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Effects of monetary policy on the long memory in interest rates: Evidence from an emerging market

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  • Sensoy, A.

Abstract

We study the presence of long memory in a variety of interest rates in Turkey by time-varying generalized Hurst exponent. We reveal that adopting inflation targeting cause a sudden and considerable decrease in the long memory in interest rates. The improvement lasts till the collapse of Lehman Brothers in 2008 which is followed with an increased persistence in interest rates. Moreover, degree of long memory increases with maturity which is in contrast to economic theory.

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  • Sensoy, A., 2013. "Effects of monetary policy on the long memory in interest rates: Evidence from an emerging market," Chaos, Solitons & Fractals, Elsevier, vol. 57(C), pages 85-88.
  • Handle: RePEc:eee:chsofr:v:57:y:2013:i:c:p:85-88
    DOI: 10.1016/j.chaos.2013.09.002
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    1. Cajueiro, Daniel O. & Tabak, Benjamin M., 2008. "Testing for long-range dependence in world stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 37(3), pages 918-927.
    2. Frezza, Massimiliano, 2012. "Modeling the time-changing dependence in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 45(12), pages 1510-1520.
    3. Tabak, Benjamin M. & Cajueiro, Daniel O., 2006. "Assessing inefficiency in euro bilateral exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 319-327.
    4. Barunik, Jozef & Kristoufek, Ladislav, 2010. "On Hurst exponent estimation under heavy-tailed distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(18), pages 3844-3855.
    5. Gradojevic, Nikola & Gencay, Ramazan, 2008. "Overnight interest rates and aggregate market expectations," Economics Letters, Elsevier, vol. 100(1), pages 27-30, July.
    6. Tsay, Wen-Jen, 2000. "Long memory story of the real interest rate," Economics Letters, Elsevier, vol. 67(3), pages 325-330, June.
    7. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Time-varying long-range dependence in US interest rates," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 360-367.
    8. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and multifractality in the term structure of LIBOR interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 603-614.
    9. Cajueiro, Daniel O. & Tabak, Benjamin M., 2009. "Multifractality and herding behavior in the Japanese stock market," Chaos, Solitons & Fractals, Elsevier, vol. 40(1), pages 497-504.
    10. Pilar Grau-Carles, 2005. "Tests of Long Memory: A Bootstrap Approach," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 103-113, February.
    11. Souza, Sergio R. & Tabak, Benjamin M. & Cajueiro, Daniel O., 2008. "Long memory testing for Fed Funds Futures’ contracts," Chaos, Solitons & Fractals, Elsevier, vol. 37(1), pages 180-186.
    12. Cajueiro, Daniel O. & Tabak, Benjamin M., 2009. "Testing for long-range dependence in the Brazilian term structure of interest rates," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1559-1573.
    13. Cajueiro, Daniel O. & Tabak, Benjamin M., 2010. "Fluctuation dynamics in US interest rates and the role of monetary policy," Finance Research Letters, Elsevier, vol. 7(3), pages 163-169, September.
    14. Tabak, Benjamin M. & Cajueiro, Daniel O., 2005. "The long-range dependence behavior of the term structure of interest rates in Japan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 418-426.
    15. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and market structure," Chaos, Solitons & Fractals, Elsevier, vol. 31(4), pages 995-1000.
    16. Peel, David A. & Ioannidis, Christos, 2003. "Empirical evidence on the relationship between the term structure of interest rates and future real output changes when there are changes in policy regimes," Economics Letters, Elsevier, vol. 78(2), pages 147-152, February.
    17. Jin, Hyun J. & Elder, John & Koo, Won W., 2006. "A reexamination of fractional integrating dynamics in foreign currency markets," International Review of Economics & Finance, Elsevier, vol. 15(1), pages 120-135.
    18. Batten, Jonathan A. & Ellis, Craig A. & Fethertson, Thomas A., 2008. "Sample period selection and long-term dependence: New evidence from the Dow Jones index," Chaos, Solitons & Fractals, Elsevier, vol. 36(5), pages 1126-1140.
    19. Cajueiro, Daniel O & Tabak, Benjamin M, 2004. "The Hurst exponent over time: testing the assertion that emerging markets are becoming more efficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(3), pages 521-537.
    20. Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
    21. Sensoy, A., 2013. "Time-varying long range dependence in market returns of FEAS members," Chaos, Solitons & Fractals, Elsevier, vol. 53(C), pages 39-45.
    22. Dimitris Politis & Halbert White, 2004. "Automatic Block-Length Selection for the Dependent Bootstrap," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 53-70.
    23. Morales, Raffaello & Di Matteo, T. & Gramatica, Ruggero & Aste, Tomaso, 2012. "Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3180-3189.
    24. Goddard, John & Onali, Enrico, 2012. "Short and long memory in stock returns data," Economics Letters, Elsevier, vol. 117(1), pages 253-255.
    25. Carbone, A. & Castelli, G. & Stanley, H.E., 2004. "Time-dependent Hurst exponent in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 267-271.
    26. Cajueiro, Daniel O. & Tabak, Benjamin M., 2004. "Evidence of long range dependence in Asian equity markets: the role of liquidity and market restrictions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(3), pages 656-664.
    27. Cajueiro, Daniel O. & Tabak, Benjamin M., 2005. "Possible causes of long-range dependence in the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 345(3), pages 635-645.
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    7. Tsionas, Mike G. & Michaelides, Panayotis G., 2017. "Bayesian analysis of chaos: The joint return-volatility dynamical system," MPRA Paper 80632, University Library of Munich, Germany.
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