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How does electronic trading affect efficiency of stock market and conditional volatility? Evidence from Toronto Stock Exchange

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  • Dutta, Shantanu
  • Essaddam, Naceur
  • Kumar, Vinod
  • Saadi, Samir

Abstract

The present paper investigates informational efficiency and changes in conditional volatility of the TSX before and after the implementation of an automated trading system on April 23, 1997. Using a battery of unit root, stationarity, as well as linear tests, we find that the introduction of electronic trading led to an increase in linearity dependence in TSX daily returns. In addition, when we examined the nonlinearity dependences using powerful econometric tests, we find that electronic trading has increased nonlinear dependencies in return series, which is the main cause of rejecting the Random Walk Hypothesis (RWH). Our results suggest that the automated trading system has negatively affected informational efficiency of the TSX. We also find evidence of long memory following automation which suggests that the introduction of electronic trading has increased the level of persistence of information and trading shocks.

Suggested Citation

  • Dutta, Shantanu & Essaddam, Naceur & Kumar, Vinod & Saadi, Samir, 2017. "How does electronic trading affect efficiency of stock market and conditional volatility? Evidence from Toronto Stock Exchange," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 867-877.
  • Handle: RePEc:eee:riibaf:v:39:y:2017:i:pb:p:867-877
    DOI: 10.1016/j.ribaf.2015.11.001
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    1. Carrion-i-Silvestre, Josep Lluís & Kim, Dukpa & Perron, Pierre, 2009. "Gls-Based Unit Root Tests With Multiple Structural Breaks Under Both The Null And The Alternative Hypotheses," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1754-1792, December.
    2. Nelson, Daniel B. & Foster, Dean P., 1995. "Filtering and forecasting with misspecified ARCH models II : Making the right forecast with the wrong model," Journal of Econometrics, Elsevier, vol. 67(2), pages 303-335, June.
    3. Fung, Joseph K.W. & Lien, Donald & Tse, Yiuman & Tse, Yiu Kuen, 2005. "Effects of electronic trading on the Hang Seng Index futures market," International Review of Economics & Finance, Elsevier, vol. 14(4), pages 415-425.
    4. 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.
    5. Baillie, Richard T & Bollerslev, Tim, 2002. "The Message in Daily Exchange Rates: A Conditional-Variance Tale," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 60-68, January.
    6. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    7. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    8. Sanford J. Grossman & Merton H. Miller, 1986. "Economic costs and benefits of the proposed one—minute time bracketing regulation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 6(1), pages 141-166, March.
    9. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    11. Chan, K. C. & Karolyi, G. Andrew & Stulz, ReneM., 1992. "Global financial markets and the risk premium on U.S. equity," Journal of Financial Economics, Elsevier, vol. 32(2), pages 137-167, October.
    12. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    13. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    14. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    15. Blennerhassett, Michael & Bowman, Robert G., 1998. "A change in market microstructure: the switch to electronic screen trading on the New Zealand stock exchange," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 8(3-4), pages 261-276, December.
    16. Nelson, Daniel B., 1992. "Filtering and forecasting with misspecified ARCH models I : Getting the right variance with the wrong model," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 61-90.
    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. Domowitz, Ian, 1990. "The mechanics of automated trade execution systems," Journal of Financial Intermediation, Elsevier, vol. 1(2), pages 167-194, June.
    19. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    20. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    21. Al Janabi, Mazin A.M. & Hatemi-J, Abdulnasser & Irandoust, Manuchehr, 2010. "An empirical investigation of the informational efficiency of the GCC equity markets: Evidence from bootstrap simulation," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 47-54, January.
    22. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    23. Frino, Alex & McInish, Thomas H. & Toner, Martin, 1998. "The liquidity of automated exchanges: new evidence from German Bund futures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 8(3-4), pages 225-241, December.
    24. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
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    2. Adamolekun, Gbenga & Sakariyahu, Rilwan & Lawal, Rodiat & Ahmed, Ammar, 2023. "Electronic trading and stock market participation in Africa: Does technology induce participation?," Economics Letters, Elsevier, vol. 224(C).

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    More about this item

    Keywords

    Automated trading; Random walk; Nonlinear dynamics; Conditional volatility;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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