Journal of Economics and Finance

, Volume 40, Issue 2, pp 235–257 | Cite as

Long memory in the Ukrainian stock market and financial crises

  • Guglielmo Maria Caporale
  • Luis Gil-Alana
  • Alex Plastun
  • Inna Makarenko
Article
First Online:

Abstract

This paper examines persistence in the Ukrainian stock market during the recent financial crisis. Using two different long memory approaches (R/S analysis and fractional integration) we show that this market is inefficient and the degree of persistence is not the same at different stages of the financial crisis. Therefore trading strategies might have to be modified. We also show that data smoothing is not advisable in the context of R/S analysis.

Keywords

Persistence Long Memory R/S Analysis Fractional Integration 

JEL Classification

C22 G12 
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References

  1. Abadir KM, Distaso W, Giraitis L (2007) Nonstationarity-extended local Whittle estimation. J Econ 141:1353–1384CrossRefGoogle Scholar
  2. Alvo M, Firuzan E, Firuzan AR (2011) Predictability of Dow Jones Index via Chaotic Symbolic Dynamics. World Applied Sciences Journal 12(6):835–839Google Scholar
  3. Anoruo E, Gil-Alana LA (2011) Mean reversion and long memory in African stock market prices. J Econ Financ 35(3):296–308CrossRefGoogle Scholar
  4. Batten J, Ellis C, Fetherston T (2005) Return Anomalies on the Nikkei: Are They Statistical Illusions? Chaos Solitons Fractals 23(4):1125–1136CrossRefGoogle Scholar
  5. Berg L, Lyhagen J (1998) Short and Long Run Dependence in Swedish Stock Returns. Appl Financ Econ 8(4):435–443CrossRefGoogle Scholar
  6. Booth GG, Kaen FR, Koveos PE (1982) R/S analysis of foreign exchange rates under two international monetary regimes. J Monet Econ 10(3):407–415CrossRefGoogle Scholar
  7. Cajueiro D, Tabak B (2005) Ranking efficiency for emerging equity markets II. Chaos Solitons Fractals 23:671–675CrossRefGoogle Scholar
  8. Cheung YW, Lai KS (1993) Do gold market returns have long-range dependence? The Financial Review 28(2):181–202CrossRefGoogle Scholar
  9. Corazza M, Malliaris AG (2002) Multifractality in Foreign Currency Markets. Multinational Finance Journal 6:387–401CrossRefGoogle Scholar
  10. Crato N, Ray B (2000) Memory in Returns and Volatilities of Commodity Futures’ Contracts. J Futur Mark 20(6):525–543CrossRefGoogle Scholar
  11. Crato N (1994) Some international evidence regarding the stochastic memory of stock returns. Appl Financ Econ 4(1):33–39CrossRefGoogle Scholar
  12. Dahlhaus R (1989) Efficient parameter estimation for self-similar process. Ann Stat 17:1749–1766CrossRefGoogle Scholar
  13. Fox R, Taqqu M (1986) Large sample properties of parameter estimates for strongly dependent stationary Gaussian time series. Ann Stat 14:517–532CrossRefGoogle Scholar
  14. Fung HG, Lo WC (1993) Memory in interest rate futures. J Futur Mark 13:865–872CrossRefGoogle Scholar
  15. Geweke J, Porter-Hudak S (1983) The estimation and application of long memory time series models. J Time Ser Anal 4:2221–2238CrossRefGoogle Scholar
  16. Gil-Alana, L.A. and O. Yaya (2014), The persistence and asymmetric volatility in the Nigerian stock bull and bear markets, Economic Modelling, forthcoming.Google Scholar
  17. Glenn, L. A., 2007, On Randomness and the NASDAQ Composite, Working Paper, Available at SSRN: http://ssrn.com/abstract=1124991.
  18. 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 336:133–145CrossRefGoogle Scholar
  19. Grech D, Pamula G (2008) The local Hurst exponent of the financial time series in the vicinity of crashes on the Polish stock exchange market. Physica A 387(16/17):4299–4308CrossRefGoogle Scholar
  20. Greene MT, Fielitz BD (1977) Long-term dependence in common stock returns. J Financ Econ 4:339–349CrossRefGoogle Scholar
  21. Helms BP, Kaen FR, Rosenman RE (1984) Memory in commodity futures contracts. J Futur Mark 4:559–567CrossRefGoogle Scholar
  22. Hurst H. E., 1951. Long-term Storage of Reservoirs. Transactions of the American Society of Civil Engineers, 799 p.Google Scholar
