?," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 38(3), pages 673-708, August.
125. David Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors: The Federal Reserve's Approach," RBA Research Discussion Papers rdp2017-01, Reserve Bank of Australia.
     • David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.).
126. Bermejo Mancera, Miguel Ángel & Peña, Daniel & Sánchez, Ismael, 2011. "Densidad de predicción basada en momentos condicionados y máxima entropía : aplicación a la predicción de potencia eólica," DES - Working Papers. Statistics and Econometrics. WS ws111813, Universidad Carlos III de Madrid. Departamento de Estadística.
127. Li, Gang & Wu, Doris Chenguang & Zhou, Menglin & Liu, Anyu, 2019. "The combination of interval forecasts in tourism," Annals of Tourism Research, Elsevier, vol. 75(C), pages 363-378.
128. Maxime Phillot & Dr. Rina Rosenblatt-Wisch, 2018. "Inflation Expectations: The Effect of Question Ordering on Forecast Inconsistencies," Working Papers 2018-11, Swiss National Bank.
129. Mário Amorim Lopes & Álvaro Santos Almeida & Bernardo Almada-Lobo, 2018. "Forecasting the medical workforce: a stochastic agent-based simulation approach," Health Care Management Science, Springer, vol. 21(1), pages 52-75, March.
130. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
     • Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005.
131. Polanski, Arnold & Stoja, Evarist & Zhang, Ren, 2013. "Multidimensional risk and risk dependence," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3286-3294.
132. Shamiri, Ahmed & Shaari, Abu Hassan & Isa, Zaidi, 2008. "Comparing the accuracy of density forecasts from competing GARCH models," MPRA Paper 13662, University Library of Munich, Germany.
133. Patrick T. Brandt & John R. Freeman & Philip A. Schrodt, 2011. "Real Time, Time Series Forecasting of Inter- and Intra-State Political Conflict," Conflict Management and Peace Science, Peace Science Society (International), vol. 28(1), pages 41-64, February.
134. Matei Demetrescu, 2007. "Optimal forecast intervals under asymmetric loss," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 227-238.
135. Gary Koop & Luca Onorante, 2011. "Estimating Phillips Curves in Turbulent Times using the ECBs Survey of Professional Forecasters," Working Papers 1109, University of Strathclyde Business School, Department of Economics.
     • Onorante, Luca & Koop, Gary, 2012. "Estimating Phillips curves in turbulent times using the ECB's survey of professional forecasters," Working Paper Series 1422, European Central Bank.
136. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
     • Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
137. Charemza, Wojciech & Díaz, Carlos & Makarova, Svetlana, 2019. "Quasi ex-ante inflation forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 35(3), pages 994-1007.
138. Zhang, Mingzhu & He, Changzheng & Gu, Xin & Liatsis, Panos & Zhu, Bing, 2013. "D-GMDH: A novel inductive modelling approach in the forecasting of the industrial economy," Economic Modelling, Elsevier, vol. 30(C), pages 514-520.
139. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
140. Wallis, Kenneth F., 2003. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 165-175.
     • Wallis, Kenneth F., 2001. "Chi-squared tests of interval and density forecasts and the Bank of England's fan charts," Working Paper Series 0083, European Central Bank.
     • Wallis, Kenneth F., 2002. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," Royal Economic Society Annual Conference 2002 181, Royal Economic Society.
141. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
142. Andrew J. Patton, 2006. "Estimation of multivariate models for time series of possibly different lengths," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 147-173, March.
     • Andrew J. Patton, 2006. "Estimation of multivariate models for time series of possibly different lengths," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 147-173.
143. Dejian Yu & Libo Sheng & Shunshun Shi, 2023. "A retrospective analysis of Journal of Forecasting: From 1982 to 2019," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 1008-1035, July.
144. Li, Yushu & Andersson, Jonas, 2014. "A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting," Discussion Papers 2014/12, Norwegian School of Economics, Department of Business and Management Science.
145. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
146. Kreye, M.E. & Goh, Y.M. & Newnes, L.B. & Goodwin, P., 2012. "Approaches to displaying information to assist decisions under uncertainty," Omega, Elsevier, vol. 40(6), pages 682-692.
147. Burkhard Raunig, 2003. "Testing for Longer Horizon Predictability of Return Volatility with an Application to the German," Working Papers 86, Oesterreichische Nationalbank (Austrian Central Bank).
148. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2013. "Predictive likelihood comparisons with DSGE and DSGE-VAR models," Working Paper Series 1536, European Central Bank.
149. Huber, Jakob & Stuckenschmidt, Heiner, 2020. "Daily retail demand forecasting using machine learning with emphasis on calendric special days," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1420-1438.
150. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.
151. Dr. James Mitchell, 2008. "Evaluating Density Forecasts: Forecast Combinations, Model Mixtures, Calibration and Sharpness," National Institute of Economic and Social Research (NIESR) Discussion Papers 320, National Institute of Economic and Social Research.
152. Ravazzolo Francesco & Rothman Philip, 2016. "Oil-price density forecasts of US GDP," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 441-453, September.
     • Francesco Ravazzolo & Philip Rothman, 2015. "Oil-Price Density Forecasts of U.S. GDP," Working Papers No 10/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
153. Peñaranda, Francisco, 2003. "Evaluation of joint density forecasts of stock and bond returns: predictability and parameter uncertainty," LSE Research Online Documents on Economics 24857, London School of Economics and Political Science, LSE Library.
154. Gatt, William, 2014. "Communicating uncertainty - a fan chart for HICP projections," MPRA Paper 59603, University Library of Munich, Germany.
155. Arroyo, Javier & Maté, Carlos, 2009. "Forecasting histogram time series with k-nearest neighbours methods," International Journal of Forecasting, Elsevier, vol. 25(1), pages 192-207.
156. Valeriu Nalban, 2015. "Do Bayesian Vector Autoregressive models improve density forecasting accuracy? The case of the Czech Republic and Romania," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 4(1), pages 60-74, March.
157. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
158. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
159. 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.
160. Alves, P.R.L., 2020. "Dynamic characteristic of Bitcoin cryptocurrency in the reconstruction scheme," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).