In this paper, trading symbols of the 30 largest companies listed in the Tehran Stock Exchange (TSE) were ranked based on the asymmetry information risk. Using the Ersan and Alici (2016) modified clustering algorithm (EA), we estimated the probability of informed trading (PIN) to measure the asymmetry information among traders for each trading symbol and trading day through a two-year horizon from 20th March 2015 to 19th March 2017. Furthermore, we used the analysis of variance (ANOVA) method to determine the source of variation in the estimated PIN. The results showed that the estimated PIN is less than 0.1 for 88.2% of the firms-trading days, and that is equal to zero for 60% of the firms-trading days. Symbol trade “MAPN” is traded with the status of full asymmetric information in about 75% of its trading days. Factor weekdays have no significant effect on changing the PIN index. The annual average of the estimated PIN index for the first year is significantly less than the second year. The effects of firm specification on the PIN value will be disappeared after one year.
Mirbagherijam, M. (2020). Ranking the Trading Symbols of the Largest Companies Listed in the Tehran Stock Exchange Based on the Probability of Informed Trade Criteria. Iranian Economic Review, 24(3), 567-589. doi: 10.22059/ier.2020.77638
MLA
Mohammad Mirbagherijam. "Ranking the Trading Symbols of the Largest Companies Listed in the Tehran Stock Exchange Based on the Probability of Informed Trade Criteria". Iranian Economic Review, 24, 3, 2020, 567-589. doi: 10.22059/ier.2020.77638
HARVARD
Mirbagherijam, M. (2020). 'Ranking the Trading Symbols of the Largest Companies Listed in the Tehran Stock Exchange Based on the Probability of Informed Trade Criteria', Iranian Economic Review, 24(3), pp. 567-589. doi: 10.22059/ier.2020.77638
VANCOUVER
Mirbagherijam, M. Ranking the Trading Symbols of the Largest Companies Listed in the Tehran Stock Exchange Based on the Probability of Informed Trade Criteria. Iranian Economic Review, 2020; 24(3): 567-589. doi: 10.22059/ier.2020.77638