Volume 11, Issue 40 (6-2020)                   jemr 2020, 11(40): 33-66 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Rezaei S, Mehara M, Souri A. Does Disclosure Lead to Lower Informed Trading and Symmetric Order-follow Shocks in the Tehran Stock Exchange?. jemr 2020; 11 (40) :33-66
URL: http://jemr.khu.ac.ir/article-1-2017-en.html
1- university of Tehran , sadeqrezaie@ut.ac.ir
2- Karegar Shomali Street, Faculty of Economics, Tehran, Iran
Abstract:   (2299 Views)
In financial markets, the symmetry of information and the homogeneous interpretation of information among traders is one of the main conditions for market efficiency, but these conditions are in fact violated. In this paper first; we accurately estimated the dynamic measures of trades stemming from information asymmetry and diverse opinions among investors indices by a hidden Markov model. Thereafter, we consider an event window of 21 days to investigate impact of information disclosure on that indices. For this purpose, we estimated the daily measures of probability of informed trading (PIN) and symmetric-order flow shock (PSOS) 32 Tehran Stock Exchange (TSE) stocks belonging to 11 industries of TSE during the period from 2015 to 2018. PIN is an indicator of asymmetric information risk and PSOS indicating diverse opinions among investors whose variations and intensity play an important role in price formation and stock liquidity. These results show that in most stocks that have higher market value experience less risks of asymmetric information and diverse opinions shocks than other stocks. Entirely, it appears that the average and the maximum of information risk and diverse opinions shocks at TSE are higher than in developed markets. Also, information disclosure decreases PIN for three days and increases PSOS for 10 days, significantly, but its impact on PIN is weaker than PSOS. Actually, in TSE, information advantage of some informed traders are independent of announcements as well as announcements causes opinion diversities to rise and stand up.
Full-Text [PDF 1332 kb]   (748 Downloads)    
Type of Study: Applicable | Subject: پولی و مالی
Received: 2020/02/10 | Accepted: 2020/07/21 | Published: 2020/09/22

References
1. Abada, D. & Yagüeb, J. (2012). From PIN to VPIN: An introduction to order flow toxicity. The Spanish Review of Financial Economics, 10, 74-83. [DOI:10.1016/j.srfe.2012.10.002]
2. Agudelo, D. A., Giraldo, S., & Villarraga, E. (2015). Does PIN measure information? Informed trading effects on returns and liquidity in six emerging markets. International Review of Economics & Finance, 39(C), 149-161. [DOI:10.1016/j.iref.2015.04.002]
3. Akerlof, G. A. (1970). The market for" lemons": Quality uncertainty and the market mechanism. The quarterly journal of economics, 83(3), 488-500. [DOI:10.2307/1879431]
4. Amihud, Y. (2002). Illiquidity and stock return: cross-section and time-series effects. Journal of Financial Markets, 5, 31-56. [DOI:10.1016/S1386-4181(01)00024-6]
5. Amihud, Y., Mendelson, H. (1986). Liquidity and stock returns. Financial Analyst Journal, 42, 43-48. [DOI:10.2469/faj.v42.n3.43]
6. Aslan, H., Easley, D., Hvidkjaer, S., & O'hara, M. (2011). The characteristics of informed trading: Implications for asset pricing. Journal of Empirical Finance, 18(5), 782-801. [DOI:10.1016/j.jempfin.2011.08.001]
7. Baker, M. and J, Stein. (2003)." Market Liquidity as a Sentiment Indicator "Journal of Financial Markets, 7 (3). [DOI:10.1016/j.finmar.2003.11.005]
8. Bień-Barkowska, K. (2013). Informed and uninformed trading in the EUR/PLN spot market. Applied Financial Economics, 23(7), 619-628. [DOI:10.1080/09603107.2012.741676]
9. Blasco, N., & Corredor, P. (2017). The Information Environment, Informed Trading, and Volatility. Journal of Behavioral Finance, 18(2), 202-218. [DOI:10.1080/15427560.2017.1308943]
10. Bortolotti B, De Jong F, Nicodano G.and S, Ibolya. (2006)." Privatization and Stock Market Liquidity" Journal of Banking and Finance, Social Scien Electronic Publishing. [DOI:10.2139/ssrn.686921]
11. Cappé O, Moulines O, Rydén T. 2005. Inference in Hidden Markov Models. Springer: New York. [DOI:10.1007/0-387-28982-8]
12. Cepoi, C. O., & Toma, F. M. (2016). Estimating Probability of Informed Trading on the Bucharest Stock Exchange. Finance a Uver, 66(2), 140-160.
