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Regime switching in the dynamic relationship between stock returns and inflation

Author

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  • Dandan Liu
  • Dennis Jansen
  • Qi Li

Abstract

This study examines nonlinear dynamic relationships between stock returns and inflation in ten major stock markets. Using Hansen and Seo's (2002) threshold error correction model to allow for possible regime shifts in the dynamic relationship between the two variables, threshold effects are found in the adjustment towards the long-run equilibrium relationship between stock returns and inflation for three out of the ten countries considered in this study (France, Switzerland and the USA). Nevertheless, the nonlinear adjustment mechanism is not uniform but rather it is country-specific.

Suggested Citation

  • Dandan Liu & Dennis Jansen & Qi Li, 2005. "Regime switching in the dynamic relationship between stock returns and inflation," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 1(5), pages 273-277, September.
  • Handle: RePEc:taf:apfelt:v:1:y:2005:i:5:p:273-277
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    References listed on IDEAS

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    1. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
    2. Barnes, Michelle L., 1999. "Inflation and returns revisited: a TAR approach," Journal of Multinational Financial Management, Elsevier, vol. 9(3-4), pages 233-245, November.
    3. John H. Boyd & Ross Levine & Bruce D. Smith, 1996. "Inflation and financial market performance," Working Paper 9617, Federal Reserve Bank of Cleveland.
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    Cited by:

    1. Andrew Phiri, 2017. "Long-run equilibrium adjustment between inflation and stock market returns in South Africa: a nonlinear perspective," International Journal of Sustainable Economy, Inderscience Enterprises Ltd, vol. 9(1), pages 19-33.
    2. repec:taf:applec:v:49:y:2017:i:18:p:1794-1807 is not listed on IDEAS
    3. Mensah, Jones Odei & Premaratne, Gamini, 2014. "Dependence patterns among Banking Sectors in Asia: A Copula Approach," MPRA Paper 60119, University Library of Munich, Germany.
    4. Faisal Khan & Saif-Ur-Rehman Khan & Hashim Khan, 2016. "Pricing of Risk, Various Volatility Dynamics and Macroeconomic Exposure of Firm Returns: New Evidence on Age Effect," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 551-561.
    5. Claudiu Albulescu & Christian Aubin & Daniel Goyeau, 2016. "Stock prices, inflation and inflation uncertainty in the U.S.: Testing the long-run relationship considering Dow Jones sector indexes," Papers 1603.01231, arXiv.org.
    6. Hayashida, Minoru & Ono, Hiroyuki, 2016. "Tax reforms and stock return volatility: The case of Japan," Journal of Asian Economics, Elsevier, vol. 45(C), pages 1-14.
    7. Karagianni Stella & Kyrtsou Catherine, 2011. "Analysing the Dynamics between U.S. Inflation and Dow Jones Index Using Non-Linear Methods," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-25, March.
    8. Claudiu Tiberiu Albulescu & Christian Aubin & Daniel Goyeau, 2017. "Stock prices, inflation and inflation uncertainty in the U.S.: testing the long-run relationship considering Dow Jones sector indexes," Applied Economics, Taylor & Francis Journals, vol. 49(18), pages 1794-1807, April.
    9. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].

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