Is the Extension of Trading Hours Always Beneficial? An Artificial Agent-Based Analysis

Article

Abstract

The extension of trading hours to provide more trading opportunities and improve price efficiency has increasingly been discussed. However, currently, stock market trading activity during the extended-hours session is quite limited. Thus, we should examine whether the extension of trading hours is effective in creating more trading opportunities and increasing price efficiency even if there are only a few market participants during the extended session. For this study, we build an agent-based market model and analyze the effect of extending trading hours. We find that although the extension of trading hours could increase daily trading volume, price formation and trading activity could be distorted if the number of market participants during the extended-hours session is limited. Specifically, the extension could result in more concentrated trading at the open of the regular trading session, greater divergence between market prices and the fundamental value of assets, as well as higher return volatility (especially at the open).

Keywords

Extended trading hours Agent-based market model Price efficiency Return volatility Trading volume 

References

  1. Abhyankar, A., Ghosh, D., Levin, E., & Limmack, R. J. (1997). Bid-ask spreads, trading volume and volatility: Intra-day evidence from the London Stock Exchange. Journal of Business Finance and Accounting, 24, 343–362.CrossRefGoogle Scholar
  2. Andersen, T., & Bollerslev, T. (1997). Intraday periodicity and volatility persistence in financial markets. Journal of Empirical Finance, 4, 117–158.CrossRefGoogle Scholar
  3. Barclay, M., & Hendershott, T. (2003). Price discovery and trading after hours. Review of Financial Studies, 16, 1041–1073.CrossRefGoogle Scholar
  4. Barclay, M., & Hendershott, T. (2004). Liquidity externalities and adverse selection: Evidence from trading after hours. Journal of Finance, 59, 681–710.CrossRefGoogle Scholar
  5. Brock, W. A., & Hommes, C. H. (1997). A rational route to randomness. Econometrica, 65, 1059–1095.CrossRefGoogle Scholar
  6. Brock, W. A., & Hommes, C. H. (1998). Heterogeneous beliefs and routes to chaos in a simple asset pricing model. Journal of Economic Dynamics and Control, 22, 1235–1274.CrossRefGoogle Scholar
  7. Brock, W. A., & Kleidon, A. (1992). Periodic market closure and trading volume. Journal of Economic Dynamics and Control, 16, 451–489.CrossRefGoogle Scholar
  8. Chen, S. H., Chang, C. L., & Du, Y. R. (2012). Agent-based economic models and econometrics. Knowledge Engineering Review, 27, 187–219.CrossRefGoogle Scholar
  9. Cont, R., Potters, M., & Bouchaud, J. P. (1997). Scaling in stock market data: Stable laws and beyond. In B. Dubrulle, F. Groner, & D. Sornette (Eds.), Scale Invariance and Beyond. Berlin: Springer.Google Scholar
  10. Easlay, D., & O’Hara, M. (1992). Time and the process of security price adjustment. Journal of Finance, 47, 576–605.Google Scholar
  11. Engle, R. F., & Bollerslev, T. (1986). Modelling the persistence of conditional variances. Econometric Reviews, 5, 1–50.CrossRefGoogle Scholar
  12. Fan, Y. J., & Lai, H. N. (2006). The intraday effect and the extension of trading hours for Taiwanese securities. International Review of Financial Analysis, 15, 328–347.CrossRefGoogle Scholar
  13. Foster, F. D., & Viswanathan, S. (1990). A theory of intraday variation in volume, variance, and trading costs in securities markets. Review of Financial Studies, 3, 593–624.CrossRefGoogle Scholar
  14. Glosten, L., & Milgrom, P. (1985). Bid, ask and transaction prices in a specialist market with heterogeneously informed traders. Journal of Financial Economics, 14, 71–100.CrossRefGoogle Scholar
  15. Hamao, Y., & Hasbrouck, J. (1995). Securities trading in the absence of dealers: Trades and quotes on the Tokyo stock exchange. Review of Financial Studies, 8, 849–878.CrossRefGoogle Scholar
  16. Harris, L. (1986). A transaction data study of weekly and intradaily patterns in stock returns. Journal of Financial Economics, 16, 99–118.CrossRefGoogle Scholar
  17. Hommes, C., Kiseleva, T., Kuznetsov, Y., & Verbic, M. (2012). Is more memory in evolutionary selection (de)stabilizing? Macroeconomic Dynamics, 16, 335–357.CrossRefGoogle Scholar
  18. Hong, H., & Wang, J. (2000). Trading and returns under periodic market closures. Journal of Finance, 55, 297–354.CrossRefGoogle Scholar
  19. Houstion, J. F., & Ryngaert, M. D. (1992). The links between trading time and market volatility. Journal of Financial Research, 15, 91–100.CrossRefGoogle Scholar
  20. Jain, P. C., & Joh, G. H. (1988). The dependence between hourly prices and trading volume. Journal of Financial and Quantitative Analysis, 23, 269–283.CrossRefGoogle Scholar
  21. Kyle, A. (1985). Continuous auctions and insider trading. Econometrica, 53, 1315–1336.CrossRefGoogle Scholar
  22. LeBaron, B. (2006). Agent-based computational finance. Handbook of Computational Economics, 2, 1187–1233.CrossRefGoogle Scholar
  23. Mandelbrot, B. (1963). The variation of certain speculative prices. Journal of Business, 36, 392–417.Google Scholar
  24. Mandelbrot, B. (1997). Fractals and scaling in finance. Berlin: Springer.CrossRefGoogle Scholar
  25. Merton, R. (1971). Optimum consumption and portfolio rules in a continuous-time model. Journal of Economic Theory, 3, 373–413.CrossRefGoogle Scholar
  26. Osaki, S. (2014). TSE looking at extending cash trading hour again. NRI Financial Research Paper “lakyara”, 78.Google Scholar
  27. Pagan, A. (1996). The econometrics of financial markets. Journal of Empirical Finance, 3, 15–102.CrossRefGoogle Scholar
  28. Palczewski, J., Schenk-Hoppé, K., & Wang, T. (2015). Itchy feet vs cool heads: Flow of funds in an agent-based financial market. Journal of Economic Dynamics and Control, 63, 53–68.CrossRefGoogle Scholar
  29. Wood, R. A., McInish, T. H., & Ord, J. K. (1985). An investigation of transactions data for NYSE stocks. Journal of Finance, 40, 723–739.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Tokio Marine Asset Management Co., LtdTokyoJapan
  2. 2.The University of TokyoTokyoJapan

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