13. Copeland, L., Wong, W. K., & Zeng, Y. (2009). Information-based trade in the Shanghai stock market. Global Finance Journal, 20(2), 180-190. [DOI:10.1016/j.gfj.2009.02.002]
14. Davallou, M. & Azizi, N. (2017). The Investigation of Information Risk Pricing; Evidence from Adjusted Probability of Informed Trading Measure. Financial Research, 19(3), 415-438. {In Persian}
15. DeLong, J.B., Shleifer, A., Summers, L.H. & Waldmann, R.J. Noise trader risk in financial markets, Journal of Political Economy 98 (1990) 703-738. [DOI:10.1086/261703]
16. Dey, M. K., & Radhakrishna, B. (2015). Informed trading, institutional trading, and spread. Journal of Economics and Finance, 39(2), 288-307. [DOI:10.1007/s12197-012-9249-4]
17. Diamond, D. W., & Verrecchia, R. E. (1991). Disclosure, liquidity, and the cost of capital. The journal of Finance, 46(4), 1325-1359. [DOI:10.1111/j.1540-6261.1991.tb04620.x]
18. Duarte, J., & Young, L. (2009). Why is PIN priced? Journal of Financial Economics, 91(2), 119-138. [DOI:10.1016/j.jfineco.2007.10.008]
19. Easley, D., R.F Engle, M. O'Hara and Liuren Wu, 2008, Time Varying Arrival Rates of Informed and Uninformed Trades, Journal of Financial Econometrics, vol. 6(2), 171-207. [DOI:10.1093/jjfinec/nbn003]
20. Easley, D., S. Hvidkjaer and M. O'Hara, 2002, Is information risk a determinant of asset returns? Journal of Finance. 57, 2185-2221. [DOI:10.1111/1540-6261.00493]
21. Engel, C. and Hamilton, J.D. (1990). Long Swings in the Dollar: Are They in the Data and Do Markets Know it? American Economic Review, Vol. 80, pp. 689-713. [DOI:10.3386/w3165]
22. Eom, K. S, Kang, J. and Kwon, K. Y. (2017). PIN, Adjusted PIN, and PSOS: Difference of Opinion in the Korean Stock Market. Asia-Pacific Journal of Financial Studies. V.46, Issue3.Pp 463-490. [DOI:10.1111/ajfs.12177]
23. Fama E.F (1970). Efficient capital markets: A review of theory and empirical work. Journal of Finance, 25 (2) (1970), pp. 383-417 [DOI:10.1111/j.1540-6261.1970.tb00518.x]
24. Gordon, N., & Wu, Q. (2018). Informed trade, uninformed trade and stock price delay. Applied Economics, 50(26), 2878-2893. [DOI:10.1080/00036846.2017.1412075]
25. Grossman, S. J., & Stiglitz, J. E. (1980). On the impossibility of informationally efficient markets. The American economic review, 70(3), 393-408.
