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Dynamic efficiency of European credit sectors: A rolling-window multifractal detrended fluctuation analysis

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  • Aloui, Chaker
  • Shahzad, Syed Jawad Hussain
  • Jammazi, Rania

Abstract

In this paper, we explore the market efficiency hypothesis for 22 European credit market sectors using the multi fractal detrended fluctuation approach (MF-DFA). The market efficiency of the credit market sectors is compare in short- and long-run horizons and for small and large fluctuations. The time-variations in the market efficiency level are captured by adopting a rolling-window framework of MF-DFA. We find that all the Eurozone credit market sectors are multifractal in nature and that credit sectors are marked by a persistent long memory phenomenon in their short- and long-term components. Furthermore, market efficiency levels are time-varying for both short- and long-term horizons and significantly change under crisis and non-crisis scenarios. Our findings render the generally adopted full sample MF-DFA results less reliable.

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  • Aloui, Chaker & Shahzad, Syed Jawad Hussain & Jammazi, Rania, 2018. "Dynamic efficiency of European credit sectors: A rolling-window multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 337-349.
    • Handle: RePEc:eee:phsmap:v:506:y:2018:i:c:p:337-349
    DOI: 10.1016/j.physa.2018.04.039
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    as
    1. P. Oswiecimka & J. Kwapien & S. Drozdz & A. Z. Gorski & R. Rak, 2006. "Multifractal Model of Asset Returns versus real stock market dynamics," Papers physics/0605147, arXiv.org, revised Aug 2006.
    2. Zhao, Huan & He, Shaofang, 2016. "Analysis of speech signals’ characteristics based on MF-DFA with moving overlapping windows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 343-349.
    3. Grech, D & Mazur, Z, 2004. "Can one make any crash prediction in finance using the local Hurst exponent idea?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 133-145.
    4. Rizvi, Syed Aun R. & Arshad, Shaista, 2017. "Analysis of the efficiency–integration nexus of Japanese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 296-308.
    5. Mensi, Walid & Tiwari, Aviral Kumar & Yoon, Seong-Min, 2017. "Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 135-146.
    6. Benoit Mandelbrot & Howard M. Taylor, 1967. "On the Distribution of Stock Price Differences," Operations Research, INFORMS, vol. 15(6), pages 1057-1062, December.
    7. Di Matteo, T. & Aste, T. & Dacorogna, M.M., 2003. "Scaling behaviors in differently developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 183-188.
    8. Alexeev, Vitali & Tapon, Francis, 2011. "Testing weak form efficiency on the Toronto Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 661-691, September.
    9. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    10. Sensoy, A., 2013. "Generalized Hurst exponent approach to efficiency in MENA markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5019-5026.
    11. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    12. Metghalchi, Massoud & Chen, Chien-Ping & Hayes, Linda A., 2015. "History of share prices and market efficiency of the Madrid general stock index," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 178-184.
    13. Kim, Suk-Joong & Salem, Leith & Wu, Eliza, 2015. "The role of macroeconomic news in sovereign CDS markets: Domestic and spillover news effects from the U.S., the Eurozone and China," Journal of Financial Stability, Elsevier, vol. 18(C), pages 208-224.
    14. Oświe¸cimka, P. & Kwapień, J. & Drożdż, S., 2005. "Multifractality in the stock market: price increments versus waiting times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 347(C), pages 626-638.
    15. Cajueiro, Daniel O. & Tabak, Benjamin M., 2005. "Testing for time-varying long-range dependence in volatility for emerging markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 577-588.
    16. Shahzad, Syed Jawad Hussain & Nor, Safwan Mohd & Mensi, Walid & Kumar, Ronald Ravinesh, 2017. "Examining the efficiency and interdependence of US credit and stock markets through MF-DFA and MF-DXA approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 351-363.
    17. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    18. Mubariz Hasanov & Tolga Omay, 2007. "Are the Transition Stock Markets Efficient? Evidence from Non-Linear Unit Root Tests," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 7(2), pages 1-12.
    19. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    20. P. Gopikrishnan & M. Meyer & L.A.N. Amaral & H.E. Stanley, 1998. "Inverse cubic law for the distribution of stock price variations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 3(2), pages 139-140, July.
    21. Rizvi, Syed Aun R. & Dewandaru, Ginanjar & Bacha, Obiyathulla I. & Masih, Mansur, 2014. "An analysis of stock market efficiency: Developed vs Islamic stock markets using MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 86-99.
    22. He, Shanshan & Wang, Yudong, 2017. "Revisiting the multifractality in stock returns and its modeling implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 11-20.
    23. Yang, Liansheng & Zhu, Yingming & Wang, Yudong, 2016. "Multifractal characterization of energy stocks in China: A multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 357-365.
    24. Norden, Lars, 2017. "Information in CDS spreads," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 118-135.
    25. 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.
    26. Wang, Qizhen & Zhu, Yingming & Yang, Liansheng & Mul, Remco A.H., 2017. "Coupling detrended fluctuation analysis of Asian stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 337-350.
    27. Wengner, Andreas & Burghof, Hans-Peter & Schneider, Johannes, 2015. "The impact of credit rating announcements on corporate CDS markets—Are intra-industry effects observable?," Journal of Economics and Business, Elsevier, vol. 78(C), pages 79-91.
    28. Kwapień, J. & Oświe¸cimka, P. & Drożdż, S., 2005. "Components of multifractality in high-frequency stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 466-474.
    29. Stanislaw Drozdz & Jaroslaw Kwapien & Pawel Oswiecimka & Rafal Rak, 2009. "Quantitative features of multifractal subtleties in time series," Papers 0907.2866, arXiv.org, revised Feb 2010.
    30. Lars Norden & Martin Weber, 2009. "The Co†movement of Credit Default Swap, Bond and Stock Markets: an Empirical Analysis," European Financial Management, European Financial Management Association, vol. 15(3), pages 529-562, June.
    31. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    32. Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu & Yoon, Seong-Min, 2017. "A multifractal detrended fluctuation analysis of financial market efficiency: Comparison using Dow Jones sector ETF indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 182-192.
    33. Pasquini, Michele & Serva, Maurizio, 1999. "Multiscale behaviour of volatility autocorrelations in a financial market," Economics Letters, Elsevier, vol. 65(3), pages 275-279, December.
    34. Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997. "A Multifractal Model of Asset Returns," Cowles Foundation Discussion Papers 1164, Cowles Foundation for Research in Economics, Yale University.
    35. Zhang, Gaiyan & Zhang, Sanjian, 2013. "Information efficiency of the U.S. credit default swap market: Evidence from earnings surprises," Journal of Financial Stability, Elsevier, vol. 9(4), pages 720-730.
    36. Parameswaran Gopikrishnan & Martin Meyer & Luis A Nunes Amaral & H Eugene Stanley, 1998. "Inverse Cubic Law for the Probability Distribution of Stock Price Variations," Papers cond-mat/9803374, arXiv.org, revised May 1998.
    37. Adlai Fisher & Laurent Calvet & Benoit Mandelbrot, 1997. "Multifractality of Deutschemark/US Dollar Exchange Rates," Cowles Foundation Discussion Papers 1166, Cowles Foundation for Research in Economics, Yale University.
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