  23. Hurvich CM, Ray BK (1995) Estimation of the memory parameter for nonstationary or noninvertible fractionally integrated processes. J Time Ser Anal 16:17–41CrossRefGoogle Scholar
  24. Jacobsen B (1995) Are Stock Returns Long Term Dependent? Some Empirical Evidence, Journal of International Financial Markets. Institutions and Money 5(2/3):37–52Google Scholar
  25. Künsch H (1986) Discrimination between monotonic trends and long-range dependence. J Appl Probab 23:1025–1030CrossRefGoogle Scholar
  26. Lento C (2013) A Synthesis of Technical Analysis and Fractal Geometry - Evidence from the Dow Jones Industrial Average Components. Journal of Technical Analysis 67:25–45Google Scholar
  27. Lo AW (1991) Long-term memory in stock market prices. Econometrica 59:1279–1313CrossRefGoogle Scholar
  28. Lobato IN, Velasco C (2007) Efficient Wald tests for fractional unit root. Econometrica 75(2):575–589CrossRefGoogle Scholar
  29. Los C (2003) Financial Market Risk: Measurement & Analysis. Taylor & Francis Books Ltd, London, UK, Routledge International Studies in Money and Banking, 460 pCrossRefGoogle Scholar
  30. Mandelbrot B (1972) Statistical Methodology For Nonperiodic Cycles: From The Covariance To Rs Analysis. Ann Econ Soc Meas 1:259–290Google Scholar
  31. Matteo TD et al (2005) Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development. J Bank Financ 29(4):827–851CrossRefGoogle Scholar
  32. Niere HM (2013) A Multifractality Measure of Stock Market Efficiency in Asean Region. European Journal of Business and Management 5(22):13–19Google Scholar
  33. Onali E, Goddard J (2011) Are European Equity Markets Efficient? New Evidence from Fractal Analysis. International Review of Financial Analysis 20(2):59–67CrossRefGoogle Scholar
  34. Peters EE (1991) Chaos and Order in the Capital Markets: A New View of Cycles, Prices, and Market Volatility. John Wiley and Sons, Inc, NY., p 228Google Scholar
  35. Peters EE (1994) Fractal Market Analysis: Applying Chaos Theory to Investment and Economics. John Wiley & Sons, NY., p 336Google Scholar
  36. Phillips PC, Shimotsu K (2004) Local Whittle estimation in nonstationary and unit root cases. Ann Stat 32:656–692CrossRefGoogle Scholar
  37. Phillips PC, Shimotsu K (2005) Exact local Whittle estimation of fractionalGoogle Scholar
  38. Robinson PM (1994) Efficient tests of nonstationary hypotheses. J Am Stat Assoc 89:1420–1437CrossRefGoogle Scholar
  39. Robinson PM (1995a) Log-periodogram regression of time series with long range dependence. Ann Stat 23:1048–1072CrossRefGoogle Scholar
  40. Robinson PM (1995b) Gaussian semi-parametric estimation of long range dependence. Ann Stat 23:1630–1661CrossRefGoogle Scholar
  41. Serletis A, Rosenberg A (2007) The Hurst exponent in energy futures prices. Physica A 380:325–332CrossRefGoogle Scholar
  42. Shimotsu K, Phillips PCB (2002) Pooled Log Periodogram Regression. J Time Ser Anal 23:57–93CrossRefGoogle Scholar
  43. Sowell F (1992) Maximum likelihood estimation of stationary univariate fractionally integrated time series models. J Econ 53:165–188CrossRefGoogle Scholar
  44. Velasco C, Robinson PM (2000) Whittle pseudo maximum likelihood estimation for nonstationary time series. J Am Stat Assoc 95:1229–1243CrossRefGoogle Scholar
  45. Velasco C (1999a) Nonstationary log-periodogram regression. J Econ 91:299–323CrossRefGoogle Scholar
  46. Velasco C (1999b) Gaussian semiparametric estimation of nonstationary time series. J Time Ser Anal 20:87–127CrossRefGoogle Scholar
  47. Velasco C (2000) Non-Gaussian log-periodogram regression. Econometric Theory 16:44–79CrossRefGoogle Scholar
  48. Zunino L, Tabak B, Garavaglia M, Rosso O (2009) Multifractal structure in Latin-American market indices. Chaos Solitons Fractals 41(5):2331–2340CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Guglielmo Maria Caporale
    • 1
    • 2
    • 3
  • Luis Gil-Alana
    • 4
  • Alex Plastun
    • 5
  • Inna Makarenko
    • 5
  1. 1.Brunel UniversityLondonUK
  2. 2.CESifoMunichGermany
  3. 3.DIWBerlinGermany
  4. 4.University of NavarraPamplonaSpain
  5. 5.Ukrainian Academy of BankingSumyUkraine

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