Information Distribution and Informed Trading in Mixed and Islamic Capital Markets

  • Rahma Tri Benita Universitas Indonesia
  • Siti Damayanti Universitas Indonesia
  • Irwan Adi Ekaputra Universitas Indonesia
Keywords: Indonesia, informed trading, Saudi Arabia, SIAH, MDH

Abstract

The correlation between volume and frequency with return volatility can explicate the information distribution process and informed traders' transaction behavior in a stock market. In this study, the Indonesian stock market represents the mixed market, while the Saudi Arabian stock market represents the Islamic market. We find that 94% and 96% of sharia-compliant stocks in Indonesia and Saudi Arabia follow the Mixture of Distribution Hypothesis (MDH). Consequently, we may conclude that sharia-compliant stocks in both markets are informationally efficient. However, we find that informed traders tend to behave differently in both markets. In the Indonesian market, informed traders exhibit competitive behavior in 95% of shariacompliant stocks and strategic transaction behavior in only 5% of the stocks. In contrast, in the Saudi Arabian market, we find that informed traders exhibit competitive behavior in only 38% of the stocks and strategic behavior in 62% of the stocks. The findings suggest that social and religious contexts may affect market participants' behavior.

References

Arago, V., & Nieto, L. (2005). Heteroskedasticity in the returns of the main world stock exchange indices: volume versus GARCH effects. Journal of International Financial Markets, Institutions, & Money & Money, 15, 271–284. doi: https://doi.org/10.1016/j.intfin.2004.06.001

Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31, 307–327.

Bose, S., & Rahman, H. (2015). Examining the relationship between stock return volatility and trading volume: new evidence from an emerging economy. Applied Economics, 47(18), 1899–1908. doi: https://doi.org/10.1080/00036846.2014.1002885

Canepa, A., & Ibnrubbian, A. (2014). Does faith move stock markets? Evidence from Saudi Arabia. Quarterly Review of Economics and Finance, 54(4), 538–550. doi: https://doi.org/10.1016/j.qref.2014.04.002

Chan, K., & Fong, W. (2000). Trade size , order imbalance, and the volatility-volume relation. Journal of Financial Economics, 57, 247–273.

Clark, P. K. (1973). A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices. Econometrica, 41(1), 135–155.

Copeland, T. E. (1976). A Model of Asset Trading Under the Assumption of Sequential Information Arrival. The Journal of Finance, 31(4), 1149–1168.

Darrat, A. F., Rahman, S., & Zhong, M. (2003). Intraday trading volume and return volatility of the DJIA stocks : A note. Journal of Banking and Finance, 27, 2035–2043. https://doi.org/10.1016/S0378-4266(02)00321-7

Easley, D., Kiefer, N. M., & O’Hara, M. (1997). One Day in the Life of a Very Common Stock. The Review of Financial Studies, 10(3), 805–835.

Ekaputra, I. A. (2014). Impact of foreign and domestic order imbalances on return and volatility-volume relation. Asian Academy of Management Journal of Accounting and Finance, 10(1), 1–19.

Ekaputra, I. A., & Asikin, E. S. (2012). Impact of tick size reduction on small caps price efficiency and execution cost on the Indonesia stock exchange. Asian Academy of Management Journal of Accounting and Finance, 8(SUPPL.), 1–12.

Fama, E. (1970). Efficient capital markets : A Review of theory and empirical work. Journal of Finance, 25(2), 383–417.

Harris, L. (1987). Transaction Data Tests of the Mixture of Distributions. Journal of Financial and Quantitative Analysis, 22(2), 127–141.

Hong, H., & Rady, S. (2002). Strategic trading and learning about liquidity. Journal of Financial Markets, 5, 419–450.

Jones, C. M., Kaul, G., & Lipson, M. L. (1994). Transactions, Volume, and Volatility. Review of Financial Studies, 7(4), 631–651.

Karpoff, J. M. (1987). The Relation Between Price Changes and Trading Volume. The Journal of Financial and Quantitative Analysis, 22(1), 109–126.

Lamoureux, C. G., & Lastrapes, W. D. (1994). Endogenous Trading Volume and Momentum in Stock-Return Volatility. Journal of Business & Economic Statistics, 12(2), 253–260.

MSCI. (2018a). MSCI Arabian Markets Islamic Index. Fact sheet. Retrieved from http://www.msci.com/search.

MSCI. (2018b). MSCI Indonesia Islamic Index (USD). Fact Sheet. Retrieved from http://www.msci.com/search.

Omran, M. F., & McKenzie, E. (2000). Heteroscedasticity in stock returns data revisited: volume versus GARCH effects. Applied Financial Economics, 10(5), 553–560. doi: https://doi.org/10.1080/096031000416433

Purwono, Y., Ekaputra, I. A., & Husodo, Z. A. (2018). Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments. Computational Economics, 51(2), 295–321. doi: https://doi.org/10.1007/s10614-017-9692-6

Pyun, C. S., Lee, S. Y., & Nam, K. (2000). Volatility and information flows in emerging equity market: A case of the Korean Stock Exchange. International Review of Financial Analysis, 9(4), 405–420. doi: https://doi.org/10.1016/S1057-5219(00)00037-5

Ratsimalahelo, Z. (2005). Generalised Wald Type Test of Nonlinear Restrictions. IFAC Proceedings Volumes, 38(1), 100-105. doi: https://doi.org/10.3182/20050703-6-CZ-1902.02252

Sensoy, A., Aras, G., & Hacihasanoglu, E. (2015). Predictability dynamics of Islamic and conventional equity markets. North American Journal of Economics and Finance, 31, 222–248. doi: https://doi.org/10.1016/j.najef.2014.12.001

Published
2020-12-07
How to Cite
Rahma Tri Benita, Siti Damayanti, & Irwan Adi Ekaputra. (2020). Information Distribution and Informed Trading in Mixed and Islamic Capital Markets. International Journal of Business and Society, 21(3), 1333-1351. https://doi.org/10.33736/ijbs.3353.2020