Author/Authors :
Shafiee، Mahboobeh نويسنده Department of Accounting, Mashhad Branch, Islamic Azad University, Mashhad, Iran Shafiee, Mahboobeh , Yazdi، Hoda Majbouri نويسنده Department of Accounting, Mashhad Branch, Islamic Azad University, Mashhad, Iran Yazdi, Hoda Majbouri , Panahi، Hamid نويسنده Department of Accounting, Bojnourd Branch, Islamic Azad University, Bojnourd, Iran Panahi, Hamid , Hesari، Hamid نويسنده Department of Accounting, Bojnourd Branch, Islamic Azad University, Bojnourd, Iran Hesari, Hamid
Abstract :
Most researchers conducted on stock returns have investigated the linear relationship between the independent variables and stock returns, and statistical methods. Today\ʹs world is a paradigm shift from classical modeling and the analyses - based on the basic initial model- to the development of models directly from raw data. Nowadays, with the advancement of information technology and entrance of artificial intelligence including support vector machine and decision tree into the field of scientific research, it has become possible to examine the nonlinear relationships between variables.
This study mainly aims to investigate the relationship between independent variables and stock returns using data mining techniques and it has tried to answer the question of whether a model can be presented to forecast stock returns using these techniques? The studied population is the companies listed on Tehran Stock Exchange from 2001 to 2008. Applying the existing data to the support vector machine, stocks returns is forecasted with accuracy of 92.16, which is better than the decision tree with 9 degrees of freedom with a probability of almost one hundred percent.
