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The influence of trading volume on market efficiency: The DCCA approach

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  • Sukpitak, Jessada
  • Hengpunya, Varagorn

Abstract

For a single market, the cross-correlation between market efficiency and trading volume, which is an indicator of market liquidity, is attentively analysed. The study begins with creating time series of market efficiency by applying time-varying Hurst exponent with one year sliding window to daily closing prices. The time series of trading volume corresponding to the same time period used for the market efficiency is derived from one year moving average of daily trading volume. Subsequently, the detrended cross-correlation coefficient is employed to quantify the degree of cross-correlation between the two time series. It was found that values of cross-correlation coefficient of all considered stock markets are close to 0 and are clearly out of range in which correlation being considered significant in almost every time scale. Obtained results show that the market liquidity in term of trading volume hardly has effect on the market efficiency.

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  • Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "The influence of trading volume on market efficiency: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 259-265.
    • Handle: RePEc:eee:phsmap:v:458:y:2016:i:c:p:259-265
    DOI: 10.1016/j.physa.2016.03.080
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    as
    1. Oh, Gabjin & Kim, Seunghwan & Eom, Cheoljun, 2007. "Market efficiency in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 209-212.
    2. Gu, Rongbao & Shao, Yanmin & Wang, Qingnan, 2013. "Is the efficiency of stock market correlated with multifractality? An evidence from the Shanghai stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(2), pages 361-370.
    3. Ladislav Kristoufek & Miloslav Vosvrda, 2014. "Measuring capital market efficiency: long-term memory, fractal dimension and approximate entropy," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(7), pages 1-9, July.
    4. Wen-Jie Xie & Zhi-Qiang Jiang & Gao-Feng Gu & Xiong Xiong & Wei-Xing Zhou, 2015. "Joint multifractal analysis based on the partition function approach: Analytical analysis, numerical simulation and empirical application," Papers 1509.05952, arXiv.org.
    5. 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.
    6. Kristoufek, Ladislav, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 194-205.
    7. Wang, Dong-Hua & Suo, Yuan-Yuan & Yu, Xiao-Wen & Lei, Man, 2013. "Price–volume cross-correlation analysis of CSI300 index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1172-1179.
    8. Cajueiro, Daniel O. & Gogas, Periklis & Tabak, Benjamin M., 2009. "Does financial market liberalization increase the degree of market efficiency? The case of the Athens stock exchange," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 50-57, March.
    9. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2010. "Cross-correlations between Chinese A-share and B-share markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(23), pages 5468-5478.
    10. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
    11. Bariviera, Aurelio Fernández, 2011. "The influence of liquidity on informational efficiency: The case of the Thai Stock Market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4426-4432.
    12. Muniandy, S.V. & Lim, S.C. & Murugan, R., 2001. "Inhomogeneous scaling behaviors in Malaysian foreign currency exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 301(1), pages 407-428.
    13. 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.
    14. Wang, Qing & Hu, Yiming, 2015. "Cross-correlation between interest rates and commodity prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 80-89.
    15. Vassoler, R.T. & Zebende, G.F., 2012. "DCCA cross-correlation coefficient apply in time series of air temperature and air relative humidity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2438-2443.
    16. 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.
    17. Grech, Dariusz & Pamuła, Grzegorz, 2008. "The local Hurst exponent of the financial time series in the vicinity of crashes on the Polish stock exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4299-4308.
    18. 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.
    19. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo & Fernandez-Anaya, Guillermo, 2008. "Time-varying Hurst exponent for US stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6159-6169.
    20. 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.
    21. Wang, Gang-Jin & Xie, Chi & He, Ling-Yun & Chen, Shou, 2014. "Detrended minimum-variance hedge ratio: A new method for hedge ratio at different time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 70-79.
    22. Sensoy, A., 2013. "Time-varying long range dependence in market returns of FEAS members," Chaos, Solitons & Fractals, Elsevier, vol. 53(C), pages 39-45.
    23. Liu, Li & Ma, Guofeng, 2014. "Cross-correlation between crude oil and refined product prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 284-293.
    24. 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.
    25. da Silva, Marcus Fernandes & Leão Pereira, Éder Johnson de Area & da Silva Filho, Aloisio Machado & Nunes de Castro, Arleys Pereira & Miranda, José Garcia Vivas & Zebende, Gilney Figueira, 2015. "Quantifying cross-correlation between Ibovespa and Brazilian blue-chips: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 124-129.
    26. B. Podobnik & I. Grosse & D. Horvatić & S. Ilic & P. Ch. Ivanov & H. E. Stanley, 2009. "Quantifying cross-correlations using local and global detrending approaches," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 243-250, September.
    27. Kristoufek, Ladislav & Vosvrda, Miloslav, 2013. "Measuring capital market efficiency: Global and local correlations structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 184-193.
    28. 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.
    29. Gao-Feng Gu & Wei-Xing Zhou, 2010. "Detrending moving average algorithm for multifractals," Papers 1005.0877, arXiv.org, revised Jun 2010.
    30. Wang, Yudong & Liu, Li & Gu, Rongbao & Cao, Jianjun & Wang, Haiyan, 2010. "Analysis of market efficiency for the Shanghai stock market over time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1635-1642.
    31. Liu, Li, 2014. "Cross-correlations between crude oil and agricultural commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 293-302.
    32. Zhi-Qiang Jiang & Wei-Xing Zhou, 2011. "Multifractal detrending moving average cross-correlation analysis," Papers 1103.2577, arXiv.org, revised Mar 2011.
    33. Barabási, Albert-László & Szépfalusy, Péter & Vicsek, Tamás, 1991. "Multifractal spectra of multi-affine functions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 178(1), pages 17-28.
    34. Bariviera, A.F. & Guercio, M. Belén & Martinez, Lisana B., 2012. "A comparative analysis of the informational efficiency of the fixed income market in seven European countries," Economics Letters, Elsevier, vol. 116(3), pages 426-428.
    35. Aurelio Fernández Bariviera & M. Belén Guercio & Lisana B. Martinez, 2014. "Informational Efficiency in Distressed Markets: The Case of European Corporate Bonds," The Economic and Social Review, Economic and Social Studies, vol. 45(3), pages 349-369.
    36. Xi-Yuan Qian & Ya-Min Liu & Zhi-Qiang Jiang & Boris Podobnik & Wei-Xing Zhou & H. Eugene Stanley, 2015. "Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces," Papers 1504.02435, arXiv.org, revised Apr 2015.
    37. Zebende, G.F., 2011. "DCCA cross-correlation coefficient: Quantifying level of cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 614-618.
    38. Zebende, G.F. & Filho, A. Machado, 2009. "Cross-correlation between time series of vehicles and passengers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4863-4866.
    39. Podobnik, Boris & Fu, Dongfeng & Jagric, Timotej & Grosse, Ivo & Eugene Stanley, H., 2006. "Fractionally integrated process for transition economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 465-470.
    40. Barkoulas, John T. & Baum, Christopher F., 1996. "Long-term dependence in stock returns," Economics Letters, Elsevier, vol. 53(3), pages 253-259, December.
    41. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    42. T. Di Matteo, 2007. "Multi-scaling in finance," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 21-36.
    43. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
    44. 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.
    45. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
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