Search published articles


Showing 2 results for Market Microstructure

Moloud Rahmaniani, Reza Taleblo,
Volume 8, Issue 29 (10-2017)
Abstract

The level of asymmetric information in financial markets is important for its impact on the market formation, price levels and its interaction with investment risk. Also, determining the optimal rules by policy makers and determining the trading strategy by investors is done according to the level of information symmetry in the market. In financial literature, many metrics have been developed to measure the asymmetry of market information. In recent years, another measure known as probability of informed trading (PIN) has been introduced to measure the level of asymmetric information, based on the framework of market microstructure. Larger PINs from 0 to 1 range indicate higher information asymmetry levels. In this study, using the Easley, O'Hara (1992) approach, the probability informed trading as a measure of the level of market information asymmetry for the 12 selected companies from listed companies in Tehran Stock Exchange is estimated. We used maximum likelihood to estimate parameters with R package. The results show that average of PIN varies from 0.35 to 0.4 for different companies.

Mohsen Mehrara, Habib Soheyli,
Volume 9, Issue 32 (7-2018)
Abstract

The aim of this study is to investigate the dynamics of information risk at the Tehran Stock Exchange (TSE). We estimated the daily probability of information based trade (PIN) for 22 stocks from 11 different industries of TSE over 4 years. The total average of the daily PIN for all stocks was 27% from 2013 to 2016. The lowest and the highest average of PIN estimates for individual stocks are 20.2% and 39.4%, respectively. In this research, the lowest and the highest daily PIN for individual stocks are estimated as 1.2% and 93.3%, respectively, which indicate that information risk varies substantially along time and there is a substantial need to use dynamic models to study this risk. Generally, it seems that the average and the maximum of information risk at TSE are much higher than in developed markets. Results showed that petrochemical and metal industries benefit from the lowest information risk and the highest is recorded for insurance and cement industries.


Page 1 from 1     

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

Designed & Developed by : Yektaweb