Simulating and Estimating Trade Probability Based on Informed Trading in Tehran Stock Exchange

One of the most prominent issues in financial markets is the effect of information asymmetry. Information symmetry proved to be one of the most important requirements of efficient markets. As a result, the risk of information asymmetry and the existence of inside information is one of the most effective risks for investors. The main purpose of this study is to investigate the level of information asymmetry on the Tehran Stock Exchange and also to investigate the accuracy of estimating the trading model based on the probability of informed trading model (PIN) using different trading classification algorithms. Accordingly, after selecting 40 shares of stocks present in Tehran Stock Exchange, which have been active more than 75% of the trading days of the market and using LR and EMO algorithms in the classification of transactions, the PIN was calculated and observed that the probability of informed trading had a considerable level (on average 0.25) in the Tehran Stock Exchange, which increased by moving to smaller volume deciles. Also, using the microstructure simulation method, it was observed that any deviation in the correct classification of trades affects the probability of informed trading and, as a result, can significantly affect the accuracy of the supervision system.