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Yield curve and Recession Forecasting in a Machine Learning Framework

Citations

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Cited by:

  1. Cyrille Lenoel & Garry Young, 2020. "Real-time turning point indicators: Review of current international practices," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-05, Economic Statistics Centre of Excellence (ESCoE).
  2. Oleksandr Castello & Marina Resta, 2025. "Optimal Time Varying Parameters in Yield Curve Modeling and Forecasting: A Simulation Study on BRICS Countries," Computational Economics, Springer;Society for Computational Economics, vol. 65(4), pages 2081-2113, April.
  3. Yasmeen Idilbi-Bayaa & Mahmoud Qadan, 2021. "Forecasting Commodity Prices Using the Term Structure," JRFM, MDPI, vol. 14(12), pages 1-39, December.
  4. Lulin Xu & Zhongwu Li, 2021. "A New Appraisal Model of Second-Hand Housing Prices in China’s First-Tier Cities Based on Machine Learning Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 617-637, February.
  5. Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
  6. N. Loukeris & I. Eleftheriadis & E. Livanis, 2016. "The Portfolio Heuristic Optimisation System (PHOS)," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 627-648, December.
  7. Cepni, Oguzhan & Gupta, Rangan & Karahan, Cenk C. & Lucey, Brian, 2026. "Retraction notice to “Oil price shocks and yield curve dynamics in emerging markets” [International Review of Economics and Finance 80 (2022) 613–623]," International Review of Economics & Finance, Elsevier, vol. 105(C).
  8. Jaehyuk Choi & Desheng Ge & Kyu Ho Kang & Sungbin Sohn, 2021. "Yield Spread Selection in Predicting Recession Probabilities: A Machine Learning Approach," Papers 2101.09394, arXiv.org, revised Jan 2022.
  9. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
  10. Vrontos, Spyridon D. & Galakis, John & Vrontos, Ioannis D., 2021. "Modeling and predicting U.S. recessions using machine learning techniques," International Journal of Forecasting, Elsevier, vol. 37(2), pages 647-671.
  11. Cheng-Feng Wu & Shian-Chang Huang & Chei-Chang Chiou & Tsangyao Chang & Yung-Chih Chen, 2022. "The Relationship Between Economic Growth and Electricity Consumption: Bootstrap ARDL Test with a Fourier Function and Machine Learning Approach," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1197-1220, December.
  12. Maas, Benedikt, 2019. "Nowcasting and forecasting US recessions: Evidence from the Super Learner," MPRA Paper 96408, University Library of Munich, Germany.
  13. Knut Lehre Seip & Dan Zhang, 2021. "The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model," Forecasting, MDPI, vol. 3(2), pages 1-16, May.
  14. Ranik Raaen Wahlstrøm & Florentina Paraschiv & Michael Schürle, 2022. "A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 967-1004, March.
  15. Söhnke M. Bartram & Jürgen Branke & Mehrshad Motahari, 2020. "Artificial intelligence in asset management," Working Papers 20202001, Cambridge Judge Business School, University of Cambridge.
  16. Christos Alexakis & Michael Dowling & Konstantinos Eleftheriou & Michael Polemis, 2021. "Textual Machine Learning: An Application to Computational Economics Research," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 369-385, January.
  17. Bouri, Elie & Demirer, Riza & Gupta, Rangan & Wohar, Mark E., 2021. "Gold, platinum and the predictability of bond risk premia," Finance Research Letters, Elsevier, vol. 38(C).
  18. Theodore Syriopoulos & Michael Tsatsaronis & Ioannis Karamanos, 2021. "Support Vector Machine Algorithms: An Application to Ship Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 55-87, January.
  19. Emmanouil Sofianos & Thierry Betti & Theophilos Papadimitriou & Amélie Barbier‐Gauchard & Periklis Gogas, 2026. "Using DSGE and Machine Learning to Forecast Public Debt for France," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(5), pages 2173-2185, August.
  20. Emmanouil Sofianos & Christos Alexakis & Periklis Gogas & Theophilos Papadimitriou, 2025. "Machine learning forecasting in the macroeconomic environment: the case of the US output gap," Economic Change and Restructuring, Springer, vol. 58(1), pages 1-19, February.
  21. Plakandaras, Vasilios & Gupta, Rangan & Gogas, Periklis & Papadimitriou, Theophilos, 2015. "Forecasting the U.S. real house price index," Economic Modelling, Elsevier, vol. 45(C), pages 259-267.
  22. David Mayer-Foulkes, 2018. "Efficient Urbanization for Mexican Development," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(10), pages 1-1, October.
  23. Kian Tehranian, 2023. "Can Machine Learning Catch Economic Recessions Using Economic and Market Sentiments?," Papers 2308.16200, arXiv.org.
  24. Andreas Psimopoulos, 2020. "Forecasting Economic Recessions Using Machine Learning:An Empirical Study in Six Countries," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 18(1), pages 40-99.
  25. Mirza, Nawazish & Rizvi, Syed Kumail Abbas & Naqvi, Bushra & Umar, Muhammad, 2024. "Inflation prediction in emerging economies: Machine learning and FX reserves integration for enhanced forecasting," International Review of Financial Analysis, Elsevier, vol. 94(C).
  26. Jaehyuk Choi & Desheng Ge & Kyu Ho Kang & Sungbin Sohn, 2023. "Yield spread selection in predicting recession probabilities," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1772-1785, November.
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