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Citations for "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks"

by Swanson, Norman R & White, Halbert

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  1. Dilip M. Nachane & Jose G. Clavel, 2005. "Forecasting interest rates: A Comparative assessment of some second generation non-linear model," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2005-009, Indira Gandhi Institute of Development Research, Mumbai, India.
  2. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.
  3. Ramazan Gencay & Aslihan Salih, 2003. "Degree of Mispricing with the Black-Scholes Model and Nonparametric Cures," Annals of Economics and Finance, Society for AEF, vol. 4(1), pages 73-101, May.
  4. Andrew Patton, 2002. "(IAM Series No 001) On the Out-Of-Sample Importance of Skewness and Asymetric Dependence for Asset Allocation," FMG Discussion Papers dp431, Financial Markets Group.
  5. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen Miller, 2013. "Forecasting Nevada gross gaming revenue and taxable sales using coincident and leading employment indexes," Empirical Economics, Springer, vol. 44(2), pages 387-417, April.
  6. Martha Misas A. & Enrique López E. & Carlos A. Arango A. & Juan Nicolás Hernández A., 2003. "La Demanda de Efectivo en Colombia: Una Caja Nagra a la Luz de las Redes Neuronales," BORRADORES DE ECONOMIA 002963, BANCO DE LA REPÚBLICA.
  7. Peter Exterkate & Patrick J.F. Groenen & Christiaan Heij & Dick van Dijk, 2013. "Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression," CREATES Research Papers 2013-16, Department of Economics and Business Economics, Aarhus University.
  8. Eric Ghysels & Norman R. Swanson & Myles Callan, 2002. "Monetary Policy Rules with Model and Data Uncertainty," Southern Economic Journal, Southern Economic Association, vol. 69(2), pages 239-265, October.
  9. Yvon Fauvel & Alain Paquet & Christian Zimmermann, 1999. "A Survey on Interest Rate Forecasting," Cahiers de recherche CREFE / CREFE Working Papers 87, CREFE, Université du Québec à Montréal.
  10. Kiani, Khurshid M., 2016. "On business cycle fluctuations in USA macroeconomic time series," Economic Modelling, Elsevier, vol. 53(C), pages 179-186.
  11. Hartmann, Matthias & Herwartz, Helmut & Ulm, Maren, 2017. "A comparative assessment of alternative ex ante measures of inflation uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 76-89.
  12. Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009," CREATES Research Papers 2011-28, Department of Economics and Business Economics, Aarhus University.
  13. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
  14. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics.
  15. Qi, Min & Zhang, Guoqiang Peter, 2001. "An investigation of model selection criteria for neural network time series forecasting," European Journal of Operational Research, Elsevier, vol. 132(3), pages 666-680, August.
  16. Khurshid M. KIANI & Terry L. KASTENS, 2006. "Using Macro-Financial Variables To Forecast Recessions. An Analysis Of Canada, 1957-2002," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 6(3).
  17. Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
  18. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, December.
  19. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, Department of Economics and Business Economics, Aarhus University.
  20. Kanas, Angelos & Yannopoulos, Andreas, 2001. "Comparing linear and nonlinear forecasts for stock returns," International Review of Economics & Finance, Elsevier, vol. 10(4), pages 383-398, December.
  21. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
  22. Anderson, Richard G. & Binner, Jane M. & Schmidt, Vincent A., 2012. "Connectionist-based rules describing the pass-through of individual goods prices into trend inflation in the United States," Economics Letters, Elsevier, vol. 117(1), pages 174-177.
  23. Krishna, Kala & Ozyildirim, Ataman & Swanson, Norman R., 2003. "Trade, investment and growth: nexus, analysis and prognosis," Journal of Development Economics, Elsevier, vol. 70(2), pages 479-499, April.
  24. Khurshid Kiani, 2011. "Fluctuations in Economic and Activity and Stabilization Policies in the CIS," Computational Economics, Springer;Society for Computational Economics, vol. 37(2), pages 193-220, February.
