Designing a model for realizing the probability of closing price manipulation in Tehran Stock Exchange

The confidence to market health improves their liquidity and efficiency which is an important matter to capital market and stock exchange. The effect of public confidence to the market on investors’ decision is as important as the risk within these markets. Higher risk leads to lower efficiency, dampens market improvement and finally actuates capital to parallel markets. The economic and political news and rumors will directly affect the changes of market index. The effect of information and rumors on investors is reflexed in price changes and trading volume. So stock price manipulators are motivated to propagate wrong information and get illicit profit.
In this research we study the concept of price manipulation, especially closing price, and introduce a model for realizing the probability of closing price manipulation. According to the results stock return, bid & ask price, trading frequency, trading volume and stock turnover determine the closing price manipulation. The relationship among these variables is investigated in econometric models. The Logistic Regression model is used to predict the probability of closing price manipulation. The sample is divided into two groups named manipulators and non-manipulators using run test and sign test. Then the logistic model is run on the basis of the results from these two tests. The estimated relationship confirms the research hypotheses.