IDEAS home Printed from https://ideas.repec.org/r/zbw/sfb373/199443.html
   My bibliography  Save this item

Nonlinear Interest Rate Dynamics and Implications for the Term Structure

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Dankenbring, Henning, 1998. "Volatility estimates of the short term interest rate with an application to German data," SFB 373 Discussion Papers 1998,96, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  2. Leippold, Markus & Wu, Liuren, 2002. "Asset Pricing under the Quadratic Class," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(2), pages 271-295, June.
  3. Wolfgang Lemke & Theofanis Archontakis, 2008. "Bond pricing when the short-term interest rate follows a threshold process," Quantitative Finance, Taylor & Francis Journals, vol. 8(8), pages 811-822.
  4. Laurent Ferrara & Dominique Guégan, 2006. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 353-371.
  5. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
  6. Xiaoyang Zhuo & Olivier Menoukeu-Pamen, 2017. "Efficient Piecewise Trees For The Generalized Skew Vasicek Model With Discontinuous Drift," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-34, June.
  7. Lubrano, Michel, 2004. "Modélisation bayésienne non linéaire du taux d’intérêt de court terme américain : l’aide des outils non paramétriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 465-499, Juin-Sept.
  8. Chung-Ming Kuan & Christos Michalopoulos & Zhijie Xiao, 2017. "Quantile Regression on Quantile Ranges – A Threshold Approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 99-119, January.
  9. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
  10. repec:ntu:ntugeo:vol2-iss1-14-042 is not listed on IDEAS
  11. Tkacz Greg, 2001. "Estimating the Fractional Order of Integration of Interest Rates Using a Wavelet OLS Estimator," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(1), pages 1-15, April.
  12. Benjamin M. Tabak, 2007. "Estimating the Fractional Order of Integration of Yields in the Brazilian Fixed Income Market," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 36(3), pages 231-246, November.
  13. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
  14. Dominique Guegan, 2011. "Contagion Between the Financial Sphere and the Real Economy. Parametric and non Parametric Tools: A Comparison," Post-Print halshs-00185373, HAL.
  15. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
  16. Høg, Espen P. & Frederiksen, Per H., 2006. "The Fractional Ornstein-Uhlenbeck Process: Term Structure Theory and Application," Finance Research Group Working Papers F-2006-01, University of Aarhus, Aarhus School of Business, Department of Business Studies.
  17. Goldman Elena & Nam Jouahn & Tsurumi Hiroki & Wang Jun, 2013. "Regimes and long memory in realized volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 521-549, December.
  18. Gil-Alana, Luis A., 2004. "Long memory in the U.S. interest rate," International Review of Financial Analysis, Elsevier, vol. 13(3), pages 265-276.
  19. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modeling Multivariate Interest Rates using Time-Varying Copulas and Reducible Stochastic Differential Equations," Working Papers halshs-00408014, HAL.
  20. 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.
  21. Christopher S. Jones, 2003. "Nonlinear Mean Reversion in the Short-Term Interest Rate," Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 793-843, July.
  22. 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.
  23. Terence D.Agbeyegbe & Elena Goldman, 2005. "Estimation of threshold time series models using efficient jump MCMC," Economics Working Paper Archive at Hunter College 406, Hunter College Department of Economics, revised 2005.
  24. John T. Barkoulas & Christopher F. Baum & Joseph Onochie, 1997. "A nonparametric investigation of the 90‐day t‐bill rate," Review of Financial Economics, John Wiley & Sons, vol. 6(2), pages 187-198.
  25. Yizhou Bai & Yongjin Wang & Haoyan Zhang & Xiaoyang Zhuo, 2022. "Bayesian Estimation of the Skew Ornstein-Uhlenbeck Process," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 479-527, August.
  26. Clements, Michael P. & Galvao, Ana Beatriz, 2004. "A comparison of tests of nonlinear cointegration with application to the predictability of US interest rates using the term structure," International Journal of Forecasting, Elsevier, vol. 20(2), pages 219-236.
  27. Singh, Tarlok, 2014. "On the regime-switching and asymmetric dynamics of economic growth in the OECD countries," Research in Economics, Elsevier, vol. 68(2), pages 169-192.
  28. Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
  29. Fabrizio Iacone, 2009. "A Semiparametric Analysis of the Term Structure of the US Interest Rates," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(4), pages 475-490, August.
  30. Shively, Philip A., 2005. "Threshold nonlinear interest rates," Economics Letters, Elsevier, vol. 88(3), pages 313-317, September.
  31. John Hatgioannides & Menelaos Karanasos & Marika Karanassou, 2004. "Modelling the Yield Curve: A Two Components Approach," Working Papers 519, Queen Mary University of London, School of Economics and Finance.
  32. Nesmith Travis D & Jones Barry E, 2008. "Linear Cointegration of Nonlinear Time Series with an Application to Interest Rate Dynamics," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-18, March.
  33. Hans Dewachter, 1996. "Modelling interest rate volatility: Regime switches and level links," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 132(2), pages 236-258, September.
  34. Zhu, Junjun & Xie, Shiyu, 2010. "Bayesian Analysis of a Triple-Threshold GARCH Model with Application in Chinese Stock Market," MPRA Paper 28235, University Library of Munich, Germany.
  35. Kenneth R. Szulczyk & Changyong Zhang, 2020. "Switching-regime regression for modeling and predicting a stock market return," Empirical Economics, Springer, vol. 59(5), pages 2385-2403, November.
