Information disclosure by data mining approach

Abstract

Undoubtedly, one of the most important factors in the profitable securities stock market investment is timely and regulated disclosure of companies' information. Several standards affect transparency and disclosure of information but understanding and effect percentage of these factors on the level of disclosure is very complicated and beyond the investor time limitation and costs. This study aims to investigate the effective factors on information disclosure level of present companies in Tehran stock exchange market and is one of the first studies to have undertaken empirical investigation of the effective factors on the level of information disclosure of presence companies in Tehran stock exchange market, Iran. Doing so, effective factors on information disclosure in the securities stock market, had been investigated nationally and internationally in previous works, reviewed and 19 factors selected regarding Iran capital market conditions. After using data mining approach and specifically decision trees algorithm and determining most important factors, resulted findings show that Audit Organization factor (AO) is inversely related to good information disclosure while factors such as "Return of Assets (RS)", "Share Percentage of Major Shareholders (SPMS)", "Dept Ratio (DR)", "Chairman Position (CP) (bounded/non-bonded)" and "Share Percentage of Governmental Companies (SPGC)" have direct relationship with it. Analysis of poor disclosure rules, on the other hand, did not provide an appropriate model. © Indian Society for Education and Environment (iSee).