  25. Norman R. Swanson & Halbert White, 1995. "A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Macroeconomics 9503004, EconWPA.
  26. Kock Anders Bredahl, 2011. "Forecasting with Universal Approximators and a Learning Algorithm," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
  27. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, Elsevier.
  28. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
  29. Martha Misas & Enrique López & Pablo Querubín, "undated". "La Inflación en Colombia: Una Aproximación desde las Redes Neuronales," Borradores de Economia 199, Banco de la Republica de Colombia.
  30. Qi, Min, 2001. "Predicting US recessions with leading indicators via neural network models," International Journal of Forecasting, Elsevier, vol. 17(3), pages 383-401.
  31. Khurshid Kiani & Terry Kastens, 2008. "Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 383-406, November.
  32. M Sensier & M Artis & C R Birchenhall & D R Osborn, 2002. "Domestic and International Influences on Business Cycle Regimes in Europe," The School of Economics Discussion Paper Series 0202, Economics, The University of Manchester.
  33. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
  34. Kiani, K.M., 2009. "Neural Networks to Detect Nonlinearities in Time Series: Analysis of Business Cycle in France and the United Kingdom," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(1).
  35. René Garcia & Ramazan Gençay, 1998. "Pricing and Hedging Derivative Securities with Neural Networks and a Homogeneity Hint," CIRANO Working Papers 98s-35, CIRANO.
  36. Oliver Blaskowitz & Helmut Herwartz, 2009. "Adaptive forecasting of the EURIBOR swap term structure," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 575-594.
  37. Kajal Lahiri & Liu Yang, 2012. "Forecasting Binary Outcomes," Discussion Papers 12-09, University at Albany, SUNY, Department of Economics.
  38. Vroomen, B.L.K. & Franses, Ph.H.B.F. & van Nierop, J.E.M., 2001. "Modeling Consideration Sets and Brand Choice Using Artificial Neural Networks," ERIM Report Series Research in Management ERS-2001-10-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  39. Corina SAMAN, 2015. "Out-Of-Sample Forecasting Performance Of A Robust Neural Exchange Rate Model Of Ron/Usd," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 93-106, March.
  40. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
  41. Huck, Nicolas, 2010. "Pairs trading and outranking: The multi-step-ahead forecasting case," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1702-1716, December.
  42. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, Elsevier.
  43. Medeiros, Marcelo C. & Teräsvirta, Timo & Rech, Gianluigi, 2002. "Building neural network models for time series: A statistical approach," SSE/EFI Working Paper Series in Economics and Finance 508, Stockholm School of Economics.
  44. Aiolfi, Marco & Timmermann, Allan, 2006. "Persistence in forecasting performance and conditional combination strategies," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 31-53.
  45. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 245-264, October.
  46. Georgios Kouretas & Eleni Constantinou & Robert Georgiades & Avo Kazandjian, 2005. "Regime Switching and Artificial Neural Network Forecasting of the Cyprus Stock Exchange Daily Returns," Money Macro and Finance (MMF) Research Group Conference 2005 46, Money Macro and Finance Research Group.
  47. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
  48. Martha A. Misas A. & Enrique López E. & Carlos A. Arango A. & Juan Nicolás Hernández A., 2004. "No-linealidades en la demanda de efectivo en Colombia: las redes neuronales como herramienta de pronóstico," Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 22(45), pages 10-57, Junio.
  49. Huck, Nicolas, 2009. "Pairs selection and outranking: An application to the S&P 100 index," European Journal of Operational Research, Elsevier, vol. 196(2), pages 819-825, July.
  50. Sami Chaabouni, 2016. "Modeling and forecasting 3E in Eastern Asia: a comparison of linear and nonlinear models," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(5), pages 1993-2008, September.
  51. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.
  52. Clive Bowsher & Roland Meeks, 2006. "High Dimensional Yield Curves: Models and Forecasting," Economics Papers 2006-W12, Economics Group, Nuffield College, University of Oxford.