  36. Luis Gil-Alana, 2003. "Strong dependence in the real interest rates," Applied Economics, Taylor & Francis Journals, vol. 35(2), pages 119-124.
  37. Al-Sulami, Dawlah & Jiang, Zhenyu & Lu, Zudi & Zhu, Jun, 2017. "Estimation for semiparametric nonlinear regression of irregularly located spatial time-series data," Econometrics and Statistics, Elsevier, vol. 2(C), pages 22-35.
  38. Gu, Rongbao & Chen, Xi & Li, Xinjie, 2014. "Chaos recognition and fractal analysis in the term structure of Shanghai Interbank Offered Rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 101-112.
  39. Adrian Cantemir Calin & Tiberiu Diaconescu & Oana – Cristina Popovici, 2014. "Nonlinear Models for Economic Forecasting Applications: An Evolutionary Discussion," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 2(1), pages 42-47, June.
  40. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
  41. Schotman, Peter C., 2001. "When units roots matter: excess volatility and excess smoothness of long-term interest rates," Journal of Empirical Finance, Elsevier, vol. 8(5), pages 669-694, December.
  42. 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.
  43. Teresa Corzo Santamaría & Javier Gómez Biscarri, 2005. "Nonparametric estimation of convergence of interest rates: Effects on bond pricing," Spanish Economic Review, Springer;Spanish Economic Association, vol. 7(3), pages 167-190, September.
  44. Muhammad Yasir & Sitara Afzal & Khalid Latif & Ghulam Mujtaba Chaudhary & Nazish Yameen Malik & Farhan Shahzad & Oh-young Song, 2020. "An Efficient Deep Learning Based Model to Predict Interest Rate Using Twitter Sentiment," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
  45. LUBRANO, Michel, 2000. "Bayesian non-linear modellings of the short term US interest rate: the help of non-parametric tools," LIDAM Discussion Papers CORE 2000038, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  46. Dominique Guegan, 2011. "Contagion Between the Financial Sphere and the Real Economy. Parametric and non Parametric Tools: A Comparison," PSE-Ecole d'économie de Paris (Postprint) halshs-00185373, HAL.
  47. Tauchen, George E., 1995. "New Minimum Chi-Square Methods in Empirical Finance," Working Papers 95-42, Duke University, Department of Economics.
  48. John Barkoulas & Christopher F. Baum & Joseph Onochie, 1996. "Nonlinear Nonparametric Prediction of the 90-Day T-Bill Rate," Boston College Working Papers in Economics 320., Boston College Department of Economics.
  49. Breitung, Jorg, 2001. "Rank Tests for Nonlinear Cointegration," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 331-340, July.
  50. Jin-Chuan Duan & Kris Jacobs, 2001. "Short and Long Memory in Equilibrium Interest Rate Dynamics," CIRANO Working Papers 2001s-22, CIRANO.
  51. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
  52. John Hatgioannides & Menelaos Karanasos & Marika Karanassou, 2004. "Modelling the Yield Curve: A Two Components Approach," Working Papers 519, Queen Mary University of London, School of Economics and Finance.
  53. Petros Dellaportas & David G. T. Denison & Chris Holmes, 2007. "Flexible Threshold Models for Modelling Interest Rate Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 419-437.
  54. Episcopos, Athanasios, 2000. "Further evidence on alternative continuous time models of the short-term interest rate," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 10(2), pages 199-212, June.
  55. Peter Martey Addo, 2014. "Multivariate Self-Exciting Threshold Autoregressive Models with eXogenous Input," Papers 1407.7738, arXiv.org.
  56. Duan, Jin-Chuan & Jacobs, Kris, 2008. "Is long memory necessary? An empirical investigation of nonnegative interest rate processes," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 567-581, June.
  57. Jack Strauss & Mark E. Wohar, 2007. "Domestic‐Foreign Interest Rate Differentials: Near Unit Roots and Symmetric Threshold Models," Southern Economic Journal, John Wiley & Sons, vol. 73(3), pages 814-829, January.
  58. Esben Hoeg & Per Frederiksen, 2006. "The Fractional OU Process: Term Structure Theory and Application," Computing in Economics and Finance 2006 194, Society for Computational Economics.
  59. Gil-Alana, Luis A., 2004. "Modelling the U.S. interest rate in terms of I(d) statistical models," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(4), pages 475-486, September.
  60. Clements, Michael P. & Galvão, Ana Beatriz C., 2003. "Testing The Expectations Theory Of The Term Structure Of Interest Rates In Threshold Models," Macroeconomic Dynamics, Cambridge University Press, vol. 7(4), pages 567-585, September.
  61. Ait-Sahalia, Yacine, 1996. "Testing Continuous-Time Models of the Spot Interest Rate," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 385-426.
  62. Ang, Andrew & Bekaert, Geert, 2002. "Short rate nonlinearities and regime switches," Journal of Economic Dynamics and Control, Elsevier, vol. 26(7-8), pages 1243-1274, July.
  63. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modelling Multivariate Interest Rates using Time-Varying Copulas and Reducible Non-Linear Stochastic Differential," Economics Working Papers 09-02, Queen's Management School, Queen's University Belfast.
  64. Sandy Suardi, 2010. "Nonstationarity, cointegration and structural breaks in the Australian term structure of interest rates," Applied Economics, Taylor & Francis Journals, vol. 42(22), pages 2865-2879.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.