26. Kandel E, Pearson N. 1995. Differential interpretation of public signals and trade in speculative markets. Journal of Political Economy. 103: 831-872. [DOI:10.1086/262005]
27. Kubota K., Takehara H. (2009). Information based trade, PIN variable, and portfolio style differences: evidence from stock exchange firms. Pacific-Basin Finance Journal, 17, 319-337. [DOI:10.1016/j.pacfin.2008.06.001]
28. Lai, S., Ng, L., and Zhang, B., 2014. Does PIN affect equity prices around the world? Journal of Financial Economics 114, 178-195. [DOI:10.1016/j.jfineco.2014.06.005]
29. Li, F. Li (2006). Do stock market investors understand the risk sentiment of corporate annual reports? Working Paper. [DOI:10.2139/ssrn.898181]
30. Lu, Y.C., and Wong W.K. (2009). Probability of information-based trading as a pricing factor in Taiwan stock market. International Research Journal of Finance and Economics, 33, 31-49. [DOI:10.2139/ssrn.1115419]
31. Marzo M. and Zagaglia P. (2014). Asymmetric information and term lending in the Euro money market: Evidence from the beginning of the turmoil. The Quarterly Review of Economics and Finance, 54(4): 487-499. [DOI:10.1016/j.qref.2014.05.003]
32. Mehrara, M. & Soheyli, H. (2018). Arrival Dynamics of Informed and Uninformed Traders into Tehran Stock Exchange. Financial Research, 20(3), 265-288. {In Persian}
33. Mehrara, M. & Soheyli, H. (2018). Estimating the Dynamics of Information Risk at the Tehran Stock Exchange. Economic Modeling Research, 8(32), 55-90. {In Persian} [DOI:10.29252/jemr.8.32.55]
34. Paparizos P., Dimitriou D., Kenourgiosb D. and Simos Th. (2016). On high frequency dynamics between information asymmetry and volatility for securities. The Journal of Economic Asymmetries, 13: 21-34. [DOI:10.1016/j.jeca.2015.10.001]
35. Preve D., Tse Y. K (2012). Estimation of time-varying adjusted probability of informed trading and probability of symmetric order-flow shock. Journal of Applied Econometrics., 28, pp. 1138-1152. [DOI:10.1002/jae.2302]
36. Raei,R., Eyvazlu,R.& Mohammadi, S. (2012). Calendar Effects of Insider Trading Probability. Securities Exchange, 5(18), 1-15. {In Persian}
37. Raei,R., Eyvazlu,R.& Mohammadi, S. (2013). Estimating Probability of Private Information Based Trade Using Microstructure Model. Financial Research, 15(1), 17-28. {In Persian}
38. Raei,R., Eyvazlu,R.& Mohammadi, S. (2013).Survey on Information Risk using Microstructure Models. Management Research in Iran, 17(3), 71-85. {In Persian}
39. Rahmanian,M. & Taleblo, R (2017). Measuring Probability of Informed Trading in Tehran Stock Exchange. Economic Modeling Research, 8(29), 73-98. {In Persian} [DOI:10.29252/jemr.8.29.73]
40. Sarkar A, Schwartz R. (2009). Market sidedness: Insights into motives for trade initiation. Journal of Finance 64: 375-423. [DOI:10.1111/j.1540-6261.2008.01437.x]
41. Schumaker R.P., Y.L. Zhang, C.N. Huang, H. Chen. (2012). Evaluating sentiment in financial news articles, Decision Support Systems, 53, Pp. 458-464. [DOI:10.1016/j.dss.2012.03.001]
42. Tetlock P. (2010). Does public financial news resolve asymmetric information? Review of Financial Studies 23(9), 3520-3557. [DOI:10.1093/rfs/hhq052]
43. Xu, L., Xu, L., Zhao, J., & Yin, X. (2020). Information-based trading and information propagation: Evidence from the exchange traded fund market. International Review of Financial Analysis, 70(1), 1-10. [DOI:10.1016/j.irfa.2020.101495]
44. Xu, L., Yin, X., & Zhao, J., (2019). Differently motivated exchange traded fund trading activities and the volatility of the underlying index. Accounting & Finance. 59(1), 859-886. [DOI:10.1111/acfi.12407]
45. Yan, Y., & Zhang, S. (2012). An improved estimation method and empirical properties of the probability of informed trading. Journal of Banking and Finance, 36(2), 454-467. [DOI:10.1016/j.jbankfin.2011.08.003]
46. Yin, X., & Zhao, J. (2015). A Hidden Markov Model Approach to Information‐Based Trading: Theory and Applications. Journal of Applied Econometrics, 30(7), 1210-1234. [DOI:10.1002/jae.2412]
47. Zucchini, W., MacDonald, L.L & Langrock, R. (2016). Hidden Markov Models for Time Series. London: Taylor & Francis Group CRC Press. [DOI:10.1201/b20790]

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Journal of Economic Modeling Research

Designed & Developed by : Yektaweb