  53. Angelos Kanas, 2003. "Non-linear forecasts of stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 299-315.
  54. Arifovic, Jasmina & Gençay, Ramazan, 2001. "Using genetic algorithms to select architecture of a feedforward artificial neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(3), pages 574-594.
  55. Lance J. Bachmeier & Norman R. Swanson, 2005. "Predicting Inflation: Does The Quantity Theory Help?," Economic Inquiry, Western Economic Association International, vol. 43(3), pages 570-585, July.
  56. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
  57. Oliver Blaskowitz & Helmut Herwartz, 2008. "Testing directional forecast value in the presence of serial correlation," SFB 649 Discussion Papers SFB649DP2008-073, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  58. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Regime Switching and Artificial Neural Network Forecasting," Working Papers 0502, University of Crete, Department of Economics.
  59. Granger, Clive W. J. & Swanson, Norman R., 1997. "An introduction to stochastic unit-root processes," Journal of Econometrics, Elsevier, vol. 80(1), pages 35-62, September.
  60. Corradi, Valentina & Swanson, Norman R., 2002. "A consistent test for nonlinear out of sample predictive accuracy," Journal of Econometrics, Elsevier, vol. 110(2), pages 353-381, October.
  61. Bildirici, Melike & Alp, Aykaç, 2008. "The Relationship Between Wages and Productivity: TAR Unit Root and TAR Cointegration Approach," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 5(1), pages 93-110.
  62. McAleer, Michael & Medeiros, Marcelo C. & Slottje, Daniel, 2008. "A neural network demand system with heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 147(2), pages 359-371, December.
  63. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
  64. Mayte Suarez -Farinas & Carlos E. Pedreira & Marcelo C. Medeiros, 2004. "Local Global Neural Networks: A New Approach for Nonlinear Time Series Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1092-1107, December.
  65. Alfaro, Rodrigo & Becerra, Juan Sebastian & Sagner, Andres, 2010. "Estimación de la estructura de tasas utilizando el modelo Dinámico Nelson Siegel: resultados para Chile y EEUU
    [The Dynamic Nelson-Siegel model: empirical results for Chile and US]
    ," MPRA Paper 25912, University Library of Munich, Germany, revised 23 Jun 2010.
  66. Francis X. Diebold & Canlin Li, 2003. "Forecasting the Term Structure of Government Bond Yields," NBER Working Papers 10048, National Bureau of Economic Research, Inc.
  67. Ferland, Rene & Lalancette, Simon, 2006. "Dynamics of realized volatilities and correlations: An empirical study," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2109-2130, July.
  68. Corradi, Valentina & Swanson, Norman R. & Olivetti, Claudia, 2001. "Predictive ability with cointegrated variables," Journal of Econometrics, Elsevier, vol. 104(2), pages 315-358, September.
  69. Yang, Jian & Cabrera, Juan & Wang, Tao, 2010. "Nonlinearity, data-snooping, and stock index ETF return predictability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 498-507, January.
  70. Norman Swanson & Oleg Korenok, 2006. "How Sticky Is Sticky Enough? A Distributional and Impulse Response Analysis of New Keynesian DSGE Models. Extended Working Paper Version," Departmental Working Papers 200612, Rutgers University, Department of Economics.
  71. Qi, Min & Yang, Sha, 2003. "Forecasting consumer credit card adoption: what can we learn about the utility function?," International Journal of Forecasting, Elsevier, vol. 19(1), pages 71-85.
  72. Bekdache, Basma, 2001. "Term Premia and the Maturity Composition of the Federal Debt: New Evidence from the Term Structure of Interest Rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(7), pages 519-539, November.
  73. Eisinga, R. & Franses, Ph.H.B.F. & van Dijk, D.J.C., 1997. "Timing of Vote Decision in First and Second Order Dutch Elections 1978-1995: Evidence from Artificial Neural Networks," Econometric Institute Research Papers EI 9733/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  74. repec:bdr:ensayo:v::y:2004:i:45:p:10-57 is not listed on IDEAS
  75. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408 Edward Elgar Publishing.
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